Breath, breathe, we breathe and see one another. Take that time right now. Breathe, look around the room, see one another. Unless your ancestors, bones, lie in this place, we all come from somewhere else. All of us. We've all arrived here. Some of us have settled more than others. Some of us have arrived on ships. Some of us by foot. Some of us by blood. The sky knows some of us more thoroughly than it does others when we are in this place. That doesn't mean that we are not welcome. It means that our place here on this land carries a responsibility. In the same way that when you walk into your grandmother's house, your boss's office, your classmates, your lover's bed, we all carry within us a responsibility to be good visitors. I've lost my language along the way. There are things that I used to know that I forgot. But there are things and ways of knowing that my bones know that my blood knows. And all of us have this knowing in us. Whether we recognize it or trust it, it exists. I was taught a long time ago in ceremony in the prairies that there are grandfathers that sing and whisper and speak to us, but we have to learn how to listen. Because in your hand is one of those grandfathers. I went to the lake on our behalf and I asked the grandfathers for help. I told them that there was going to be a room of people that may or may not know who they are. They may or may not understand the responsibility to be a visitor in this place on this land, under this sky. And would they consider coming with me and helping us to remember knowledge? In your hand is a way of knowing that your bones may have forgotten. Take a moment. Breathe. Hold that knowledge in your hand. Feel it warm. Your blood. Breathe. The people whose land we're visiting, they don't owe us anything. We've walked through these doors uninvited, all of us. We've chosen to make ourselves present. We've decided for people who aren't present that we are deserving of being here. We've made money. We've driven. We've flown in planes. We've made sacrifices to be here. But it's not your right to be here unless your ancestors' bones lie under the ground. You are owed nothing. And in that lies one of the grandfather teachings of humility. There is no shame that's necessary. There's merely an understanding of what our place is. That's all it is. It's a relationship that we have to ourselves. It's a relationship we have to ancient knowledge that we're all holding in our hands right now. Like it's no big deal. Breathe. We breathe and see one another. Or we don't. Breathe. We breathe and see ourselves. Or we don't. You all have names. The rock in your hand has a name. If you're lucky it will speak it to you. Breathe. Listen for just a minute. Receive. So my question is, how are we being good visitors? How am I being a good visitor? Whenever I enter a new space, a new room, a new circle, a new land or territory, a new body of water, in what way are you able, am I able to honor the relationship that exists, which is that I may or may not, I may or may not remember what I'm supposed to know. My father taught me a long time ago two things. He said, when you come to a new land, if you don't know who you are and if you don't know who the people are, find a rock. And I remember asking him, why a rock? And he said, because we're prairie people, we don't have a lot of trees. So you find a rock, he said, and you hold on to that rock and you ask that rock if you are welcome, if you can come and stay for whatever period of time that you're there. And the rock will ask you, what are you going to do to make this place a better place when you leave? In other words, he said to me, how are you going to be a better visitor? And I said, well, I don't know, how am I supposed to know that? And he said, well, part of it is because you've been invited there maybe or you're on holidays or you know somebody. So maybe you're there to visit, maybe you're there to teach, maybe you're there to receive teachings, maybe you're there for ceremony. So you just let that stone know what it is that's brought you to this place. So take a moment, breathe, close your eyes if you need to. Add your knowledge to the knowledge that sits in the palm of your hand. Why are you here? No, really, why are you here? Are you here to take? Are you here to save? Are you here to share? And only the stone needs to know. Breathe, breathe and see yourself. Whether you can hear it or not, the stones are asking, what are you here to do and answer that question? No one needs to know just the knowledge that exists in your hand. What are you here to do today, this week, while you're here on this land? We breathe and we see one another. Take a moment, look around the room, feel how the looking is different now that you have been seen. The other thing my father taught me, I mean he taught me a lot of things, but another thing that my father taught me was when you forget who you are, you go to a tree that tree knows more than you can even imagine. And our tree nation are memory keepers. So when you don't remember, when you feel ungrounded, when you do that with your head, he says you go to a tree and you ask that tree to help you. And you'll feel it, you'll be like, no, not the tree. So you wait, you find that tree and you ask that tree to help you. And when the tree gives its consent, you hold that tree. He says as much as you can, you hold your heart against that tree until you remember who you are. So today you've given knowledge, added a layer of knowledge to ancient knowledge that sits casually in your hand with a lot of power in this room right now. I don't know if you can feel it. And at some point, whether it's today or tomorrow or the next or the day you leave, at some point I would like to invite you to take the promise that you've placed in this stone of what you're here to do as we say, the work that you're here to do in a good way. And I'd like you to feel that promise by returning it to the land. If you can go down to the water, even better. But take that time, make that time, carve that time, go together. Ask each other, what did you do with your stone? I don't know, I didn't do anything. Again, there's no shame, there's no blame, but there is responsibility. So I invite you to enter into that space of responsibility inside all the other responsibilities that you have. And they are legion. I'm a single mom, I know, they're legion. It's okay. Take that time to give yourself ceremony. Take that time to breathe, to see yourself, to see the land, to see this place that you are being given to by, that you are taking from, that you've not been invited to. That owes you nothing. And remind yourself with a promise of what you are here to do in a good way and give that back before you leave. And if this whole time you've said nothing to the rock because you don't know that's okay, let the rock sit beside your bed when you sleep. At some point it will arrive. Why are you here? What are you here to do? And when that knowledge arrives, give it back. Let the land take care of it, let the land carry all those burdens, giving all that taking for you. And when you don't know who you are, there's some trees on this campus. They're pretty great trees. They're not like West Coast trees, but they're pretty great trees here. So if you see people hugging trees, it's a good thing. It's doing things in a good way. Breathe. We breathe and we see ourselves. We breathe and we see one another. We breathe and we know, even when we forget. Thanks so much, Lisa. You know when we first, in the earliest conversations we were talking about this conference, there were a couple of things that we very badly wanted to do. And one of them was that we felt that it was imperative that we address land acknowledgement, which of course is happening all over the place now. But everybody in this room, of course, would acknowledge that land acknowledgement is a kind of performance. And some of them are more compelling than others. And I would say some of the less compelling ones lack a sense of real presence, of sincerity, and of humility. And it's interesting that those are virtues that when you're teaching an acting course, those are things that you try to emphasize. But they have been lacking very often from the performance of land acknowledgement. And I guess I want to thank Lisa and Jen for modeling those, for teaching how to do that first. The other thing that we were sure of right from the beginning was that we wanted to have this event here at the Isabel Bader Center. It's a beautiful building, of course you've seen that. But in my opinion, one of the superb things about this building is the sensitivity which went into its design with respect to its place, where it's situated in the landscape, its relationship to what's all around it. And there's a lot to notice about that. But I won't talk about it. Instead what I would like to do is introduce Tricia Baldwin, who has been a terrific friend to us, a great friend to the dance school of drama and music, and a great friend to CATR for this conference. They've been incredibly supportive. So Tricia, would you like to come up and just say a few words about the Isabel? So Tricia Baldwin is the director of the Isabel Bader Center for the Performing Arts. Welcome everybody to this wonderful House of Dreams. And it's the home of music and drama and film and multi-disciplinary arts. And the future home of the Cataraokwe Festival for the Indigenous Arts that has been curated by Dylan Robinson. And Dylan's also working on a soundings exhibit with the Agnes-Etherington Gallery. So we feel very privileged to be here. And this center does have a wonderful soul about it. You see that the name is Bader. And Alfred Bader actually escaped from Nazi Europe through the Kindertransport. He went to England and then to Quebec. He went to apply to a university in the 40s and was told at a Canadian university, we filled our Jewish quota. Imagine escaping Nazi Europe and hearing that. He came to Queens and he was welcomed. And I think this was the first time in his life that he actually saw a future for himself after a tragic beginning. And many people do well in the world, but to Lisa's point, not everybody gives back. Sometimes they take, but Alfred is a person who actually did give back from such a tragic start to his life. He did give back and he did give back in a very transformational way. And as a result, this wonderful center, it's about 90,000 square feet, $72 million building. Every single room actually suits the art form and was acoustically built for the art form. And our students get to work on state-of-the-art equipment in a beautiful acoustic. We welcome the best artists in the world. We really have a big commitment to have a diversity in our programming and just a global look at the arts. We've championed Human Rights Arts Festival so that people can tell their stories. And I think that artists are just such powerful agents of change. And I know that's what you're going to be talking about at this conference. But any ideas that you have about powerful agents for change, please let me know because we're really growing so much here. And it's because of the great work that we're doing with people like Dylan and Lisa as well next year and beyond. And I just wish you the best conference ever because I know you're going to have a very engaged time at the center. So welcome and thank you very much. I have never received flowers from the stage. This is amazing. I'm not an actor by training. This is marvelous. Okay, I'm done now. Moving on, I would like to introduce Kim Solga, who is the general editor of Theater Research in Canada, and Tric is the sponsor of our keynote this morning. Just one moment. I was afraid Jen was going to have a password on here. Did the screen go to sleep? Showing here. There we go. See, that's why you got the flowers from the stage, Jen. Thank you so much to Jen and Craig for allowing me to occupy the stage for just a moment. And thank you to Lisa for that wonderful lesson in land association and connection. I really appreciated it. Jen noted I'm the general editor of Theater Research in Canada and we are sponsoring this session. It's a tremendous honor to do so. I just wanted to take a moment to let everyone know that our latest issue, the cover of which you see on screen, is about to be released. I'm really proud of this issue. I'm excited about it. It has, general issues don't really have themes, but this one sort of does. It's about teaching and mentorship and learning, both about writing and also about the way we teach and the way we engage with the texts in front of us from a variety of perspectives. It's got a couple of very senior scholars in it and a number of graduate students or recent graduate student scholars in it. So it takes the full spectrum of our work as scholars into account. And I really had a lot of fun writing the introduction just to reflect. It was an opportunity to reflect on my own experience learning how to edit. So I'm very happy to be inaugurating this issue, I suppose here. I want you to look for it in your inboxes soon if you've opted into digital but not print. If you have opted into print, please enjoy the print issue. And I just want to remind everybody that this is the first issue where we are actually going primarily digital in an effort, among other things, to redirect some of our not particularly fulsome resources away from the cost of cutting down and printing on trees and towards using our resources for human resources, spending more money on very much needed editorial assistants, very high quality editorial assistants and also creating some more digital stuff that you'll be enjoying on the website soon. Our web leader for this issue is actually one of our forum pieces reporting from the post margins, which is a fantastic report on the post marginal symposium that took place last April. It's a joint production of Natalie Alvarez, Rick Knowles and the Modern Times Theatre Company. It's in the issue obviously but it's also online with connections to gallery of photos, to video and other things. So please look out for that soon and thank you so much for reading and supporting theatre research in Canada as we continue to move ahead into the brave world of digital. It's now my tremendous pleasure to introduce Jill Carter, who is going to introduce Dr. Doline Tisawiyashi. Doline, have I said that correctly? Tisawiyashi Manning. Thank you very much. Oh, wait. Apparently Marlise is coming first. Is Marlise coming first? Marlise is coming first. All right. Sorry about that. Hang tight ladies. Here we are. Hello and sorry and apologies. My name is Marlise Schweitzer. I'm the president of CATR and I just wanted to take a moment to welcome you to this conference. I also want to really acknowledge the incredible work that Jen and Craig and your huge teams, your M teams, your local arrangements committees, your programming committees, all of your committees have done over the last year because I know you were on the stage or on the stage in Toronto a year ago and the planning had already begun. Thank you so much for that work and it's amazing to be here at the Isabelle having heard so much about how beautiful the Isabelle was and yes, advertising is true. This is a really big year for CATR, not just because we are here at the Isabelle but also because we'll be voting on incorporation at our AGM this coming Thursday. And hopefully you've had a chance as members to review those documents. I encourage you to do so if you haven't already. But please do attend the AGM if you can. Lunch will be provided as part of that and take part in what will surely be a really critical moment in our association's history. I also wanted to take a moment to acknowledge the many important conversations that have been happening in our field over the past year or so with respect to revelations of sexual harassment and misconduct. These have been incredibly difficult, necessary conversations and I know that they will continue for months and years to come. And as part of a larger effort to address these issues, the CATR board which is members of elected representatives or directors we have been undertaking a number of actions and this is an acknowledgement of important critiques by scholars like Sarah Ahmed who have pointed to the problem with statements that are non-performative and that statements that purport to do something but don't actually do it. And so we are really aware of that critique and are hoping to take actions that actually transform. And so some of these actions we've taken include the formation of a committee on conduct led by Erin Hurley with Roberta Barker and Kim McLeod. You'll hear more about their work at the AGM as well as yesterday the board affirmed statement of values which so you'll also hear a little bit more of that at the AGM as well. For now I just want to highlight two other events that that committee has coordinated. On Wednesday May 30th there's a workshop on sexual violence and harassment recognition response and prevention and then on Friday June 1st we'll be hosting a round table and discussion session on misconduct in theater studies practice and training. So please check the schedule for the times and locations for those events. Some of them have limited numbers of spots but please do attend if you can. And these events are just the beginning of what we hope will be at least a minimum of three years or more conversation and the way that CHR is hoping to you know consult with our members and engage in the years ahead. Finally just want to let you know if you want to know more about what the CHR board does we will be having a table upstairs just near the entrance. Various board members will be sitting there throughout the conference so please come and chat with us. If you're considering you know maybe at some point I want to be a board member. We have elections coming up you'll hear more about that soon at the AGM and so forth. Come and chat with us learn more about how you can become involved with the association. We only run because you know you are here supporting us. So just to conclude let me again just want to reiterate my thanks to Jen and Craig and your team and I hope you all have a really wonderful CHR conference. Thank you. It comes Jill. I'm just going to set up her tech. Annine Sego, welcome. My name is Jill Carter and it's a great honor for me to introduce my Niji, my good friend Doline Manning. I'm not going to spend too much time on her bio or her introduction because it is in your program schedule and we're running late they tell me. So I want to give her the platform because we've come here to see her. Doline has recently graduated with her doctorate from the University of Western Ontario in critical theory and she's going to tell you all about her work which is just amazing and crosses so many intersections. So without further ado, please welcome my Niji, Doline Manning. I'm going to say thank you for having me.  So I've left my computer over there off to the side of a feeling need that maybe there needs to be a more theoretical substance to support me. So I'd like to say thank you for having me here, for being on these lands, for the people of these lands. Lisa, I really was moved and loved that your presentation, thank you. I'm holding that ancient knowledge right here in my hand. I also, I'm not sure if I have it on me, it might be in my purse. I only have the one on me right now, I've one for Lisa also, but I want to give this to Joe Carter here. I've known Joe for a few years now, but not really well. We see each other from time to time, but it's been really a fantastic being together, really. And we're sharing a room, so it's a really good thing that we're both beautiful women. Because otherwise, we're both from the Three Fires Confederacy. I'm sure this morning we would have broken that peace treaty, fighting over who gets to use that bathroom. I conceded to her. So Joe gave a really fantastic land acknowledgement yesterday. I was able to attend and she talked about that red cloth, part of payment for these lands. So I have had these stones on me for over 20 years. They only come from one place in the States. I went down there, maybe it makes no difference what I went down there for. But those are those stones, they're medicine stones. And they're formed in the water, the way the water moves. And the red clay that's there, they can create these perfectly round medicine stones. And we know that the rocks are alive. And so I've had those things and I brought them all up really because I want to acknowledge my niece, Summer Cat. She's right now, she's out in the bush and put out for a fast. And so she's making a commitment to the people. She's going out, she's becoming a jingle dress dancer. And so when I couldn't be there, I was so sad I couldn't be there. And she was sad she couldn't be here. But we're there for each other. It doesn't matter our distance or the time between us. And when I touched that stone, I sent her one. And I was right away, I knew that was for her. And I was the same way, you know, when Joe was giving that talk, I knew this stone belonged to her. And like, so those things they don't, like we don't have ownership, let's say. We use those words, but they're particularly in English. We assume that it's innocuous, that it's a bridge in language, but it's not. We have to be mindful that it's a colonial language and it was imposed on us. So that even though that is the language, that is my first language in a sense, my mother was the first language, Ojibwe and Schnabem and Speaker. And so she taught me how to speak in English. And she taught me what those words and what those concepts mean. And it took me 40 years to realize that although I use the English language, that I'm actually, I'm not speaking in English. I'm speaking in the sense that I understand those languages, those concepts very differently. And those of you who come from that tradition, that history, that language, those languages, those European languages, and that philosophy comes along with it. You have a deep understanding, even if it's not on a conscious level, you have a deep understanding of the philosophical implications. And those things are, for me, they're at a distance. And many that I've yet to uncover. But in a like sense, having been taught by a first language speaker, that I have this other philosophical affiliation, I'll say, with the Schnabem one. And for me that's a way of being. And so, yeah, this stone is like those words in this philosophy. They're alive. And so we have, it's really important this initiative for language preservation and cultural indigenous cultural language preservation. And I fully support all the various methods that are being taken up in that regard. And whether that's through written language, there's lots of things that are now digital. But I also want to emphasize the necessity for indigenous communities to have access to funding to support those traditional ways of transferring knowledge, which is in community with other Anishinaabe. And that those funding sources are not, they do not come with stipulations. They are not like I, in full agreement, Joe was talking yesterday about this partnership, a community. And she talked about reconciliation. And she gave an example of the great law of peace. And by the Six Nations Confederacy. She made some really beautiful points about how for 3,000 years that there was proof that reconciliation can work. And I want to add to that, those people come from here. So they began with the same basis. So they're thinking in their heart, their flesh, they come from this earth. They were created from this earth. And even though they were born with one another, they were able to bring that peace about. So I'm interested in these different languages and these logic systems. And the English language, French language, which are the two official national languages in this country that call Canada today. But they are colonizing languages. So even our use of them has to be called into question and what those things mean. And I don't believe that reconciliation is possible between us without questioning and dismantling that system, those imperialistic systems of oppression. And they exist in all areas of this country. And from whether it's the military, the police, government, education, religion, even the family systems, there is a deep sense of imperialism and individualism. So when we signed these treaties, we understood it to be in a like sense in a similar way as the Six Nations came together. It was a two-way positive agreement. But that was never so on the part of the West. So we signed in good faith, but there was no to share. But that was never on the other side. So how can we possibly like to reconcile suggest that we were once friends and that we were met as equals. But that was never the case. So it is impossible. I don't believe it is possible at all. Unless those systems are dismantled. And a part of that is, you know, I'm here. I've been brought here in part because I have a PhD. That in itself is an epistemological injustice. I know I look young from my age. But I'm, you know, and finishing a PhD, I'm an old lady.  They're just kids. But for our people, we're often older because there's not a knowledge or an acknowledgement that we have to learn two systems. So we're learning what it is. We understand what it is to be in a Shinabe.  And even when we speak in English, there's, there's, there, we do not meet because there's a difference in our understanding. And I want to give you an example of that. That in my philosophy and in my theory classes, I would often get into a debate with one of my, one professor in particular. And he was always, you know, I couldn't understand why he was constantly seemed to be thrusting on to me like this notion of being. And I would, and I was making arguments about what is being. So you'd think, well, that's a very simple concept being, right? And, but it wasn't until I was like 40 years old that I realized, oh my God, they're being that in the West, they see being as static. It's like an essence that's always there. And it's never ending. And it's, so it's perfection. If something wasn't static, well, it could grow old. It could grow decrepit. It could, so, and you know, so I couldn't understand how can we not meet each other. It's so obvious being, but then I realized, like I had really no concept of that. No Xiaomi, I know those words, but it wasn't part of me. And that's what Joe, she was talking about, what is this bone, deep knowledge? Like we can talk and talk all day. And for years and years, and we have been, we've been talking for 500 years. And this isn't the first, this is not the first auditorium that have been witnessed to these discussions. I hope it's not gonna take another 500. And I hope we have another 500. But that, you know, for me, like I understood the world to be alive, everything, all of it. And that, so when I talked about being, you know, maybe it was a naive translation. I, you know, I think of being, well, like running. It's an ING, it's mobile, it's changing, it's active, it's dynamic. Because for us in our language, the majority of our language is comprised of verbs. So it is alive, all of it. So that notion of being a static is a difficult thing to penetrate. And it requires more than just head knowledge. It requires more than just intellectualizing. So, like my mother in all her years, she would ask me, what is it, what does this word mean, inanimate?  And she'd say, no. She'd say, from me to you. And what she meant by that was that, in the way that she understands the world, in the way that she taught me, that's how she wanted me to speak to her in return. So she could understand it. To not speak in the way of the white man, in the way they intellectualize. So, and where they come from is in this writing of our language, which has always been an oral language. And they often will articulate words or say objects as being animate or inanimate. And there's lots of debate over why in Anishinaabemowin there are things such as pots and pans which are considered to be animate and are pipes or drums. And depending on the dialect rocks. And in my dialect, where I'm from, they often say that it's one of, it might be the only one or one of few that I, first there are initially identified as being inanimate. And at other times, or certain zones of rocks are animate. And so, like I began at research with my mother from that simple place of if the rocks were alive. In what way am I alive and as a human? And if they're alive, do they die? And is that possible for me to die? And how do we live on or how do we, how are we in relation to the rock? And how do we talk back and forth to the rock? I just see my title. I think, oh, am I off topic? It's all related, it's all related. But yes, so that there's this moving back and forth where that, like when we move into these colonial languages which is for me now my only language. And I do speak some Anishinaabemowin but I'm certainly not fluent. But I had a great fortune to have a first speaking, language speaking mother who taught me the philosophy of the language and how it operates. And in that, that notion of, which is why she couldn't understand, why is it inanimate? And part of it is because that, when we're talking about nidol, that everything is endowed with nidol. Now we'll say, you might have heard, Getchimanitou. In my dialect we say Gozhem nidol. And when we talk about plural was the manidol. And there's all kinds of kind of variations of that translation. And that was anthropologist Hellowell who, I can't think of his first name right now, that who, Irving, Hellowell, he gave that translation of the other-than-human person. And a lot of people don't realize that. He's talking about the other-than-human. And there's no citation of where that comes from. And he worked with Anishinaabe since the 1920s anyway. And that's a translation of nidol. And that's his translation of nidol. He didn't, one could say he coined that, but it was a translation. And there's something, you know, when Anishinaabe, when indigenous people speak, we often don't have anything written down. I do lots of writing. It's just, you know, it's really pointless to pick it up. Because this is how we communicate is, you know, and we could say improvising. I was like, when are we not improvising? Except when we're reading, right? And so, you know, it's too, even in my discussion, I'm jumping all over in different places. You might at times, you know, see them as though it's unrelated, but given enough time, I'll bring it all back around and tie it in a knot for you. We won't have that time today, though. I'm waiting for the big hand to get out of here. So, where was I? Anybody tell me? Where? Oh, you want to hear about nidol? Okay. Yeah, so, like I was a small child, I might have been like seven. I asked my mom about, you know, like, what are they talking about? They're talking about their spirits. What are that? What does that mean? And she took me a window and she said, see that? What? All of it. Everything that you see, it's all alive. They're, you know, and they have to translate that word nidol as spirit. I don't say. I use that for convenience to communicate because that is often translated as such. But I think that is, for me, it becomes conflated too much with Christianity or with, what is it, new ageism. So when I asked her, what is this? She says, you know, like, that it's a closer interpretation from her understanding was a potency, a process, or energy. And so that gajem nidol is this ongoing, it's dynamic, and it's so, you know, we often talk about the creator or God. But for us, it's, you know, so when you take it out of those English interpretations, it's something that's much more complex. It's not just static and perfect. And there is a perfection there. And it's in that, those differences and the competitions, the places where there's a harmony and unison, but also in the competition. You know, I know we have competition. We have competition dances. We have competitive games.   But you have to, you know, we're not Christian. So you can't lay that Christian morality onto us. It's a separate thing. So, you know, like, so I think about that, this dynamic energy, right?  I often, you know, I give talks about where I grew up. In the home I grew up, I'm the youngest, 12. And we had no running water. We had an outhouse. I'd pump about a distance of a block behind our house. And we had no heat, but wood stoves. And, you know, and my mom, she married an Irishman.  And, but, you know, she had not only her kids, she adopted some too. But, you know, there are a lot of people that can't, oh, I can't, you know, take care of their kids there. You know, how do you talk about how I got my two kids? I can't do anything else. This woman had like 14 kids. You know, I would wash, close with her by hand. You know, we often had a ringer washer. But, you know, with so many people, like, they were often, you know, because they were just secondhand. And then no time, that ringer would break right off the bat. And then, you know, so we tied on a stick to close, you know. Sometimes, you know, she'd say, hold on the other hand, and we'd twist the clothes to ring out the water. I couldn't, but that woman, she was so powerful. She just twisted it right out of my hands, you know. And I wondered off topic again. So, what was I talking about again? Oh, you want to go back to that? Okay.  Let's see what we got here. Let's see if I got one that's right on spot. Okay, it talks about it, around about it, but maybe I just there say it. The inanimate. So, I want to say that, you know, even though we might personify it as though it's a person, right, that it's more than that. And that it's not even a, there's the rock, that one rock. But even my own hair is alive and separate from me. So, part of me and separate from me. And so, she's my teacher. She's my elder. And her and I, you know, we were always fighting, right? We were always pulling at each other this way and that. And, you know, if I don't take time, she's always telling me to slow down. Like Lisa, slow down. And so, if I don't, I'm rushing, you know, I don't take care of myself, I don't take care of my hair. You know, she'll get caught in the door, in my zipper. You know, she tells me, you're going to have to take time. She makes me stop. So, she likes to be, you know, like it's because you were hot when you just have one braid in the back. But also, I have to, when I'm not, you know, if I'm with my partner, I'll have her tie my hair in the back. But by myself, it's easier in the front. And so, I want to talk about that, you know, so it's both, you know, one could say it's animate, or it's inanimate, but it's also, it's alive. And it don't matter even if it falls. So, I'm taught that even our hair falls where we're supposed to pick it up. We're supposed to know where every hair is. That's about, you know, those teachings are about self-care, self-love. And I'll tell you, it's impossible. It's just, it's about, it's about the, it's about taking care of being of oneself. It's not really about the impossible, obsessive task of knowing where every one single hair is. I'll tell you, my house is carpeted with my hair. But I didn't want to go back, you know, to Lisa's point about responsibility. My mom would say that, you know, like in my home, it was a home without forgiveness. And that sounds harsh when you think about, you know, what you know in the West and Christian notions of morality. But when I would do something wrong, she wouldn't say, oh, you're forgiven. She'd say, don't do it again. And, you know, so it was over and over again. Don't do it again. And then I went to school. I didn't go to school until my eighth birthday. And so I went there and I saw the other kids and they're all saying, you know, they'd do something wrong and then they'd just turn to whoever it was. And they'd say, oh, sorry. And they'd say, oh, that's okay. You're forgiven. And then they'd do it again, do it again. So I got home. I said, oh, I got some new ammunition. So I'd go home and I'd do something wrong. And my mother would say, don't do it again. And I'd say, oh, well, you're not supposed to say that. And she'd say, what, why do you mean, what are you supposed to say?  And you say, you're forgiven. And you know, she laughed and she said, you know, I don't have that authority. I don't have the ability to grant forgiveness. And so she says, only the Nado can grant forgiveness. Only through the Nado are we let off the hook. And we know when that happens is when that harm has been rectified. And so we didn't have major crimes like we have today.  Because we know that that injury would not be easily healed. That would not, that we knew that whatever our crime was in that way so severe that I would have to give my life, my entire lifetime to take that back. And it would fall onto our children and their children to rectify that. And because that's when we know when you're fully restored to the place you were before that injury then you're forgiven, you're let off the hook. Oh my gosh, I think I'm getting a flag. Is that it? Oh my gosh. Gee, well, we all do that, right? We all are, we're always between. But I can say as a facilitator, I'll say an instructor, but someone who's working with others in teaching capacity. Well, one, we don't write. So, you know, we walk into a classroom and people are all talking and it's buzzing in the room.  Then everybody goes, falls quiet and maybe laptops and everybody's poised to record every word. And I tell them, you know, there's no exam in here. So I try not to have exams. I don't think that that's conducive to learning. Like, so if everything's alive and it's something in a verb base, so rather than thinking of knowledge as being an object that's out there, something that I can gather and own and put in my pocket to acquire, it's as I've been taught that it's something we become. So it's over time, not to say you can't and I'm going to go ahead and write.  Otherwise, we think about my laundry or my groceries, whatever. But yeah, so I mean, for me, that's one of the things is that, and talking about these different kinds of thought systems that in English language, it's primarily noun-based. So in a noun-based world, then you're also concerned with your individual nouns, right, that you acquire as opposed to a process of being in relation to. And that interrelationality doesn't end with human or what you consider to be animate plants, animals. But with absolutely everything, you know, she says, don't do it again. She's saying, you have to take responsibility and learn from those mistakes. You have to rectify them.  Well, we respect that life. We don't do that unless, you know, like those things there, they also offer themselves to us. So that, like, as humans, we're the youngest. We come here last, right? We say the rocks, they're our oldest people. So in comparison to their age, you can see how humans, we're infants. No matter how old, we're infants. That's why we're always messing up, right? You know, we're learning. But we have to learn. We have to not do it again, right? It's not enough. Oh, I'm sorry. That's okay. Do it again. Well, that's what that says, right? And so, you know, like thinking about those systems, like how do we address those larger systems? Even in a classroom, like this, like in our time, it's fraught with a lot of student anxiety. A lot of students committing suicide over exams and papers. I don't think that that's a healthy environment. In my classes, I mark students not against one another, but in their ability to make community, to see their gifts and others' gifts and to help each other. And so they're, you know, like those people who don't leave them behind each other, but help each other. So, you know, and I think that that's part of our responsibility is, you know, to teach that. And I think that that's something that's, you know, thinking about these different kind of pedagogical strategies that's different from Shogunash and Nishnabe. Because that's what we call the European Shogunash, which is, you know, someone say, well, it means white men. There's that word white and a man isn't in that word. What it actually identifies is British imperialism. So it identifies a way of being, a way of thinking. And similar to that, Nishnabe is a way of being together that is respectful. That we're Nishin, that's good. We say, ah, ah Nishin. We always remember life, that first breath, ah. That first breath when a baby's born, ah.  How are those ones coming? And we respect them always and everything. We say, ah, ah, oh, shu. So we, you know, and we know that it doesn't matter that life is a blade of grass. It's not a hierarchical. And similarly, ah, ah, ah, Nishnabe.  It's life-giving. Ah, Nishin. Nishin.  And, but I don't, I don't understand it in that same way as being gendered, but rather as a way of being. And that my mom would say, it's similar to the rooster. And ah, nabasa. Now that's a newcomer. That rooster was brought, imported here. So I think they, they, they recognized those attributes of that rooster. And they honored them with that name, nabasa. And so when we think about those, ah, those, ah, animate beings, those living beings and their, our elders, they teach us. We, we just look at them. What are they doing? How are they? And that's how we know ourselves. Nishnabe. That, so that rooster gets up first thing in the morning. Doesn't lay in bed. Ah, I think we'll take the day off. A dawn, break a dawn, that rooster is up and goes to the highest point. And, and from there looks all around. And so that nabasa is looking out for the community, for all members of the community. And, and it's going to sound an alert if there's danger. And then, you know, and then it's going to wake everybody up too. It's time to get to work, you know, whatever it is you want to do. And, but nabasa too is, is, ah, ah, beautiful. Nabasa has got, ah, all these beautiful feathers. He loves himself, preening, taking care of himself, right? And strutting around in the yard.   They were saying, oh, we're almost the only people of color. They'd say, oh, those manims, they think they're so good. They wouldn't stoop to pick up a silver dollar. They got their heads so high in the air. And, ah, yeah, it was, it's true. We were taught to love ourselves. But it's also about a necessity in the face of incredible, ah, oppression. This is how we survived. But also, these are our teachings. To take care of ourselves, to love ourselves. And that, and, and how can we love others? We can't even love ourselves. So this, ah, nabasa is, so we know that. Nabasa is, ah, is, doesn't, isn't, ah, kind of floats between the earth and the water. Earth and, you know, just wrap it up with, and the nabasa. So that nabasa goes between earth and, ah, and, ah, sky, right? So walks gentle. So, you know, it's the way you think about those, those, ah, and so for those, those are, ah, forms of, ah, animacies, right? And our teachers are elders. We just see how they are with one another. And, ah, ah, and so we see that in states, in, ah, for, instead of shaganas, they say jamokaman, which means, ah, the big knife. It's that, they're talking about that British saber. That's crooked. And also those words are, they're crooked. Lies, right? And they cut both ways. But that's, and that refers to, again, those British sabers. Those, those soldiers sabers. Ah, so, so today, I just want to deal with this, this, ah, notion that those, those systems of thought are still here. They're imperialistic. I'm thinking about my rights, as opposed to ours, all of us. You know, I'm going to see how I look on in all those chairs that are empty, that, that, ah, they seem empty, but they're, they're full. But all our, all our people are here with us. Ha, m'gwetch. So I want to thank you, Doolin, chi m'gwetch. I think there is a beautiful circle that happened this morning with this gorgeous land acknowledgement from Lisa, ah, to, to Marla's's cautionary notes and speaking about things, very serious things we're going to be speaking about at this conference, about disrespect, about harassment, about bullying in the professional arts world and the arts worlds that we work in, in the classrooms, about the pain and anxiety and this colonial violence that is iterated and reiterated and reiterated to the point where we have become the ciphers and Doolin is offering us some sort of answer. M'gwetch. Thank you all so much. There is coffee in the lobby and in the third floor. Lounge to the next session start at 11. Thank you.


Welcome everyone to Data Quality, the holy grail of great for our data-fluent organization by Balwinder Kaal Corona. So without any further delay, over to you Balwinder. Thanks Vijay and thank you everyone for joining. Very good morning, good evening, good afternoon to all of you based on wherever you are based off. And very warm welcome to Agile India 2022. So without wasting any time, I'll quickly start. So data quality, today I'll be talking about data quality and it is indeed a holy grail of any organization that wants to be a data-fluent organization. And aside of big data platforms and big data ecosystems, I think all of us have worked with data in one form or another. So let's keep it conversational, do pitch in with your comments, any questions that you have as we go. So last decade was the decade where every organization wanted to become a tech organization. And now almost every organization aspires to become a data-driven organization. All the enterprises have started collecting huge volumes of data from various sources from inside the organization, outside the organization. They are even collecting social media feeds and they are doing it in real time. And they hope to get insights from this data to make smarter decisions for their business. One of the biggest challenges in leveraging this data, however, is that not all of this data is useful, right? If I give a one-star review for any product and no text to support it, that data is pretty much useless for anyone who wants to use it, right? So the quality of data is not up to the mark. And even though we have made a lot of progress in the ways of implementing data platform, we have wonderful architectures. We have cutting edge tech stack to implement these data platforms. The fundamental issue of the quality of data flowing through these data platform is still there. So today I'll be talking about some of these issues. What are the causes of these issues and how can we fix these issues? I will talk about a data quality framework that we created and we've used that framework with a bunch of our clients. And we've seen how this framework actually elevates some of those challenges created by data quality. I will also briefly touch upon domain data boundaries and data platforms. And how can we shift left the data quality aspect of any data platform? And I'll do all of this using a case study so you will get more examples and more perspectives. So moving on a little bit about me. My name is Balwinder Khurana. I have 15 years of experience and I work extensively with data-driven systems. So creating solution data architectures for the clients, creating data platforms, working with them to create a data strategy for them. Currently I'm working as data architect in ThoughtWorks and I'm also leading the global data community in ThoughtWorks. So as I said, I've worked with multiple clients and majorly in the area of how data can accelerate or transform their business. But whenever we meet enterprise leaders and we talk to them, we often hear that they do not know the complete picture of their business and they do not know how to use data to join the dots. Some of them also say that they do not know if they can monetize their data. And even if they know they can monetize their data, they do not know how or they do not know what are the hurdles in their way in data monetization. Some of them fail to use data to differentiate themselves and stay ahead of competition. I think the worst part is some of them have said that their own teams do not trust the data coming out of the data platform. And they use the age-old methods of spreadsheets for finding out the insights or for decision-making. Some organizations, even though they have data available, their data is not usable for data science algorithms. So these are the things that we often hear. But if you look closely, all of these are symptoms. These are not the causes of data platform failure. These are essentially the symptoms why data platforms fail.  I think this is a very old and very cliched way of saying this. But you can build a very modern data platform with all the right set of tools and technologies in place. But if the data quality is not up to the mark, the analysis on data is not going to be up to the mark. You will see all of those symptoms that I just shown. And you will see that your teams have started losing trust in the data. So now let's start peeling the layers. Now we know the symptoms. Let's start getting to the causes. But before we do that, let me introduce you, introduce to you the case study that I'm going to use. So I'm going to use the case study of a retailer and retailer because all of us can quickly connect to the retail world. We've been using retail since long. So this retailer basically wants to price their articles. So they have been collecting a lot of data for some time now. And they feel that they can use this data to intelligently price the assortment of articles that they have. So data points like what is the demand of my article? How are the competitors playing with the prices of these articles? Does my article show any seasonal behavior? Using all of these and many, many more search dimensions and data points, they want to dynamically price their articles. However, as I said, businesses have very low trust in data in the data platform. Along with the solution, they also want answers to the critical questions that you see on the screen. So essentially, how do you measure the correctness of the prices? Basically, these are recommendations, right? So in order to measure the correctness of recommendations, you will have to measure many more data points and you will have to compare those data points against some of the SLAs that you initially agreed on and then establish the correctness of your prices. Essentially, what you're doing is you are validating the accuracy of your analytics. And as I said, untrustworthiness in analytics and insights is not because of the system which is generating these analytics and insights, but it is because of the quality of data that is getting fed to the analytics and insights, right? So in these big analytics systems, the data platforms and the data pipelines, data flows through multiple stages and there are a lot of transformations that are done on data. What we want to do is bring in transparency as data flows through these stages and then see how can this transparency establish trust with the data and insights again that we are providing to our business teams. For the analysts that are working with this data, for the development team that are working with this data, we want to enable them to discover and use the data that is being collected in various systems. So we want the discoverability aspect of data quality as well. We want to ensure all the compliances, any legal compliances, any regulatory compliances that we have. And the most important part, we want to find out who is going to own this data quality, who is responsible for ensuring data quality. So even if you have answers to all of the questions above, but you don't know who is going to take care of data quality issues and who's going to fix them and where they are going to be fixed, these answers are pretty much useless for you, right? So this is the use case that we'll be talking about and I'll use examples from here. So going back to the causes, we'd already seen the signs or the symptoms of data platform failure. But if you look inside the hood, insufficient data quality is because of certain systemic issues. And these systemic issues starts from here, addressing the data quality late in the process. So what happens is data teams, they spend disproportionate amount of time in tinkering with data quality in the downstream systems rather than the source system. This wastes time and affects the overall data quality. In my retailer example, let's say the prices and the sales that I used to feed into my retail pricing algorithm, they are incorrect to begin with. Fixing the data quality issues with the price recommendation coming out of the algorithm, it's not going to improve the overall quality. What also happens as a result of this is, because I'm fixing my issues in the downstream system, I lose a lot of context. And when I fix issues without context with a myopic view, I might create issues at other places. So I'll again take the example of this retailer, let's say I'm also generating some of the reports, right? So I have price information, sales information, I'm doing some aggregations and I'm generating some reports. And there could be some aggregated values that feel incorrect. Now, because I do not have any context, I don't know whether that is correct or not. Let's say there is one particular store that has run a short term discount on the prices. So the aggregate price is definitely going to be incorrect or it will seem incorrect. But if I attach that context of short term discount, then it is correct. So missing context also happened because of fixing the issues downstream. Most organizations work without any strategy. So they do not have an integrated process or framework which can fix the data quality issues in the entire data platform or the ecosystem. Now, having said this, we are not saying that just have one central place and fix all of your data quality issues there. What we mean is you should have a self-service framework which you can provide to the teams working with data to execute the data quality. So they are still executing with same strategy. We've also seen organizations do not invest a lot of time and effort in creating definitions for data. So each team which is working with data, they have their own definition and they fix the quality issues depending on that definition. And this leads to more trust issues in the data, right? Because at one place, because one team used a specific definition, you will see something at other place, you will see something else. As I said, because you're not addressing data quality uniformly in the organization, you do not have uniform definitions. The solutions that teams are creating for fixing data quality, they are point solution and they are getting looked at from the lens of viewer. Basically, the person who is going to use that data and not the person who is going to provide that data. So again, that price recommendation example, let's say you got some price recommendations out of the algorithm. Because you are going to consume this data and you feel that the recommended price are not correct or you feel that they are little off, you will start applying rules on the recommended prices. And now these recommended prices, you don't know whether they were incorrect because the input was incorrect or because the algorithm, the engine which is generating the prices itself is incorrect. So these point solution do not fix the data quality holistically. And the most important systemic issue that causes data quality failures is under its estimating the impact. You might feel that, you know what, this one KPI is incorrect and that is only one report which is consumed only by 10 people. So that's only impacting 10 people. But essentially what happens is teams start losing trust in the data platform. And in the longer run, it becomes an impediment to change management. So generally your data initiatives or your data platforms lead to change management in the organizations, right? So they would tell you whether your business process is going correctly or not. And if not, you should change it. But if you do not trust your data platform itself, you will not make those changes. So it's a huge impediment to change management within an organization. So what we are trying to say is treat your data as you treat your code, right? Apply the same rigor of quality on data as you apply on your code. So you would write the entire test pyramid for your code. You will test the smallest function to the integrated layer to the entire application. Use the similar rigor on your data as well. So now we've seen the symptoms and the signs. We've seen the causes also and now we want to fix them. But before we do that, let's look at the definition of data quality because that's how we know how to fix these issues. So data quality refers to ability of a given set of data to fulfill an intended purpose. Now because it is related to a purpose, it is important to note that the definition of data quality will keep on changing. So what is a good quality data today might not be so tomorrow because my requirement or my definition has changed, right? The analogy that I use is the potato quality in a fast food chain. All of us have been to fast food restaurants, right? And they make French fries with potatoes, right? To make French fries, my quality requirement is big round potatoes, right? So the purpose is making French fries quality requirement is big potatoes. But if my purpose changes, let's say I want to make mashed potatoes, this quality requirement is no longer valid, right? So as your requirements change, your data quality definition would keep on changing. So it is important to remember always the purpose for which you are going to use your data. Furthermore, if you double click into this data quality definition, there are multiple dimensions of data quality. If you work with data-driven systems, if you work with data platform, you would have encountered some of these dimensions while talking about data quality issues. We can say that these dimensions form the tactical definition of data quality, right? And this is also ever-changing. As your requirements change, the dimensions will also change. So at one point in time, you might be talking about how relevant is your data for your problem versus some other point in time you might be talking about reliability of your data. If you're working with near real-time, real-time reports, you might be talking about availability or timeliness of data, right? So there are further and more such dimensions. How usable is your data? Is your data following standard rules or not? Is it trustworthy or not? Is your data consistent over time? Is your data integrity preserved? Is it being unique, right? So all of these dimensions form the tactical definition of your data quality. These can be unpacked further, so you can go one level deeper again. So there are multiple tenets to each dimension. So let's take the example of availability. We say that the data should be available, but what does it actually mean? For data to become available, it should be accessible. The user should be able to navigate to data and it should be available within time. There is no use of data if you wanted a report today and you are getting it tomorrow. And you should be authorized to see that data. You should be authorized to access that report. So there are multiple such tenets that form one dimension of data quality, right? And again, going back to the purpose, you need to figure out what tenets and what dimension is applicable to you. Cool. So now we have a complete understanding of what we want to do and why we want to do it. Someone might think that data has always been important, right? Even with the transactional systems, you want to ensure that your data is of high quality. All of our relational databases are also used to have this as their selling point where they would say that they are asset compliant and the data quality is preserved some of those dimensions from asset you would see here as well. So why is it that we are talking about data quality so much now and why we are so deliberate and intentional in talking about data quality? I think when it comes to big data ecosystems, the characteristics of big data themselves add to the complexity of data quality and the impact of incorrect data, the impact of incorrect insights is also very huge. As we said, data platforms are agents to change. So if that agent itself is providing me incorrect insight, the impact is going to be really, really huge and across the organization. So let's look at some of the characteristics of big data ecosystems and how it makes data quality complex. I think most of you would be aware of these four weeks of big data. Now there are seven, but let's talk about these four. So the first one is volume. When you have let's say hundreds of records, hundreds of thousands of records is easier to run comprehensive data quality checks on top of that records, right? You can go to each record and validate if it is correct or not. When you are dealing with petabytes and gigabytes of data for a giant e-commerce retailer, which is our use case, the platform generates data of orders of gigabytes per second and then you cannot run comprehensive data quality checks on the entire data. Sometimes enterprises start working with approximation. So what they'll do is they'll take a batch of data and they'll do some aggregations and they'll try to see if the data quality is correct or not. So they'll use probability, they'll use confidence intervals. However, when they do this, what also happens is they also start to approximate metrics. So they'll say, okay, 90% is okay or 80% is okay. This compromises with data quality. Then as I said in the beginning, enterprises are collecting data from various sources. So you have variety of data. For an e-commerce retailer, it could have data about a product which could consist product images. It could have customer reviews, which could be text reviews, which could also be images and videos. It could have transaction records. So there are different types of records. It's no longer a structured RDBMS, right? And you need different ways to ascertain the quality of these different types of data types. Then you have velocity. Every enterprise today wants to be real-time or near real-time. So how do you take care of quality without compromising the timeliness of your insights? You might want to just check the structural validation of your data. You cannot do semantic validation in that short amount of time. And then there is veracity. I think veracity is the most complex facet of big data. Veracity refers to inherent impreciseness or noise in the data, right? And most often you will see veracity in situation when there is lot of human data entry, right? So for example, for this retailer in a store, you will see a lot of point of sale terminals where you will swipe the power code and the entire information of the sale, which is like price and discounts using code scanner, is sent to the main system. And it is accurate. But a lot of time manual entries are done and these manual entry sales transaction could have errors. And why veracity is complex is because you do not have any direct ways to identify such errors or such inaccuracies. So essentially how do I validate petabytes of data for my retailer who is sending me millions of records, millions of text reviews, images, and they are doing it per second and they also have lot of veracity inside the data. So that's what makes data quality complex in the big data world. So now let's talk about the data quality framework. We've seen that data quality is an integral part of any data platform. And with the right data quality baked into the system, we can answer a lot of questions that enterprises have been asking. We saw those questions. We can also avoid a lot of failure scenarios that we saw earlier. And we can build the lost trust back into the data and in the data platform. And to do this, we need a very comprehensive data quality framework, which I will talk about now. So going back to the data quality definition, we said that data quality definition is attached to a purpose. We also saw when retailer, in the retailer use case, most of those questions were attached to the purpose, the purpose of pricing, right? So that's where your data quality framework also begins. So at the top of this data quality framework, you have your data quality definition based on the purpose. So here the purpose is pricing algorithm. You can have many more use cases and depending on each use case, you will have a different data quality definition. This is a hierarchical data quality framework. So at one end of this data quality framework, you have data quality definition depending on purpose. We call it fit for purpose. And on the other end of this framework, you have your baseline data qualities, or we can also call them as sensible defaults. The way to think about these data quality rules is this is a common denominator, right? So irrespective of the purpose that you're going to use your data for, these are the quality rules that you would always want in your data, right? Something as a numeric field cannot have alphanumeric data or an email field should have a certain standard. All of those rules becomes your sensible default or baseline data quality. And now you want to move from this baseline data quality to your fit for purpose data quality. And you do that using a critical path. So what do we mean by critical path? We saw that data quality has multiple dimension. Each dimension also has a lot of tenets. If you want to fix the data quality issue across each dimension, you are going to invest a lot of time, you are going to invest a lot of effort, and you might not even use all of those dimensions in your purpose. So the idea is to just do enough and that is your critical path. And when you move from baseline to fit for purpose using critical path, you generate intermediate layers of data quality, right? So there could be certain purpose which do not need so high data quality standards, something like ad hoc analysis, right? So that sits in between and that forms another layer of your data quality. Now, each layer in this data quality framework also has things going inside it, right? So how do you know that for each layer, whatever data quality dimensions I have chosen, where do I want to be in terms of those data quality dimensions? So let's say I say that timeliness is my dimension. But how do you measure it? Getting data within one day or getting data within one hour, what is your timeliness requirement? So you need threshold or metrics for each of these dimensions to ascertain that whether you have those threshold or not, you have some rules. So you would say that although I need data which is not older than one day, but at times I am ready to accept data for two days, so that becomes your threshold. So you create your rules.  So you would say that most of my data I received in one day, but there were let's say these 10,000 records that I received later and this was the reason of getting these records later. Or if let's say accuracy is one of your dimension and you say that I want to be 90% accurate and you could say in the report that most of my records are correct. Some of these records have some erroneous values and this sort of reaches to 89%. So that sort of reports you will start getting and now you want to know that from 89% you have to go to 90% or from 1.5 day of delay you want to go to one day of delay. So that feeds into your data quality improvement. So this is how you improve the data quality for each layer. And those are the loops, the data quality improvement loops that you would have for each layer depending on the dimension for each layer. And this completes my conceptual data quality framework. Definitely it's a big data ecosystem and this framework cannot exist in isolation. So there are pillars that support this data quality framework. All of this falls into a bigger umbrella of data governance. However, just to talk about a few, you have data discovery. So as I said, development teams would want to know where is a specific data stored. If I'm using AWS buckets, what is my bucket location for prices data? What is my bucket location for sales data? Can I navigate to that bucket? If some new data is onboarded into my S3, what is the location of that data? So that is all your data discovery. You need repository and indexing services. So it talks about metadata of your data. So what is the schema? If I'm using prices information, how does a record look like? What is the relation? How is price related to sales? What is the lineage? Then you need metadata service. So these are the services or the API calls that would help you manage your metadata. So with all of these data points that you're storing, you also need semantics. So how do I attach business glossary to my data? How do I attach technical metadata? How do I attach lineage? And most important of all is the ownership of data quality. So if I find any issues in the data quality, who is going to fix that? Which team is going to fix it? What are they going to fix it? What are the SLO, SLA for each of these different layers, right? And the ownership of data quality is not restricted to the data platform or this data quality framework. It goes beyond this to the business process as well. So you might figure out an issue which would tell you that you need to fix your business process. So that's where ownership comes in. Cool. So I think that was a little heavier and let's try to understand the entire conceptual framework again using a retailer example. I will also talk very briefly about domain data products here. So traditionally in organizations, data users and data providers are different groups, right? So there is one group which maintains your data platform. And there are other groups which maintain your operational systems, your transactional systems. So transactional systems are generating the data and data platform is using the data, right? Both of these groups could also be from different organizations, right? So they have different goals, different operational procedures. And therefore, their notion of data quality is also different. So data providers, a lot of times they do not know how the data users are going to use their data or what are the business use cases. A lot of time they don't even care, right? And this disconnect between data providers and data users is one of the prime reason behind data quality issues. And the way we try to fix this is by defining domain data products. What we are saying is make one team entirely responsible for this whole thing, providing the data as well as consuming the data. Because this is a single team working on the entire domain, they would also understand what are the data quality rules that this domain should adhere to. And this concept of domain data products and creating a data platform using domain data products is called data mesh. If any of you needs more information, you can reach out to me, but essentially that's the idea of dividing the ownership. And because you're dividing the ownership, it aids in your data quality and we will see how. So for the retailer, let's say these are some of the example domain data products that I have picked up. Articles, which is the information about article, article name, any code if the retailer uses codes for articles, category, hierarchical category to which article belongs. Then article price. So what is the price of article in let's say a store in Pune versus what is the price of article in a store in Delhi or what is the price of article on my website. Then sales, what is the sales of article, this is in voices data, competitor prices, how is competitor pricing the same article. All of these are your domain data products. And now you would have your quality rules defined according to your domain. And these quality rules, if you go back to my data quality framework, these are the baseline data quality rules you want to adhere to these quality rules irrespective of purpose. So baseline data quality rule for article could be that article has a fixed category. So let's say I have categories like edible, non-edible, within edible I will have let's say fresh vegetables, packaged food, meat, dairy. So every article should have a fixed category from this predefined set of categories. It cannot have any random category because I cannot handle that. So that's the baseline data quality rule. Then there is article price. The data quality rule can say that I don't want any negative prices. That's illogical. So no negative prices. Or I can say that there should be a unique price point. So at a given point in time, I cannot have an article sold at Rs 1000 and at Rs 2000 as well. So there should be a unique price point. For sales now, let's say there are return sales. And as a retailer, the return sales also is a line item in my sales data. For return sales, the total amount would definitely be negative. So you see the difference because of domain. For article price, I was not allowing negative prices, but for sales I can allow negative values. So that's how your domains aid in the data quality. You are more clearer and more intentional in your data quality rules. Now you can combine some of these domains to create more domains which would feed into your eventual use case. So here going back to my use case, my use case was dynamic pricing algorithm. And I need article prices as well as sales data to come up with the price recommendation. Because I want to see how sales change if I change my prices. Now here at the bottom layer, we were talking about baseline data quality rules because we did not even know what the purpose is. But now we know the purpose here and we will now talk about data quality rules based on purpose. Purpose is dynamic pricing algorithm. So my data quality rule can say that there should be no outliers in the price. So there should be no very high prices or very low prices because that is going to skew my algorithm. But let's say I'm using the same data for another purpose. The purpose here is reporting. In this case, the data quality rule of outliers is no longer valid because I definitely want to see the outliers and fix those outliers. So the purpose defines my data quality rule. And that's how you fix you fit the entire data quality framework using purpose and baselines. Now we have seen how data quality works from one lens, which was a hierarchical framework of moving from baseline to purpose. Definitely when you actually implement the data platform, there is another lens of looking at data movement, which is from source to insight. So these are the technical boundaries of your data moving through the entire platform. And this is where we start talking about shifting left of your data quality. We saw in the systemic issues of data quality that the failure happens because we are fixing the issues in downstream. So if you had some data quality issues while you are actually ingesting it from source. The source itself was giving you wrong data and you try to fix it while you try to extract some information from that data. You lost all of that context. You are working with data that you don't completely understand and you might not be able to fix it correctly also. So we are saying that try to identify the data quality issues as early in the process. So at each of these process, source, ingestion, storage, information, you run your data quality rules. Again, you use the same hierarchical framework, but you run the data quality rules at each of these transformations. You figure out what are the issues and you try to fix those issues there itself. So some of the examples of such data flow could be this. So when you have not even started your ETL, you have just ingested the data, you would want to check for format. So if I'm expecting JSON data from any source, if I encounter binary data, that's a data quality check failure for me and I want to fix it. I would ask the source like why are you giving me binary data or I would check for completeness of the data. If I'm running batch pipelines every 24 hours, I would want to confirm that within 24 hours, the number of records that I'm consuming is equal to the number of records that the source is providing. So you do that reconciliation. After you consume all of this data, you have ETLs, you have simulations, so you would have certain checks over there. You would see that your data transformations are completely working correctly or not. You could also write your unit test to check your transformation functions. So now you start also creating your data quality test pyramid as you have your code quality test pyramid. You will check for data completeness again. You will check for correct metadata getting generated. For your data science and algorithms, you would also check the validation of your model. For aggregation, you have validations for all the aggregations that you're doing. And even at the consumption layer, you will have UI validation. So you will have validation for representation. So if you're using date and the SLA is to use date in DD, MMY format, you will have that data quality check in place. Or you will also see how intuitive are your reports. So all of these checks keep on happening as your data flows through your pipeline. And I think this is also one crucial bit. We talked about continuous data quality improvement loop in each of my layers in that framework, the quality framework. And this is essentially the double click in that loop. This is very similar to how you would operate in the software world, right? So you would plan something. After you plan, you will assess and then develop. After you have developed your software, you will analyze this software, whether it confirms to the plan or not. And then you will keep on maintaining it. Similarly, if you want to operationalize the data quality, the first thing you want to figure out your goals of collecting data. Remember that data quality is defined using a purpose. So we want to know what is my goal of collecting this data. Depending on the goal, I will figure out which data quality dimensions are applicable out of those 10, 20 and many more such dimensions. I will figure out which dimension is most applicable for this goal. And then I will figure out KPIs. So earlier I was giving the example of accuracy. So I could say that for this goal, I want my data to be really accurate. And currently the KPI that I want to operate on is 90% accuracy. Okay. And then you create your evaluation baseline. Sometimes you also do a quick pilot to see that if this data is way off. And if it is way off, there is no use of creating a data platform, you would actually want to fix that first. But with that quick pilot, you will basically do feasibility check of creating the data platform.  And that assessment would basically tell you whether you are satisfying your goals or not. If not, you go back to the step of probably collecting more data if required and if not cleansing the data furthermore. So you do that until you reach your evaluation baseline. Once you satisfy your goals, you are good to go ahead and use that data for your purpose, the eventual purpose. Important thing to note here is you are always generating your data quality report. Whether or not you satisfy your goals, you need to generate those data quality reports to give you the direction in which you should move ahead. And this data quality life cycle is like not done once and it is done. It is a continuous loop. It is a continuous improvement data quality life cycle. Once you complete one iteration of it, you might have new goals, right? Or you might have new baselines as well. So you said that I wanted to be on 90% accuracy, but now I have made certain changes and now I want to be on 95% accuracy. So you get into another cycle of this data quality. So just summarizing, you're trying to identify the data quality issues and rules. You're trying to quantify them, prioritize which ones you want to fix first based on your goals and then mitigating those. So that's the summary of operationalizing data quality and that's what I would like to leave you guys with. I think that's what I had for data quality. Any questions, suggestions, any thoughts? Thanks Balwinder. I don't see anything in the chat or comments or Q&A section. Thanks a lot everyone. Thank you.


This study investigated whether creatine supplementation could enhance the protective effects of exercise against doxorubicin-induced hepatotoxicity in mice. The results showed that doxorubicin caused hepatotoxicity characterized by increased levels of inflammation, oxidative stress, and fibrotic changes. However, exercise alone partially protected against these effects, and when combined with creatine supplementation, it further enhanced the protective effects of exercise. This suggests that creatine supplementation can be used to potentiate the beneficial effects of exercise on liver health. This article was authored by Lorraine R. L. Costa-Gaudenho, Paula S. Sela, Tatiana A. Esquimares, and others.


Lately I've been giving thought to the current dating marketplace, and I call it the dating marketplace because it really is a marketplace ever since Smartphones activated the opportunity to connect with people through a swipe Environment and if you think back to before electronics, you know You actually had to meet people in real life for the most part although there was when I was in the 90s There was 1900 numbers and there was the personal ads and such I mean and I used it a couple times Then there was video dating services out there, but prior to that you just had to meet people organically, right? So, you know the the environment to connect was so different in the past than it is today And for many of us who are midlifers, which is after baby making years and before retirement You know we remember a time in real life how it was so different And I look at someone like my son who was only known electronics for meeting people although that's not really true because in high school He met you know, he had a girlfriend and in college you had a girlfriend, but certainly since then as an adult Okay, so the conversation I want to lean into is the topic is dating courting or just hooking up because With the swipe environment We no longer see traditional Courting and or dating we just it's it's become a byproduct of really the opportunity to hook up Because the reality is is that sex today is rather easy to obtain there. I said it sex is easy to obtain I remember when I was growing up you really had to practically beg for it to happen and now it's just handed on a platter Why is that you know, what's wrong with that Jonathan?  I'm not suggesting there isn't any you know I'm not saying that a woman can't do what she wants But the reality is is if a person genuinely wants a fully committed relationship I'm of the belief that that should be more reserved for people who Or sex should be more reserved or commitment should research should be reserved for those people who want a fully committed relationship So there's a saying women are the gatekeepers of sex and men are the gatekeepers of commitment Well, the reality is just today a man doesn't have to make much of a commitment whatsoever in the process He doesn't he all he has to simply say is I want a relationship What does that mean? I want a relationship But what does that mean in your mind? It might be where we see each other three or four days and nights a week together doing shared activities hobbies mutual interests spending time with family and friends traveling together teamwork building skills both in our personal and professional life and Intimacy both physical and emotional intimacy. That's what it might mean to you a relationship to the guy It might simply mean when I just want to see at my beck and call That's what it might mean. So if you don't understand the context of Words it really makes a difference. So let's unpack these words, you know What is dating? Dating is a vetting process to decide if you want to be in relationship with someone That's my opinion about dating. It's a vetting process to decide if you want to be in relationship with someone Now it's it that's the purpose of dating now some of you. It's about having a good time. I should just have a good time I should just live in the moment and have a good time Okay, you can do that You can live in the moment have a good time and you can do it again and again and again and after a while After you've had repeated Experiences that go nowhere it can wear on one's emotional well-being You know, the number one emotional health issue is I'm not good enough. I'm not lovable and I'm not likable And so imagine you've had experience after experience after experience that goes nowhere And that's even electronic experiences that go nowhere Not just the real life experiences the electronic experiences that go nowhere. Can you imagine how this wears on a person? Folks, I've probably have had close to 400 dates after my divorce First dates I should say now. I'm not proud of that. I mean I was on a binge that first year After my marriage the first couple years before I met someone six years after my marriage And I had my most you know I had a significant relationship that lasted six years and it took another five years before I felt met someone I'm really, you know genuinely interested in And I don't share I share this because that's the environment we live in Just because I do this for a living doesn't make me any less immune to you out, you know to what's going on out there for you as well so Understanding the purpose of dating really can help you because I'm here to promote Intentional dating which is what courting used to be courting was intentional. It was I want to marry this person So I'm going to make effort With this person now the problem with previous court, you know courting of the past It was very short-lived because two people wanted to have sex with one another and they oftentimes got engaged or married very quickly But the difference was there was a level of intentionality because there was going to be a significant commitment And by the way, I think that's one of the real problems today is a lack of Commitment to either the process of dating or getting to know someone or the commitment to actually exploring the depth Of long-term partnership with someone because you know in the Pat listen I think when two people are fully committed to want to explore a long-term relationship with partnership That's the best commitment at all and two people are fully committed I know a lot of people who were married one person was committed and the other person wasn't I'm not here to suggest you stay in Something broken just because you've made a commitment. I'm here to say Be committed to the process of getting to know someone have two people committed to the process of getting to know each other have two People intentional in the process of wanting to go the distance. This is really big This is why one of the things when I work with a client I help them vet for those men who are commitment ready who are emotionally mature enough To be in a relationship to my private coaching is all about because it is a mess out there. I get it I was in this mess Thankfully, I've met someone yay And I really feel strong about it because we're both committed to the process We both recited my relationship vowed my dating vows Now that's not a guarantee of any long-term commitment, but at least it's some effort Because the reality today is most people are just hooking up We're not seeing courting. We're not even seeing intentional dating We're seeing mostly hookup because they figure, you know, and I'll just wing it hoping That something might come of this This is why we see people drag out the dating process for so long because the reality is is the hookup is because We are dealing with a rather dysfunctional emotionally dysfunctional society with terrible emotional maturity and weak relationship skills That's right. This is true of men and women like ladies You like to blame on men, but let me just tell you you are just as equally dysfunctional. There are entitled women out there There are the doormat women out there You know, we men are suffering with that too Men complain that women 80% of the women are after only 20% of the men and Men are just, you know, 80% of men don't want commitment So no wonder it's a mess out there. This is why I'm such a big proponent is you do personal development work You read my book.  You read the book the Hoffman process. You read John Gottman's work You read Barbara DeAngelis And the list goes on and on. Brene Brown is another great one out there. I highly recommend reading Because the reality is of this if you're not actually aware of The dysfunctionality of human beings and human behavior if you're not aware the Dysfunctionality of the dating process you're going to find yourself in an endless trauma loop or an endless circle going nowhere And then you're going to be discouraged and I'm here to invite love in your life I'm here to invite something more substantial. This is why I invite you all right now to say this prayer with me Dear God universe spirit I invite genuine romantic love in my life where we have amazing chemistry with one another and we have excellent Communication skills with one another and we can resolve conflicts and different disease and the banter between us can go on for hours And hours at a time because we genuinely like each other And we are compatible with one another because we can blend our lives together because our lives are actually in sync that this Can happen we don't have to jump through multiple hoops to make this happen in addition We share the same core values That allow us to be in alignment with one another and lastly we want to develop the roots of The roots of commitment to take this from just meeting for the first time to actually going the distance and God universe spirit I invite that into my life Invite that all for you Because let's face it dating courting hooking up. I mean it's a mess out there So when you can pull back for a moment and see it from the big picture You can then focus on yourself and what's most important for you Rather than getting hung up on the minutiae of what's wrong with men and what's wrong with society and everything else Is this sinking in is this resonating? Please let me know post a comment below I'd like to hear your thoughts as always if you find value in the group Please tell your friends about midlife love mastery send them to my website Jonathan assay.com Have them click the group coaching button so they can join our fantastic group and I'm gonna sign up this videos I always do first off give myself a big gigantic Jonathan Barrett of self love I'm gonna reach into the camera and give you a hug of love if that's okay I'm gonna ask you to turn to someone a pet a teddy bear pillow give it or them a hug of love Because hugs are a great source of love and let's face it. We could all use more love in our lives. Thanks a bunch. Bye. Bye now. Bye. Bye


Honourable Ayuba Nuhu Abok, the Speaker of the Platter-State House of Assembly, who was reinstated on Monday, has resumed office to continue with his responsibilities to the state. Honourable Abok was reinstated following a judgment delivered by Platoon High Court presided over by Justice Nafisa Musa. He resumed office as early as 9am today in what is generally regarded as a move to take over his mandate. The reinstated speaker who spoke with Newsman on Tuesday morning in his office are sure of the security agencies that they are going to be peaceful in their responsibilities without any fight. Hello, hope you enjoyed the news. Please do subscribe to our YouTube channel and don't forget to hit the notification button so you get notified about fresh news updates.


My name is Tagajap Marvin. I am 13 years old and I live on Nammaruk Atoll in the Marshall Islands. I love this land so much. The land protects our culture and beliefs. Sometimes I just think, wow, this is the very, very place my ancestors stood. But every year the waves are eating away at our land, so we have less and less ground to live on. My grandfather showed me how much of the land has been taken by the sea and where the rising waters made the trees fall down. Climate change is also making the ocean warmer, which is damaging our reef and hurting the fish that live there. So is all of the trash people keep throwing in the sea. Our ancestors drank from the coconuts and ate from the breadfruit trees and from the sea. Nature provided for them. In Nammaruk we are doing things to try and keep our land and our lagoon safe. We use traditional canoes and bikes to get around. They don't need any fuel. Now we do pro farming to protect wild oysters and we use our coconuts to make oil and handicrafts to sell because we can't rely on the sea and the land to provide for us anymore. It's hard to imagine that when people do things far away it can affect our lives here. But that is happening so we have to find different ways to provide for ourselves. I want to say to people in places where they don't see what climate change does, don't just think about yourself, think about others too. When me and my friends play here, we are happy because Nammaruk is our home. That's why we want to look after nature and we'll do everything we can to make sure our island stays above water. So we don't have to leave. I will do whatever I can to keep my island safe. But I know that the only real solution is if others around the world join in and do the right thing as well.


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