Welcome and thank you for joining us today on a Friday which is a fundraising academy sponsored ask and answer episode we reserve one day of the week this day Friday for your questions and this is an opportunity for Julie and I or a fundraising Academy guest to come on and help us answer your questions and we of course have seen these questions change as we continue to navigate the the differences within the pandemic and pandemics plural so again thanks for joining us for today's episode. We are so grateful to have the continued support and investment of our presenting sponsors. There are so many amazing companies in our sector, helping you do more good in and around your community so please do check out these sponsors that support us in supporting you. They are here for your mission and they want to help you move that mission goal forward. Just as Julia Patrick is thanks for having this lovely idea to start the nonprofit show. Hello, Julia is the CEO of the American nonprofit Academy, and I am so grateful and honored to serve alongside as your co host I'm Jarrett ransom, your nonprofit nerd CEO of the Raven group. I shared, you know, just briefly, every Friday so one day a week we come on and we address questions that are viewers, all of you have sent into us there are numerous ways in which you can send us your questions, as well as take advantage of the live opportunity so if you are a live audience member right now watching this national broadcast, we do encourage you to ask us on the spot any questions that you might have, or any, you know, issues that you might be dealing with today on your Friday, you can just use the q&a or the chat button down below and let's get started Julia. This is one of our favorite days. Okay, you know how I live for the name withheld, but it's a double whammy when it's city withheld. Yes. Okay, so this is, you know, this is going to be good. I'm on the five person development team. I just found out that we have made our 2021 goal, which is great. That's not great. That's astounding. Congratulations. Absolutely. I mean huge. I also just found out that our development director will be getting a bonus and the team is not. I am super angry. Wow. You know this is interesting and I'm not quite sure how to answer and address this because I do feel, and now I know why you you submitted this as name withheld city withheld. I know that I've ever been in this position and experienced this exact situation. So I unfortunately do not have firsthand experience to share. But I can tell you that if I were the development director, and I found out that someone within my team was angry by this bonus and this extra support. I do believe that I would address it. I would have a conversation with my team and in particular this, you know, individual, and I would also on the flip side, you know, go back to the CEO or whatever measures we make for our promotions and our bonuses to find out if there's something we can do to be more equitable in the future. And so again, I don't, I would say we don't know the situation. We don't know if this was, you know, a hiring agreement or an annual performance review. I'm thinking there's so many additional layers to this very complex challenge that you're facing. And I don't know that I have the right answer, Julia. What, what is your experience say, you know, I don't know either because I'm old school. This is where that 20 years difference comes into play because, you know, throughout my career and my business, you know, it was verboten to speak about salary. And that's really changed. I mean, now it's much more open and people are talking about it within their organizations and within the sector. So to get a an understanding of what the employment landscape is. So having said that this is going to be an issue that comes up more and more as we know what's going on. I was talking with a development director or development officer last week who received a bonus unsolicited just like here you go, because the organization had received a massive, massive donation that was unplanned. Sure. And so the board and the CEO decided that this because their team had worked so hard for so low for so long that they wanted to take some extra money and disperse that to that team. I don't know if it went across the rest of the organization or just to this development team. But this person confided in me and that while he was really excited that he and honored that he got a bonus, he wondered if he had to go back out and raise that same amount of money. So meaning, you know what I'm saying? It's like he got a bonus and he's super thrilled and super excited. But there's a part of him that says, okay, that money has to come from somewhere. So now next year, the bonus was $1,500, which is, you know, for a surprise is a lot of money. Yeah. Do you know, that was kind of in his brain. I thought it was a fascinating discussion. That is interesting. You know, I will say the majority of my years and tenure as an employee on a nonprofit staff, rarely did we receive bonuses very rarely. There was often an annual review that came with, you know, a 3% to 7% raise, very nominal. And so the fact that, you know, you made your budget is fantastic. As Julia said, absolutely, that is something to celebrate. And I think, you know, the bonus is a conversation that I would definitely address. You're right, Julia, it is something because I remember, you know, my very early years of my career, it was so taboo to talk about your salary to talk about your pay. And so there's so much increased transparency when it comes to our pay, even, you know, our hiring salary, as soon as that new person is on the job, we pretty much know the range in which they're making. So it's not so much of a guess anymore. And so I, I tend to go towards the, let's have a very honest conversation and how might I play a role in this five person development team, so that we can all receive a bonus in the next opportunity. Right.  But to, I don't want to use the word soften the blow or to be gratuitous, but to be grateful, right. And so you can, you can know what that cost is.  Right. You can go to them and say, okay, if we gave two days off this next year to each member of our team, what is the value of that, so that then you could take that back to your team and say, look, you know, we are investing X amount of dollars in the situation of letting people take the day off. Not to mention Julia, you remember when we talked about maybe last year, you know, providing gift cards to employees and how that's taxed differently, bonuses are just the same they are taxed differently. So, again, you know, it's a whole ball of yarn. And you know, I love that this person wrote in and said that they're angry. I will fess up and say that I took their city, the name of their city off. Okay. I thought that it might be something that our viewers could figure out just on the offset. I didn't want that to happen. But anyway, long story short, this is going to be something that can fester and create a much bigger problem than the original situation. So get on it, address it to your point, Jared, figure it out and move forward, because you don't want an unhappy team. No. No, absolutely. Wow. Okay, well, that, that's a, that's a hoppin way to start. That's a whammy on a Friday. I know that like turned on my brain. Okay, let's talk with Clara from Los Angeles, California. And she writes, I'm a grant writer for a nonprofit that I just love. I've been with the organization for eight years. In my 2022 in 2022, my husband and I want to move to a rural part of the country. And that would mean I would need to work remotely. Any tips on presenting this new work style with our CEO. Boom, boom, boom, boom, boom. I think this is fantastic. Congratulations. You know, being with an organization for eight years means that you have quite a bit of institutional knowledge and history with this organization. So it's clear, Clara, that you have been seen as a very trusted and respected employee, because they have also chosen to keep you for eight years, right, like it's, you've chosen to stay they've chosen to keep you. And so I would highly recommend that you do, you know, offer the offer the opportunity to work remotely and lay out, you know, what would your hours of working be what would your communication expectation be. And really, you know, how would you be able to streamline this effort and make it easy for the organization. We've all, by default, just, you know, have experience working remotely, what even if it was for a short time, or over, we're still doing it, for many of us. So I think now is an great, great opportunity to address this. We've talked a lot with another one of our sponsors Katie Warnick with staffing boutique about how you can negotiate your current employment situation. And that's exactly what you're looking to do Clara is to negotiate with your current employer, a different working arrangement. And so I think now is a wonderful opportunity because it is proven that it can work and especially I think the grant writing position is a probably one of the best situations to be remote, because you have that quiet time, you have the opportunity to really focus on your writing and have conversations with the funders. They may they the organization may want you to come and be on site and experience the programming or perhaps, you know, the board meetings on occasion. And that, again, could be remote, or maybe you come in quarterly or every other month. So again, just think through all of those situations I think it's a wonderful opportunity. Thank you. And I would say a couple things. It's really a function. Are you going to be in the same time zone? Because that that can present some opportunities and issues. If you're, if you're staying in that time zone, if you're not sometimes that that creates problems. And the other thing is, what is it costing for the organization to house you. So for example, can your office area be given up to something else, you know, the costs associated with having you as a physical spot within that campus. Can that space be used some other way. And, and those are real costs, again, real costs that you should be able to figure out. So, yeah, really, really interesting. That also makes me think of the expense cost, Clara, that your organization may incur for you to take some of those technology assets with you. So, again, both sides of the spectrum when it comes to the financial, you know, assets, whether it's an increase for the organization or an expense, look at it both ways. But great suggestion, Julia. Well, hey, you know, it's a reality. Okay, before we go on to our next question, we have a viewer from the Middle East who's just written in to says, says that he loves watching us. So thank you. We love that we have a viewer from the Middle East. Okay, so let's get to our next question that comes to us from Fort Lauderdale, Florida. Wanna write I work in programming. I know it's a hard it's it is hard for the fundraising staff to do their job. However, I have some new ideas and I would like to know how the organization is growing. Is it a bad idea to ask them how they are doing with their fundraising. Super interesting question. No one has ever asked this question. That is interesting. And I really, so I don't know, wanna your role within programming. But my first thought is, it seems the organization is very siloed, and there's not a lot of communication going either direction. And so the fundraising team and the programming team really should work in concert with one another. And I always recommend that there's so much transparency when it comes to the cost of programming and operating entire organization as well as all revenue streams. So this could be grants that could be individual donors that could be events that could be reimbursements that could be so many so many streams of revenue. But I would go to your again not knowing you know your role within the programming team I would go to your immediate supervisor and ask if, if and when these data points are shared. Again, your, your annual report or impact report might be a good baseline for how this has been managed previously and years prior. So I think that's a good, you know, I would do a little bit more homework to find out what has been done, typically whatever the operating budget is should also be coming in through fundraising initiatives and again many other ways of this of this revenue that we talked about. But this to me tells me there's not a lot of communication. And that is the core challenge that I, I'm hearing when I see this question what about you Julia. Well my first thought is if you have something that has an intellectual property capacity to generate revenue. Let's say you have a program that is something that you could sell or replicate. It has, it has a financial impact in terms of generating revenue. Get that out into the before the people who could make that happen. Because a lot of times we don't look at programming as revenue generating. And, and it can be the intellectual property the IP aspect of this is enormous. And so if you are involved in something like that, that's really important. And then conversely wanna, if you have an idea, but you know it's going to cost money to implement, you know, to launch and run, then you need to do your homework too. And I agree with you too is Jared is you're saying, you know, why is it, what is it that you would need in order to increase your programming services so that people know what they're raising money for I guess. Very interesting, very, very interesting. And I agree with you, this is max of an organization that is not communicating enough internally, which means externally to Okay, let's go to Devin in Oklahoma City. Okay. I love that. I am working on my 2022 personal goals, which have a lot to do with work. Should I share this with my manager. I'm not sure if this is appropriate in the nonprofit sector. Wow, okay. Absolutely. And I don't know why this would be any different than any other sector. To me, I always coach my clients. You know, once we have shared in community and with our team or another individual, our own personal goals and again have a lot to do with work. Great, you know what I always say to you what are those resources that you need to be successful. And maybe your manager could help to, you know, advocate for these additional resources. Maybe it's a CFRE that you want to achieve and that's something that fundraising Academy can certainly help you with. In particular, our friend Jack Jack a lotto who will be joining us again. I think this is a great opportunity. You know, if you want to share personal goals that are not work related that might not be a very conducive environment, however, I think we can all witness over the last two years. There's been a lot of crossover between truly personal personal details and professional personal details. And again, depending on your relationship with your manager and the culture of your organization and your team.  Maybe that's something that's more personal. I always think it's great to share that and again to reciprocate what are your personal goals of your manager and how might I support you in achieving your own personal goals. So that we make it a win-win scenario. I would not have thought of that approach. My first approach is like, no, you don't do this work is work. And you know, home is home. So I mean, again, old school mentality, but I agree with you. I like what you said, Jared separate out what is more, you know, home versus work, if you will, if you want to, you know, get to that point. And then to talk about that because I think that's important. A shared goal is a goal that's easier to achieve. And then I really thought it was magical when you said, do you want to share manager your goals with me so that I might be able to support that. That's cool. That's that's that's magical thinking for me. I mean, no one's ever said that to me and I've never said that to anyone and and Morris the pity. So I appreciate that you said that, Jared. Well, good. I hope that's helpful for all of us. Julia, you have shared very personally that you set your goals. You're probably doing them now. You probably did them. I think you've heard them in October. October 15 is always the date. And you have someone that you share them with I mean for for us as entrepreneurs and you know we tend to not be surrounded by a very large team so finding that person, as you said shared goals are more achievable so Yeah, it's somebody who I know who I've done this with probably 20 years. I don't really share it with my family. I don't share it. I have a system that I created that is on my desktop. And I work with three screens. So it's on one of my screens and the things now the one thing I'll witness to you and Devin you might want to take this. This is really interesting. I did this for the first time I used the nonprofit nerds goal concept of best bet we The three layers. Absolutely. I did good better best. Okay. And so I did do that I did take the the framework of all my goals and I put that into I put everything into those categories and it really was transformative and it made me change some things interesting very yeah it was very interesting and so I'll report back as we're moving through that process because I think it's a good thing and it was a good exercise for me. I always started in October because I need to kind of think about it. But by December 15, it's got to be done, because I have to retool my brain so that on the first of January, we're, we're, we're, we're cooking, we're working on it. So today's the 10. So you have five more days. Oh yeah, I know. I know, believe me. It's on my, no, I know. I mean, and I think it's important. So anyway, Devin, we've been talking about ourselves, but we are thrilled that we could talk about you because yay team on sharing goals. Definitely a cool thing. Okay, we don't have a lot of time left but we want to squeeze in this extra question. Roger from Santa Fe, New Mexico, one of my favorite places. Once again, we are canceling our holiday staff party. Any ideas that we could plan for that helps celebrates our team and at the same time gives them a break. I'm afraid this has to be on zoom. Sorry, Roger.  I was able to attend a staff holiday party here in my community in Arizona, our weather is beautiful. The outdoors is an amazing opportunity to hold something like this. You know, and really abiding by the CDC guidelines is what this organization is committed to. So I would say Roger find something fun online, or, you know, yes I'm sorry it probably does have to be zoom, or some other. Yeah, it's cold now in Santa Fe. Oh yes it is cold. I'm not going to be able to just let go to an outside venue, unless they're doing a ski venue. You know, I just thought of this, totally, you know, out of the blue but you could do something like a scavenger hunt where you send out and, you know, a company email and you say here's the items we're looking for people could submit photos or they could share them online. However you want to do this bingo is something that's been done online virtually, there's been very. There's been a lot of innovation when it comes to zoom. I know that you can hire an animal to be an attendance maybe a llama, or an ostrich I mean there's so many different opportunities. We laugh, however, most of these are nonprofits that have said hey, we need to find a revenue generation stream for us and we have who doesn't love llamas. I mean, I don't know but the zoos the zoos have implemented this as well where you know, maybe the zoo will say, you know, I don't know there's so many opportunities to think about this but I hear you we're all tired, we're all, you know, tired of looking at ourselves and our co workers via the screen so you'll see you I know it's difficult. Well hey, you know we are not tired of looking at you to our viewers of the American nonprofit academies. The nonprofit show along with our wonderful wonderful presenting sponsor fundraising academy really briefly they're doing something something super innovative. We're launching the 2022 online cause selling accelerate it's going to be a cohort of people that work together from all over the country. And I would imagine North America, and maybe even international I shouldn't say that because I don't know but I will I will find out. The really cool thing is that you can be a part of an amazing training with folks from different parts of the service area to learn from them and to learn together it's going to be operated by again our friends over at Fundraising But Jared, the co host that you had on last week. She's going to be the one that's, that's, you know, serving this and so we're going to hear more and more about this. I just learned about this. They just getting ready to launch it. So it's going to be super exciting and we just want to let everyone know. Again, I'm Julia Patrick I've been joined today by the nonprofit nerd herself. I was going to say, Hannah burger is her name, and it's a very low cost. I want to say 400 is what Hannah shared. So it's not a huge investment but hopefully your employer will be able to support that. And again so grateful to have fundraising academy as part of our, our team and our community here thanks to all of our sponsors that you see in on the screen. Now's a great time to check them out. So as soon as we do close down today's Friday episode, please check out these companies because they are here to help you and support you through the end of this year and to start 2022 really strong. So thank you to our presenting sponsors that continue these conversations with so many thought leaders around the nation. Absolutely. Hey, it has been a great week. We've learned a lot. We've been confronted with some new challenges in our sector during an incredibly busy time. This is the opportunity to remind everyone to stay well so you can do well. Jared, I hope you have a restful weekend my friend. Thank you you too and to all of you that have that have stayed with us today. Thank you.


In this module, we will continue with our discussion on Islamic credit cards. In the previous module, we looked into an Islamic credit card in which the credit facility was generated through a process known as Tawarruq. As I mentioned in that module and before that in quite a few other modules that Tawarruq is a mode of financing which has attracted a lot of controversy in Islamic banking and finance. So a credit card which is based on Tawarruq would be frowned upon by many observers of the Islamic banking and finance industry. Hence, some people or some organizations came up with an alternative Islamic credit card which is based on Ujra. Ujra of course is an Arabic word. We call it Ujrat in Urdu. So this concept of Ujrat is above. In this model of Islamic credit card, credit facility is decided by the card provider i.e. the bank based on some information it receives from the customer in the application form. So based on the profile of the customer, especially the credit worthiness of the customer and the personal circumstances of the customer, the credit provider, credit card provider determines the credit facility. So this Tawarruq work is not done. The central to Ujra based credit card is the P, Ujrat for certain goods and services which the credit card may facilitate for the customer to receive. The benefits the credit card provider facilitates take Ujrat. Ujra based Islamic credit cards originated from the Middle East. I think it was Dubai Islamic Bank which first structured an Islamic credit card based on Ujra. However, the use of Ujra based credit cards, Islamic credit cards has spread to other countries, especially in Malaysia. In Pakistan, no Islamic Bank offers an Islamic credit card except two. It is Basel Bank which has structured an Islamic credit card based on the mechanism of Tawarruq and of course standard chartered Sadik Bank also offers an Islamic credit card. Other banks, especially Islamic banks, they have yet to come up with an Islamic credit card. What are the rules governing Ujra based Islamic credit card? Number one, credit card provider should ensure that the Ujra is imposed on the services which are Sharia compliant. They are not fictitious services. What could be those services? It could be access to a business lounge at an airport, access to a golf course. Certain discounts offered by stores and vendors to the holders of this Islamic credit card. So, these benefits, they should be Sharia compliant. It is also permissible and this is rule number two. It is also permissible for the card provider to charge different fees to different levels of cards. A simple card, a silver card, a gold card, a platinum card, can have different fees as long as these cards offer different sets of benefits and this is acceptable from Sharia viewpoint. The imposition of Ujra on the services and benefits and privileges which are not related to debt, card or deferment of debt and exchange of cash with cash at a different value is permissible. So, as such services, cash withdrawal, debt deferment and we said that this is actually prohibited interest, so all other services which do not involve exchange of debt for debt or deferment of debt and cash for cash, these services should be excluded when the credit card provider is determining the Ujra or the fee. Why? Because all these activities, card, deferment of debt and exchange of cash for cash, especially if it's higher amount of cash, then all these things are not permissible in Sharia. However, charges may be imposed to cover the actual management costs associated with these activities. So, in case of an Ujra based Islamic credit card, a credit facility is decided by the card provider based on a score card, based on the personal circumstances of the applicant and their credit worthiness and a fee is imposed to offer this credit card to the customers.


So let's say we have two coordinate systems like this, and two events happen, which we assign x, y, and z coordinates with respect to each coordinate system. Now we can calculate what we call the Euclidean distance between these points. We call this d, and just using the Pythagoras theorem, d squared is equal to distance in x squared plus distance in y squared plus distance in z squared. And before we knew about relativity, this distance was thought to be invariant between frames. It didn't matter if someone was moving, if someone was rotated, the distance that two people would measure would be the same. However, with things like length contraction, we now know that this is no longer the case. So what can we use instead as our idea of distance? So the answer turns out to be something that we call the invariant interval, ds. And this is calculated by ds squared is change in x squared plus y squared plus z squared minus c squared times the time spacing between the two events. Now this is the same between any two frames, which you can work out by just plugging in the Lorentz transformations. Now in our transformations, we've made assumptions that all the motion is along the x-axis, that the coordinate systems are not rotated relative to each other, and then at time t equals zero, the origins coincide. Now you don't have to make any of those assumptions. So you can go ahead and do the most general kind of transformation, which would be a lot more complicated, but you'd still find that this interval is invariant. Now we never actually deal with ds. We always talk about the interval squared, ds squared. And the reason for this is that the interval can be negative because of this minus c squared delta t squared term. So for simplicity, let's assume the two events occurred along the x-axis. So there's no separation in y, there's no separation in z. And let's look at the three cases for if ds squared is greater than zero equal to zero or less than zero. So if ds squared is greater than zero, that tells us that delta x squared is greater than c squared delta t squared. Or in other words, delta x on delta t is greater than c. What this means is if an object wants to travel between these two events, it would have to travel at a speed, distance over time, greater than the speed of light. So in other words, it's impossible. Nothing, no signal, can travel between these two events. And we say that the events are space-like separated. If ds squared is equal to zero, then we have delta x is equal to c delta t. Or delta x on delta t is equal to c. So if something wanted to travel between these two events, it would have to travel at the speed of light. And for that reason, we call these events light-like separated. Lastly, that's the case where ds squared is less than zero. So these are the two events where signals can travel between them. One of them can influence the other. And these are the events that we call time-like. So the reason for calling these events space-like and time-like is you can show if two events are space-like separated, you can find a reference frame where they happen at the same time, but at different points in space. Meanwhile, if two events are time-like separated, you can find a reference frame where they happen at the same place, but at different points in time, one after the other.


My dear constituents of Castry Central, on June 6, 2016, amid the pouring rain, muddy pathways and slippery hillsides of Monde Udon, Black Stars, Poipatat, Leslie Land and Lastic Hill, you made your way to your various polling stations and waited for hours to cast your vote.  Some with little encouragement, some with much encouragement and others at their own resolute insistence with shared determination. At the close of the day when the votes were being counted, as each vote was called in my name, I prayed for the person who had cast this vote and begged Almighty God for His grace and blessing to respond to that person in a unique and personal way. Each vote mattered at that moment and more so the person who cast the vote. You responded to my request for support and you elected me as your parliamentary representative. Yours was a deliberate act in response to my request for your support. I continue to thank you for this singular honour and privilege. In my thank you speech following the election, I dared to publicly share a bold aspiration. I said that I wanted to know each constituent by name. You might ask, how am I coming along with this? I smile and say, I am trying very hard. I thank you for your patience. In 2017, many of you visited me at the Constituency office on Showsay Road, sent emails to my direct email address or WhatsApp messages. I thank you for taking the time to visit personally, message me or email.  I very much value that trust. Over the past months, our team in Castry Central has been able to respond and assist in many ways. Many matters were resolved and others are in various stages of implementation. We have been able to generate some employment, assist with building footpaths, retaining walls, walkways and bridges, advocate for constituents on a number of community or personal matters with various agencies. The workload remains heavy. There is so much which needs attention every single day. As we begin this new year, I would like to share with you briefly my vision for the way forward in the short to medium term on some key matters of importance to us. There are many issues which affect us within our city.  I will continue to work with the Castry City Council to ensure that maintenance of these essential services continues to improve so that the quality of life of the residents and visitors to our city is improved. I thank the Mayor of Castries and the Castries Constituency Council for their continued efforts and assure them of my unwavering support. I trust that you will agree with me that among the many priorities for our constituency are unemployment, crime and poor housing. These go to the heart of our quality of life. They are very serious and urgent issues to be addressed and there are no quick fixes. These are national concerns which require comprehensive and deep-rooted solutions. I assure you that as a government we are working hard to address these in effective and sustainable ways. For a moment, as your parliamentary representative, I would like you to reflect with me on the issue of housing as it relates to our families. I need to say frankly that on my frequent visits to the constituency it has been heartbreaking to witness the conditions which too many constituents live under. Older persons whose roofs are leaking, whose floorboards have gaping holes who live in partly collapsed houses where to remain in occupancy is a danger in itself. Unacceptable. Overcrowding and the lack of basic amenities in the home which affects the ability of parents to provide structure and discipline and to properly nurture children in their tender years. The continued inability of families to own a home of their own makes it impossible for people to make key decisions about their future in both big and small matters and affects overall stability. This too is unacceptable. I am committed to addressing the issue of housing in Castery Central in a decisive way during this term of office. On the issue of crime, a lot can be said. First of all, I wish to thank the Royal St. Lucia Police Force for their tireless efforts in combating crime.  Dealing with crime means dealing with the causes of crime, one of which I have already addressed. Our behaviour is an outward reflection of who we are inside A violent crime does not start with a violent action.  A person's actions on the outside will not change unless the person himself changes on the inside. In our homes, communities and in our personal lives, each one of us needs to examine closely in a way we have never done before, who we are and commit ourselves to changing all the bad in us and replacing it with good, rooting out vices and replacing them with virtues. One thing at a time, one day at a time. This is a tough task and it is a challenge for all of us, not some of us. Fortunately, as Christians, we are not alone. As we have, as our Lord, our brother and our friend, Christ himself, whose birth we celebrated during the festive season. He became friends with the hardest sinners and guaranteed salvation to a thief and a robber just because he was asked. He has shown us a remarkable example which he commands us to follow. I now turn to the issue of unemployment. By far the most urgent issue to address as it contributes to and compounds all of the other issues which we have reflected on today. The hardship, anxiety, sorrow, and sheer frustration of the unemployed looking for work is inexplicable. By far this is the greatest challenge facing constituents, the majority of whom want to work to earn an honest living. Although our government has been able to reduce the level of unemployment, it is still much too high and youth unemployment is particularly high. As individuals we have been commanded to and are expected to work. Work adds value and meaning to our lives and allows us to live with dignity and provide for our needs and that of our families. Our gifts and talents have been given to us by God for this purpose to be used to develop ourselves and the world we live in to produce and be fruitful in all aspects of our lives. Each one of us is good at something. Each one of us is capable of using our gifts and talents to contribute to national development, to assist others by working with them or to create opportunities for others to work with us. In Castry Central as your MP, I am committed to working with each one of you to discover, define, and refine your talent to help you reach your full potential no matter your age, circumstances, your past, or indeed your political affiliation. Within the next few weeks, we will begin a personal development, training, and recruitment project called Synergy in Castry Central. We will offer uniquely tailored services to constituent sick in employment in a way which has never been done before in our communities. The Synergy program will be tailored to each client's personal needs and provide the best opportunity for personal development geared towards work readiness. We will work with you individually to identify job opportunities to prepare you for them and to explore avenues for self-employment. A full website for the Synergy program is now being developed, which you will be able to log into and to register your interest. Please continue to liaise with our office, monitor the news and social media for details of this program and how you can participate. I have taken time today to share with you some thoughts that have occupied my mind ever since you elected me as your Member of Parliament 18 months ago. Our journey started in 1997, more than 20 years ago, and though there have been interruptions, our relationship has never been severed. We have come to understand each other well and I am sure you will appreciate the approach which is characterised by less talk and more action. The approach which takes time to find real and lasting solutions to problems and which does not engage in window dressing. With this approach, planning takes time and so does setting up structures. A strong foundation requires a longer time to dig deep and well to ensure the structure is properly anchored to withstand knocks and bruises. I thank you for your patience during these last few months which has involved much planning and preparation and I look forward to an exciting and productive 2018 with my castry central family. Happy New Year! May God bless you and keep you. I thank you.


This is stock number 9446. We are here at Summit Automotive in Fond du Lac, Wisconsin. You're new and used Truck headquarters today. We are checking out this super clean 2011 Chevy avalanche This vehicle has the 5-3 liter V8 motor From this HD video you will be able to tell that this truck is extremely clean considering the age and miles on it All the way around inside and out does have the factory fog lights You can see the front valance is in really nice condition headlights are nice and clear This truck has brand new Goodyear Wrangler 275 55 R20 tires on it and it has the factory polished aluminum rims. These tires are brand new We put these on in our safety inspection So we guarantee it has four brand new tires Front fenders in pretty nice condition. It's got a couple little nicks on it One little ding nothing major Still in really nice condition. This truck has close to a hundred thousand miles on it You can see that that tire is brand new as well little bit of light corrosion on those rims, but They still hold all the air and They look good Down this side of the truck Pretty clean We take these HD videos So if you're far away or even if you're close by and just can't make the trip down You can still see the truck here the truck and have confidence in the vehicle that you're looking at before even get here So one tiny little ding behind that door But other than that pretty nice and cleaned on this side of the doors has the factory running boards Backrooms in about the same condition as the rest and this back tire is brand new as well We want to make sure you get the most accurate representation so that when you get here there's absolutely no surprises Rear bumpers in really nice condition Full towing package which includes receiver a chance seven pin wiring tailgates in nice condition as well I didn't see any dense or dings on that And it has the factory bed mat back here And it's really clean back here as well Shuts nice and solidly and as you go down this side of the truck just as clean as that pass near side I didn't see any denser dings down this side of the truck very very clean has power folding mirrors with the built-in directional signals inside truck has I Believe the LT3 package, which gives you the black leather interior There are no rips or tears on these seats Both these seats are heated and power guy a power windows power locks power mirrors these mirrors do power fold in like so And they also power fold out has the factory brake controller auto headlamps and turned dial four-wheel drive As you can see this truck has 97,109 miles has the leather wrap steering wheel That's in pretty nice condition no rips or tears on it Has Bluetooth audio controls and radio controls on that side and the cruise controls on this side has the AM FM serious satellite radio capabilities and It has boas sound system in it dual climb control power pedals backup sensors and stability control Passing your seat is very clean as well. No rips or tears on that Smells very clean in this truck Factory floor mat on that side up here. We have the on-star system And we also have the home link system, which is for your garage store security systems and lighting systems and the power sunroof This is actually an LT one so an LT one with leather. I apologize but still has the heated seats and sunroof and dual power seats so all the nice options Has the 20 inch rims to back seats are very clean as well. No rips or tears back here. It has the factory Latch child safety system and it has the removable rear window We also have radio controls back here and an all-weather floor mat for the floor back here as well Let's take a quick look under the hood and then we will Finish up the video All of our vehicles go through 130 point inspection this one's been no different It has been fully safety and inspect by our service shop As a fresh oil and filter change all the fluids have been checked and topped off Has four brand-new tires and is 100% ready to go To see more pictures of this truck or one of our other four hundred new and used Cars trucks SUVs minivans wranglers half-tons you name it. We got it go to our website www.SummitAuto.com full pictures and descriptions of every single vehicle on our lot videos of every single used vehicle That we have on On our lot all at SummitAuto.com. Thanks for checking out the video if you want to make this one yours Give us a call right now nine two zero nine two one zero eight five zero as per one of our sales associates to make this truck yours today Once again that number is nine two zero nine two one zero eight five zero Thanks again for checking out the video if you want to check out more go to youtube.com slash summit I'll remember to like subscribe and share on this truck and Any of the videos you see there in fact in a second you'll see a link to subscribe to our YouTube channel on your left A link to more half-ton truck videos like this one on your right if you haven't been to our website on the bottom link to This truck on our website click those check us out and we really look forward to helping with this super clean 2011 Chevy avalanche LT thanks again


Hello everyone, and welcome to this Eucadator Service webinar introducing Hadoop. I see there's still a lot of people joining, so I'm going to give it a couple more seconds until we actually start the presentation, but there's already a lot to be on, so thank you for joining. Okay, let's just start with some introductions in the meantime. So I am Marguerita, I work for the Eucadator Service and I'm based at JISC in Manchester. And presenting today is Peter Smyth, he's a research associate working for the Eucadator Service as well, and he is based at the University of Manchester. Just a few things before we start, you have a menu on the top right corner of your screen, which hopefully you have time to familiarize yourself with. You can collapse and expand it using the red arrow, and you can type in comments and questions and the questions box. We probably won't be able to answer them until the end of the presentation, but if you do have a comment during the presentation, please do write it to us, and all attendees are muted, so we won't be able to hear you. We are recording this webinar, so if everything goes smoothly, the recording will be available on our website, it will be under using events and then past events. And last thing is under handouts, I have uploaded the slideshow in PDF format, so if you do want to download it, you can do so now, and if you want to write comments on it, you can do that. But the slides will be available on the past event page too. Right, so before I hand over to Peter, I'd just like to see if all of you can hear me, so I'm going to launch a poll, just to check that you can all hear me, okay? Okay, so all of you at the moment can hear me, all some struggleers, but most of you have voted now. I just have a slide for people that can't hear me. I'll pull it up in a second, so it looks like 98% can hear me, so that's really good. However, I've got one slide here up for people that can't hear me, of course talking to them won't help, but there's some numbers that can dial in as well, and they can check their speaker and headset, so hopefully the sound will improve then. Right, so I'm going to hand over to Peter now, and he's going to start the presentation. Okay, thank you, Margarita, for that. Our presentation today is five sessions welcome, which Margarita's already done, so I'll welcome you as well. We're going to look at what big data is in terms of the definitions, why big data, which might be translated as what is made with data being in the first place. We're going to look at the processing of big data with Hadoop in a very simplified format, and then at the end we're going to show you some examples of using the Hadoop system using Hive, which is a component of it. So what is big data? I've got an idea, and you'll have heard of all the definitions starting with the word V. It started off with three Vs, volume, velocity, and variety, and then people started adding a few more, so we've got seven there, you can probably find more in the dictionary. But we also need to consider where this data is coming from, so we've got various sources of big data, new social media, GPS, modern systems for generating data, many of them. What kind of data are we talking about? Big data is quite often associated with unstructured data, free form, text, audio, video, it's stored in different formats, JSON and XML, and stored often in no SQL type databases. Further that we've got destructive data, now this is normally associated with more traditional small data in these formats, but of course if a table is big enough it's going to be big data. And then finally, what can we use to process big data? There's Cassandra, there's MongoDB, there's probably many more, but the one we're going to talk about today is Hadoop, just one of many. So despite all the words and everything I've said about big data, perhaps the easiest way to think of big data is this little definition from Wikipedia. Big data is a broad term for data sets so large or complex that traditional data processing applications are inadequate, or if we put that another way, your use of processing a little bit of data on your PC in your favorite applications, whether it's SPSS, Starter, R or whatever, and it gets to the point where the data is just too big to fit into your desktop application. At that point, you personally are going to consider that to be big data. But we've already mentioned in the previous slide that it comes from a variety of data. And one of the key things about these new sources of data is that they haven't been generated specifically for analysis. And in addition, the unstructured data is typically verbose in the layout and constitution. So you can also have situations where the data simply contains more than we actually need for analysis. That's derived from the fact that it's not actually being generated specifically for the analysis. So we've had a look at structured data. This is the more the traditional data, so the tabular data and so on. Relational database systems like Oracle and SQL Server and so on all rely on structured data. So it consists mainly of tables where you construct a table, you put column names, you say the types of data that these columns are going to contain, and then you populate the table with the rows and rows of data in the right format, in the right position in the table. So the disadvantage of this is that it makes it somewhat inflexible in dealing with changes in the structure. If you suddenly got a new column that was needed, or worse, you need to reorder columns, then you've got a bit of a problem. On the other hand, an advantage is that you can perform a lot of validation checks as you load the data, because you already know what type of data you're expecting in a certain column position. On the other hand, unstructured data is free format data. There's no guarantee what data items will be included, nor the order which they'll appear. When data is originally received, it's just stored as is. So you've got a data source coming from somewhere, you read a record in, you just stored as a data, you're going to process it later on. When the data is subsequently processed, then you worry about the values from specific fields. Despite the name, however, there is still some structure in unstructured data. So here's some examples of unstructured and unstructured data. You can see the top one is an Excel format, where you just have a worksheet and you've got your column names at the top of the table, and the rows just represent the data. The CSV and the tab delimited below that are very similar and they're very compact. But they are assuming that having given the row headers at the beginning, every row of data that follows is in the correct format and in the correct positions. When we look at the unstructured data examples, some of XML, let's see, structured data. So on XML, we've got, again, within a header, we've got something called a column and we've got, clearly, we've got a name QN, which is a column name, and we've got the PC column and the HN column and the QA column. But all of these column names are preceded and afterwards they have tags associated with a column and forward slash column. And similarly on the cells further down, each cell value is preceded and post-seeded or anti-seeded or whatever it is, with the backslash cell. So you can see this format, although it's very descriptive and it clearly allows you to change things around a bit, it is quite a verbose system of recording the data. The JSON format, which is probably the most popular unstructured format out of thought, is also comes with everything in a row of data contained in the row of data. That is, each row contains what in other terms would be called a column name followed by the value for that column and so on and so forth. So they've got exactly the same data represented in JSON. Now the thing to remember about that is that the next row would again repeat QN and quotes followed by a value for the next row of data and so on and so forth. So in fact, every row of data has the column names repeated. So again, you can see why that becomes verbose, but it is quite a flexible format. So that explains the verbosity of data, which can help make it big. Let's look at another example. This is a map of a trip across Manchester. The data used to produce it was recorded on a GPS logger and you put your GPS logger into your PC or the USB port and the software provided draws you nicely on a map like that. So you can see where you've been. Very common application and what you're seeing on the screen is the typical use of it. But you can do other things with it as well. So the data that the GPS logger records will include a timestamp, a longitude, a latitude value and various other bits of information and it does that in regular intervals every 15 seconds, say. Now it uses all that information to plot the graph, plot that table, map, I beg your pardon. What we're going to do, we're just going to use the longitude, the latitude and the timestamp and then we're going to take a bit of a liberty. We're going to use Pythagoras and we're going to pretend we're part of the Flat Earth Society and we're going to use that to generate some graphs of a different type. So the first graph is a sort of a speed against time graph and you can see on this graph that at the beginning of the end the speed is very low, that represents walking and the section in the middle, up and down, up and down, up and down, that is a tram journey across Manchester. Pretty well what you expect. I had to use the same data in the same way to generate another graph of distance versus time. Very simple graph, start off slowly because I'm walking, I'm on the tram so I've got constant speed, get off the tram, start walking again, it slows down, that's all very, very obvious. The point about this is that if you compare those top two graphs with these two at the bottom, they look very similar. You can see the start stop, you can see me walking on the left hand side, on the right hand side, they're almost identical shapes, but the bottom two graphs are drawn with only every tenth data point that was available to me. So in fact by discarding 90% of the data, I've actually lost very little information at all and that's a type of decision you may have to face when you're looking at your data. How much of it do you need, what can I get rid of, how can I get rid of it? And so we look now at another source of examples and explain where the problem comes in. If we consider tweets, if you send the tweets it's very small. I should just point out the scale at the bottom of your screen is a pseudo log type scale just to give you an idea of volumes. There's no attempt to be precise at any of this, but a single tweet is going to be less than 1k. If you actually try to record tweets from Twitter.com using the various means of doing so, you'll find that a tweet, same tweet if you like, is probably about 4 to 5 kilobytes in size. If you, for your analysis, you needed to tweet from all of the tweets from a user spanning several years to a prolific Twitter, you could have well over a gigabyte of data to worry about, but so that's not too bit of a trouble on your application, your desktop application. If, however, you want to look at all of the tweets from a user and all of the tweets from all of their friends and potentially their friends as well, then it's very easy to see how this data quickly is going to get out of hand and will well into the 10 plus gigabax here. Or it could be if you've got lots of friends. Looking at this from the other point of view, let's look at some smart meter data. Here you're presented with a data set of smart meter data from whatever source. There is a source of smart meter data in the UKDS discovery system, so you can find some there. And this is going to start off as a very large file. This file, the data records in this file are recorded every half hour, which is possibly not what you want. So if you want to aggregate that smart meter by day, you can reduce the size. If you do it by month, you can reduce the size even more. And if you reduce it by month and just look at a specific geographical area, you can get it down to something very manageable, I'm sure. The point about this A is that if you want to put in an arbitrary line, approximately five gigabytes in this case, and decide that anything on the left of that side of that line, you're happy to treat in your desktop application. You feel you can process this happily. So you're not going to consider that big data, so you're okay there. And anything on the other side is big data. Now the problem is that in both these scenarios, there is a situation where you're in the big data environment. And at that point, even if you're subsequently going to discard a lot of the data, you don't really have any choice but to treat it as big data, and therefore you need a big data environment to work in. And that's where Hadoop comes in. So Hadoop was created by Doug Cutting and Mike Carfarella, 2003, 2004, it's based on the Google file system. MapReduce itself has been around for 40 years and first came in the language list in 1961. And just for a bit of information, the elephant that you see at the bottom of the screen, which is the icon always used to depict Hadoop, it comes from a cuddly toy elephant owned by Doug Cutting's son. And if you Google Doug Cutting and Hadoop Elephant, you'll find lots of pictures of the real elephant and you'll find it's a far scrawny affair than the beefed up one there, obviously done to represent big data. So let's have a look at the infrastructure of Hadoop. A Hadoop cluster consists of thousands of nodes. Each node is an individual computer many times more powerful than the average desktop. It's the same in that it has RAM, and it's got disk, and it's got memory, but a lot more of everything. The minimum number of nodes you'd really need to have a cluster would be four, but you can't have many thousands if you want to, if you can afford them. Certainly there likes a Yahoo and Google will have thousands in their clusters. The strength of Hadoop though is not this raw power, despite the fact you've got powerful computers in there, but it's the ability to break a processing task down and run all of the parts in parallel, effectively divide and conquer, that's what it's going to do. It's also built to be very resilient and cope with server failures because if you think about it, a low servers are very stable and don't break down very often. If you've got a cluster with thousands of them in them, the chances are one's going to break every day. If you go to Hortonworks.com or several other places, you'll find plenty of diagrams showing, in this case it says Hortonworks data platform, other companies have their own name, but essentially this diagram is depicting a Hadoop system with various components in it. Some of them are essential components, others are optional type elements. So we're going to look at this in a very cut down way. We'll look at HTFS, we'll look at MapReduce, and at the end we're going to do a demonstration using Hive, which is SQL based. So that's our minimal environment. So starting with HTFS, to the end user it's just a file, and later on when we do the demo I'll show you this looking just like a file system. But internally the files are segmented into blocks of 128 megabytes and randomly distributed across all of the available data nodes, whether they all get used, you don't know. You don't really care either. The data node is a server as a Hadoop cluster where actual processing takes place, i.e. where your programs are run. So HTFS is going to place the data onto these data nodes, which are just big computers, and they're going to be run from there. The name node is another server in the cluster, which is going to keep track of where all the blocks of your data are, but you don't want to do that, you just know it as a file name. Just as an aside, if you consider what an ordinary client server system looks like, so on your desktop, well, in a traditional client server, which Hadoop is not, it's normal for the data to be stored on a server, like a file server, and on your desktop you'll have office applications such as Word and other things. When you need to edit a Word document, a copy is sent from the server to the desktop, and you edit it there. When you finish, the new version is copied back to the server. That is, the data comes across as moved to meet the program. This makes sense because typically, the MS Word program is many times larger than the document is edited. Now in a Hadoop environment, it's a bit different. So on the left-hand side you've got a traditional client server, and the data is moved to the program. On the Hadoop side, because the data is so, so much bigger than the program, it makes more sense to do it the other way around. The program is moved to where the data is, and that's exactly the way Hadoop works. One of the reasons why the name mode needs to be practically correct of where all your data is. The other Hadoop component is MapReduce. The two parts are MapPart and a Reduce part. They're just names. Nothing to do with MapsReduce, although it typically involves aggregations, and doesn't necessarily mean reducing like smaller. They're both effectively smallish programs, typically written in Java, but can be written in other languages such as Python. In a couple of slides, I'm going to show you, walk you through a demonstration of MapReduce. There's a couple of things you need to know about MapReduce. The first one is, it's got to be shown for completeness in any basic Hadoop type introductory webinar. The second thing you need to know is you're probably never actually going to have to do it, because there's so many alternatives in the different Hadoop components and different things that you can do. We're just showing this to give you an idea of what you're missing, or what you will be missing. Now, the scenario I'm going to walk you through in MapReduce is, let's pretend you have a questionnaire of 10 questions, yes or no answers. It's completed by a random number of households in each postcode area starting with the letter M, and you want to know, by postcode, the percentage of yes answers for each of the 10 questions, okay? So, this is what is going to happen. The storing of the data in HDFS means that it is automatically split into blocks and spread across multiple data nodes. I mentioned that earlier. The mapper process is sent to each of these nodes, which is part of your data, to process the block of data on that node. The records output from the mapper process are sent to another data node, on which the reducer process will run. Again, both cases are just standard computers, big computers, where you're going to run a program. All records with the same key value will be sent to the same data node, which will be one which will run the reducer process. The output records from the reducer process are sent to a final HDFS, each reducer produces its own output file. So, diagrammatically, this is what we have sort of. Now, I'm going to pick a record at random, like this one. So, this is just one of the records in your input data set. This record was moved to this machine, okay? This is a machine piece where all of these records are going to be processed. And the output of your mapper process on this machine is to simply rearrange the record so that the question number, that's QN3 in this case, is going to be counted as a key, and the rest of the record is a value. Now, from your point of view, it's just reorganizing the record. The reason I have described it as keen value is that the key part, it's significant for the next step. Because the next step is what's called a shuffle step, and that sends the record with the same key value to the same reducer. So, this highlighted area now is the reducer. It's just another data node somewhere in the cluster who is going to receive all of the question 3s from your data set. And the job of the reducer, in this case, is to do an aggregation. So, for each poster code that I get a record for, it's going to sum the records up and work out the percentage of yes for question 3. And when it's done that, that record is sent to the output data set. And that's it. So, at the end, on the output data set, we've got the percentage just records by poster code area, okay? Moving on from that, there are alternatives to MapReduce. But, first of all, you really need to understand your data. You only need to use Hadoop for big data and big data tools because it's too big. We've said that already. You have two choices. Either you can perform the analysis inside Hadoop itself using specialized tools, or you can use the big data tools to transform and reduce the size of your data if it's a viable option. And then download results to your favorite desktop application. And that is the scenario where it gets in. But if you do have to analyze it inside Hadoop, there's plenty of add-on products that you can use. There's Mahoot, which is an add-on to Hadoop. There's Spark, which works with Hadoop, but it is also standalone. And in Spark, there's something called MLlib, which is a machine learning library internal to Spark. There's also something called HiveMount, which is an add-on to Hive, which again can do data analysis type functions. So moving on to our demonstration in Hive, what we're going to assume is we want to reduce the large data set into something that your desktop can handle. For this, we're going to use Hive. The Hive Processing Language, which will be using HQL, is based on SQL. This makes it easy to learn, well, easy if you have any SQL experience. And even if you haven't, it's a lot easier to learn than Java. Now, where are we getting our Hadoop from? In this particular case, we don't really have a proper Hadoop cluster to work with. So what we're going to use is a virtual machine, a sandbox virtual machine. These are available from the likes of CloudDera or Hornworks, which is the one we'll be using. You can also get similar to the sandbox VMs in the cloud under Azure or AWS, that's Amazon Web Services. UKDS are currently developing a cloud Hadoop system and also have it on-premises Hadoop system for secure data, but they're still currently under development. Okay, the environment we're going to use, like I said, it's a Hornworks sandbox. I'm using VM player on a PC. We're fixing gigabytes of RAM into the likes of the processor. If you look at a guide for installing Hortonworks, it will be on our website in a few weeks. The Hortonworks side of that guide will tell you that you need 10 gigabytes to run the VM. In fact, you can run it in six. So if you've got a PC with eight gigabytes of memory, you should be able to run it. Well, I won't say happily, but you'll get away with running it at least. Now, in the demonstration, I'm going to show you the sandbox provided web interface, and I'm also going to show you a third-party Windows-based Hive interface package. This package is currently in beta release, and it's free. I'm not sure if it'll remain free when it gets into its final release. Okay. This is what we're going to do. We'll look at the dataset, select the filtering, generate a sample of records, a random sample of records. This is an aggregation, and we'll create a dataset containing a subset of data. Next month's webinar, what is Hive? We'll cover these in more detail, like loading data tables, creating tables, et cetera, et cetera. Okay. Now, this is where it gets tricky because this is where we go into a live demo mode. Excuse me for a minute while I check if I've got all the right things available to me. Okay. When you first run your sandbox in VM player, whatever, you end up with a screen like this. You don't have to touch the screen in reality. All you're interested in is this web address here because that is the web address that you're going to put into your web browser, any modern web browser, and you'll get this screen up here. If you click on the advanced options, down here you'll see a reference to Hive, and this is what we're going to use. It gives you the address. You can just click on that. It gives you a user ID and password. Now, I've actually already logged into Hive, and this is the screen that you're going to end up with. Within Hive, you can access the various other components of Hadoop, some of which we're going to use, some of which we won't. So, what we're going to look at, we're going to use the Hive UI, which is the Hive editor. It's where we can write queries. We're going to look at each catalog, which is where your tables are going to be stored, and file browser where your files are being stored. We're actually, we are just going to look at those, and then we're going to move on to the other system to do the demonstration. So, if we start at the file browser, for user Hive, there's a little bread drum down here, you see all the users, little folder icons. You click on the folder icon, it shows you the files in the folder. Just what anyone would expect of a file system. Hive makes use of tables. So, one of the things that you often have to do is create a table based on your file. And again, the interface helps you out here. It gives you an option to create a new table from a file. If you click on that, you give it a table name, you can give it input file. If I say choose, I pick one of those, or I can upload a file from my PC. So, it's quite flexible, it'll do most of the things that you really need to be doing. We won't let you do it because we've got all the files in place for what we're going to demonstrate. The query editor, you just write your queries in here in HQL, select star from question there. Question there. Semicolon, very important at the end. And then you run execute, and it will run that for you. You don't have to worry about anything down this side particularly. And then when you want to execute, the results will appear on the screen. Now, everything I've just shown you is quite a complete way of doing most of the things you want to do. But for this demo, I'm actually going to use this deltoed for Apache Hadoop, which has all the same functionality. You can see here all my tables, ways of importing files and what have you. The file point of view, all I really want to show you is these little queries down here which we're going to run and see what happens. So, I've got my questionnaire file loaded, stored on thing. If we just do a select star from questionnaire, it will run that and it will show you all of the records in the file. So, this is based on the example we did before. So, I've got post codes, begin with M, question numbers, house numbers, question numbers, and answers randomly generated, okay? If I wanted to know how many records are in there, I could run this one, select count from questionnaire. I won't run that. I'll just tell you there's about 640,000 records in the file. The next thing we want to do is look at ways of cutting down this data. And the first way of cutting down is, well instead of you asking for four columns, why don't we just ask for two columns? Which may seem a bit trivial when I've only got four to start with, but if you've got a data set which has tens of hundreds of columns, this is a very important way of reducing the data down to what you actually need. The other obvious way of doing it is to use the statement down here, which in this case I'm going to take all of the columns, but I'm only interested in the rows where the postcode is M65AU. So if I run that and let that run, you can see it comes back all M65AUs right across the board. So again, if you can filter out record types or record values that you don't need, then this is the way to do it. And obviously you can use it too in combination. The next example is aggregation. There's a few things worth pointing out in this one. The first one is aggregation functions like sum and count and there's average and there's some statistical ones like standard deviation. You can use in place of or alongside or in association with column names. The point, the problem with doing that of course is that the result doesn't actually have a proper column name. So this as statement here as total yes is effectively creating an alias for what that column is. And so this is effectively the new name of that column when I produce the result. So I'm just gonna run that, do I run that? No, I didn't. So when that runs, this one will take a few seconds because it's more work involved for it. But when it comes back, when we see the answers we're gonna have three columns, we're gonna have postcode, total yes, and total questions and postcode. And they're grouped by postcode. So in fact, there's only one row per postcode and I've got the total number of yeses in those questionnaires and the total number of questions in that postcode. Of course, the reason that all multiples of 10 is because there's 10 questions in the questionnaire. The next I want to show you is, well, what if I just want to random selection? I've got a very large file. I just want to take a random selection and download that and see if that's any good in my PC. So here, this is where you do it. You effectively split your data set. You tell the system I want to split the data set on a number of buckets. And in this case, I've chosen 64 buckets. You can have as many as you like. The more buckets you've got, the less records are gonna end up in each bucket. So if I run this one, I'm dividing by 64 and you can see I get these records back and just 9, 14, 18, 19. If I was to run that again, because I've put a value in the RAND function here, it means I will always get this consistent set of records back. So if you need to be able to reproduce what you've done, that is the way to do it. Before, well, everything we've done so far just produced a result onto the screen down at the bottom here. But of course, in many cases, you actually want to store that for further processing elsewhere. And the way that is done is to use a create table as a statement. In fact, what I've got here is create table if not exists. And I've given it a name of the table and as. And the query behind it below it is exactly the same as we saw before. Now the point about the questionnaire postcode, if not exist is if the questionnaire postcode does exist, it's not going to do anything. And if I run that, it'll come back almost straight away saying, yeah, that ran successfully. It just didn't actually do anything because questionnaire postcode actually exists down here. I can actually delete it from this interface, but you can also drop them manually. So I've got a drop table questionnaire postcode there. And if I run that, it will actually drop that table. Drop equals delete. If I run this again, it will repopulate it. Or put same ones in there. Now as a final example, I want to show you a mixture of what we've done so far. So we're going to create a table called questionnaire answers. We're going to do aggregation by PC in question number. And we want the postcode. We want the question number. And this little, slightly complex calculation here using aggregate function sum and count is going to do our percentage of yes answers. So I've called that yes answers. And if I run that, what I get back is nothing visible because it's self listening just in returning. If I then ask to show me some of those records from that questionnaire answers which we've just created here, it will come back and it will show me for the first postcode that's got M65AA, questions one to 10 and the percentage of yes answers. And that query encapsulated the whole of our map reduce example that we showed before. So this is a very clear indication why you really don't have to worry about map reduce because there's always far, far easier ways of doing things. Okay, that is the end of the demonstrations. I think that is the end. So we just have a summary now. So let's remember, there may be no choice in using big data, especially if you don't control a source which increasingly is the case. And do open big data tools are just the tools. You're going to use them to get the data the way you want to deal with it. You need them to do all of your analysis or to cut the data down to size for your preferred desktop application. Although Java MapReduce are available, there's an increasing number of other tools available which will make the processing simpler. And that is the end. Thank you, Peter. That was very interesting. I'd just like to add a few things about the work that you can do to service is doing around big data. We are scaling up to big data. So we are in the process of setting up the Duke system and liking to be able to process and have large data sets and analyze state, safeguarded and secure data. So all types of data with different access conditions. However, this is very much work in progress on our side. It is a very complex project and we will be updating users. So watch this space. You can follow us on Twitter, Facebook. We've got a blog and an amazing list as well. As Peter mentioned, we will be running other training events. So there's two webinars coming up. One about Hive on the 22nd of March and one about Spark on the 19th of April and you can see them on screen. But we will be providing some more guides about this, how to download a sandbox, for example, through your own computer and we will having workshops. So to get the full list of all of our events, you just have to use the data service news and events and events. And if you do join our mailing list, then you will be emailed every time we add a new event. And I do want to say that this is the first time we're running this webinar on Hadoop. So we welcome any feedback at the end of the webinar. Whenever you leave the webinar, there's going to be a survey popping up asking you just a couple of questions. And we really appreciate if you took the time, if you had any comments or suggestions for improvement, please send them to us. And we'll now take questions. So thank you very much for attending this webinar. Bye everyone.


Functions of a Lesson Plan Foundation First of all we must understand that the lesson plan is the most important foundation in English teaching. With a sound curriculum plan, perfect teaching can be carried out. Set out the purpose of teaching in the course plan. Arouse the students' interest in learning English, cultivate their intention to learn English, and build their confidence in learning English initially. To cultivate the students with the necessary language sense, and good phonological and intonational basis, and good study habits. Give them the initial potential for simple day-to-day communication in English. Cultivate students' potentialities of observation, memory, thinking, imagination, and creativity at the same time. Teaching tasks Secondly we must understand the teaching tasks in the curriculum plan, be able to read and recognize speech sounds, and cultivate students' listening and speaking potential. Be able to master the vocabulary, sentence patterns, and language materials. Can read, speak, understand, and write everyday communication language to improve students' potential in language use. Can progress perception understanding grammar, grasp the elementary grammar knowledge. Good lesson plan checklist Before you start the lesson, there are several practical things you can do to make sure your lesson go smoothly. Check that you have your lesson plan. Run through your lesson plan and make sure you have all the necessary aids and materials needed. Check that the equipment works. Lay out materials and aids so that you can easily find them. Arrange the seating as desired. Make sure that the board is clean. Be ready to chat with the students as they come into class. This will help break the ice with the students and get them in the mood to learn. At the start of your teaching careers, you are probably going to want to structure your plans more, so that you have a clear guide as to what you want to achieve and how you are going to do it. Including all of the following and lesson plan, learner objectives, personal aims, language point, teaching aids, anticipated problems, of students and the teacher, procedure, phase, timing, interaction, class level, number of students, date and time, teachers and observers names. A lesson plan is a teacher's detailed description of the course of instruction or learning trajectory for a lesson. A daily lesson plan is developed by a teacher to guide class learning. Details will vary depending on the preference of the teacher, subject being covered, and the needs of the students. A lesson plan is the teacher's guide for running a particular lesson, and it includes the goal, what the students are supposed to learn, how the goal will be reached, and a way of measuring how well the goal was reached. Lesson plan and unit plans. A well-developed lesson plan reflects the interests and needs of students. It incorporates best practices for the educational field. The lesson plan correlates with the teacher's philosophy of education, which is what the teacher feels is the purpose of educating the students. Secondary English program lesson plans, for example usually center around four topics. They are the literary theme, elements of language and composition, literary history, and literary genre. A board, a thematic lesson plan is preferable because it allows a teacher to create various research, writing, speaking, and reading assignments. It helps an instructor teach different literature genres and incorporate videotapes, films, and television programs. Also it facilitates teaching literature and English together. Similarly lesson plans focus on content, analytic thinking, scaffolding, and the practicality of lesson structure and meeting educational goals. Unit planning is the proper selection of learning activities which presents a complete picture. Unit planning is a systematic arrangement of the subject matter. Unit is an organization of various activities, experiences, and types of learning around a central problem, or purpose developed cooperatively involving planning, execution of plans, and evaluation of results. Criteria of a unit plan needs capabilities interest of the learner should be considered. Prepare it on the sound psychological knowledge of the learner. Provide a new learning experience, systematic but flexible. Sustain the attention of the learner till the end. Related to the social and physical environment of the learner. Development of learner's personality.