algebraix data robin bloor
Algebraix mathematician Robin Bloor, PhD
Analysts estimate that the market for data analytics — the industry term for sifting through mountains of data until you actually learn something useful from it — will hit $125 billion this year.

This is an industry segment with a lot of fear, uncertainty, and doubt: Competing technologies, plus a lot of confusion about how to best put them to work, results in a lot of similar-sounding vendors all insisting that they, and only they, can help you get the most usage about your data.

But there's a dirty little secret with data analytics.

To get all of your data nice and tidy for analysis, it has to go through a process called "ETL," which stands for "extract, transform, load." It can be a costly, time-consuming, and error-prone process.

ETL software can cost big enterprises hundreds of thousands of dollars in licensing; hiring consultants to put it all into place can drive the price tag into the millions.

Enter Algebraix Data, a California-based data analytics startup that's changing the equation with what it calls "data algebra." Here's the scoop on its mathematical secrets.

"Today, enterprises of any size can use advanced analytics to turn their data into a revenue-driving asset, easily and affordably. And it all started with data algebra," says Algebraix Data CEO Charles Silver.

For the last five years, Algebraix has been working on data algebra, a hyper-specialized field of pure mathematics that uses set theory to describe any kind of data — charts, graphs, lists, whatever — in a way that can be understood and quickly processed by analytical systems, says Algebraix mathematician Robin Bloor, PhD.

"All of these files can be represented algebraically," Bloor says.

Algebraix CEO Charles Silver
In plainer English, data algebra is a way of looking at data, such that it doesn't need to go through that super costly, super-risky ETL phase. Algebraix's analytical systems just use math to break all of it down into a long, sophisticated equation that it can work with, without having to do any of the conversion itself.

It's a totally different way of doing things, and the company holds nine patents for the data algebra-based technology it uses.

For customers, it's easy to sign up for the Algebraix platform. It's hosted with Microsoft's Azure cloud platform, meaning it's all handled from the Internet. And it's a lot cheaper than those million-dollar solutions from legacy vendors.

Interestingly, Algebraix was first merely trying to build a better database, Silver says, but found that its would-be customers were increasingly turning to Amazon, Microsoft, and Google to suit their data-storage needs. And so it called an audible and decided to put data algebra to work as an analytics product, crunching all that data that sits in the database.

"The database is only good if you're going to use that data for something," Silver says.

For the first five years of the company's existence, Algebraix played its cards close to the chest and kept data algebra as a company secret.

But just recently, the company has started to open the door a little bit: It's published a book by two of its in-house mathematicians called "The Algebra of Data," and it's made the core data algebra algorithms available for any programmer anywhere to download.

The gist is that Algebraix is hoping to force data algebra into the spotlight, placing itself into the center of what it hopes becomes the next wave of analytics. Other programmers can use Algebraix's technology, but as the inventors, and the holders of the patents, the company stands to profit most.

"We'll be the ones to make a lot of money from this," Silver says.

Algebraix is a venture-backed startup with over $38 million in funding from undisclosed sources.