Self-Service Analytics for Big Data
The Spreadsheet Experience
In thinking about the idea of giving users more power, one naturally thinks of spreadsheets. Spreadsheets allow nontechnical people to do things that might otherwise require hard-core programming. They allow business people to do their own analysis and be masters of their domain. Of course conventional spreadsheets aren't able to handle large amounts of data, so their use in more serious analysis is quite limited. But what if spreadsheets could handle more data? What if there were a spreadsheet that could handle a trillion rows as easily as Excel handles one thousand?
We needed to identify annual trends of total store quantities. We had to decompress our weekly SAS datasets (80 million records/week). However it would take several days because I had to decompress many datasets (one hour each), then extract the weekly information and merge all the weeks. We executed the query against the historical data literally in a matter of seconds. Using this approach I could complete this task in about 15 minutes. It saved us a lot of work and provided us with very useful information, which we would have never been able to access before. |
Bringing Spreadsheets to Big Data
With this in mind, in 2000 we built a Cloud-based service for data management that brought the spreadsheet experience to large amounts of data, even Big Data. Now, many years and hundreds of customers later, our unique and proven technology allows users to gain unparalleled insight into their businesses without the usual technology hurdles.
We also provide a choice of technical interfaces typical of conventional databases, so we can be thought of as a database. But the flexibility and performance necessary to support the spreadsheet experience has tremendous benefits to these interfaces as well. It makes them faster and more pliable, and it allows programmers to create applications more quickly.