Companies have a lot of different choices when it comes to how to store their data. But when it comes time for analysis, how and where your data is stored matters more than ever. Choosing the wrong data platform could be holding your company back a lot more than you realize.
At one end of the spectrum are legacy database systems built on the concept of always structuring data in rows and columns. These databases make analysis straight-forward and easy, but only for the data it can accept. In today’s world, more and more data isn’t structured, meaning they cannot be included for analysis, which gives your company an incomplete picture. The other concern is performance. Storing data in such a highly structured format is not optimized for analysis. Even with a moderate amount of data and a handful of users, performance will quickly become an obstacle for growth.
On the other end of the data spectrum are more flexible systems, like Hadoop. These data storage engines make it incredibly easy to ingest any type or quantity of data. However, when it comes time to retrieve that data for analysis, their lack of structure actually becomes a hindrance. The lack of any structure makes data analysis a difficult and inefficient task that takes both time and effort to accomplish.
Fortunately, there is a middle ground in the data architecture world, and that’s the type of data engine that is loosely structured. Elasticsearch, the platform that Qrvey is built on, is a good example of such technology. I’ve previously written above how Elasticsearch can save you big money. It offers the structure that makes analysis possible, but still remains flexible enough to include all of the semi- and unstructured data that your company has previously been leaving behind. Now, for the first time, all of your company’s data can be included for analysis while still enjoying maximum performance. No longer will you have to choose one extreme or the other. Now, you can enjoy analysis the way it was meant to be.