This week at Under The Radar we will be talking about 3 key concepts that have an impact on how businesses adopt big data analytics:

• :: Analytics over storage. Today, the quantity of data that companies store doesn’t matter as much as what they can do with it.  Banks don’t benefit from having lots of cash in the vault if it’s just sitting there; data is the new currency for businesses—and it’s time that businesses unlock the value. Check out the famous “Elephant and the Rider” analogy applied to Big Data.

• :: The end of the data sample. In the past, storage was expensive and business analytics software was slow. Businesses couldn’t analyze at scale either because they didn’t have budget to pay for more storage or the time to wait for software to analyze huge data sets. Today, storage cost has plummeted and any company can use commodity hardware to analyze 10 Terabytes in less than 10 seconds.  This performance would have cost millions a few years ago but it can now be executed for less than $10,000.

• :: The demise of the stack. For decades, IT has been led to believe that they needed to build costly best-of-breed analytics stacks, which typically meant buying a database, an ETL platform, and visualization tools.  Each part of the stack would be deployed by different parts of the organization and bought from different vendors. Beyond the obvious issue of technology integration, this led to lack of alignment and poor performance.

Until recently, most businesses were ill-equipped to efficiently analyze data; many were under the impression that they had to learn complex concepts and, as a result, less than 24% of businesses deployed business intelligence (BI) solutions. The solution is to move to simpler, more scalable solutions that remove the challenges associated with technology integration and enable IT to focus on helping the business deliver better performance rather than learning how to be become better technology integrators.

Indeed, the future of data requires simplicity.  Any business user should be able to buy the solution they need, work with it in minutes, and pay for it as a subscription.  Deploying any modern software solution should not require an army of engineers or consultants. The future of data is also about unlimited potential; technology should allow us to “squeeze more” out of the simplest machines so users don’t have to feel limited.  It should be seamless and offer the choice to deploy on premise or in the cloud.