Big Data Analytics : Moving Past the Old Way of Doing Things

Posted by Naresh Agarwal on Aug 13, 2015 9:00:00 AM

When it comes to Big Data, many companies have a hard time moving past the old way of doing things.

In many cases, this is because the responsibility of doing Analytics, Business Intelligence and ETL is divided between different teams and groups within an organization. While Analytics is still largely a business responsibility, Business Intelligence and ETL activities are conducted within IT but delivered through the various teams or LOBs. Thus most of what is produced using big data is standard reports, dashboards, scorecards and other visualizations tools to report on KPIs.

This division of responsibility made sense in the past, when building data warehouses lead the data management strategy, or when massive amounts of unstructured data were not the norm. But this approach fails in the current age of agility, where hyper competitive business environments demand rapid innovation and change.

A sports analogy may be useful in describing why this approach is deficient. Imagine the chaos if we asked an American football team, with their different offensive and defensive teams, to play soccer. In this scenario, even the best football teams will appear chaotic, uncoordinated and slow, because they are not accustomed to playing together in this way.

On the other hand, those teams experienced at playing soccer, where all defensive and offensive player work together to drive the ball in the same direction, will be able to move much faster and in a streamlined way.

We believe that big data and the data science world today requires a team mentality; one where data engineers, data analysts and data scientists come together to leverage the most advanced technologies. This is the only way to acquire, process and analyze data all at the same time to deliver rapid insights.

That being said,recognizing the need to change and actually being able to facilitate that change are two different things. Companies that want to embrace this way of working with big data and analytics still face challenges. Few organizations have the right in-house people, skillsets and time to tackle more complex big data efforts.Some organizations have found the vast amount of data overwhelming, messy, fragmented and siloed. Understandably, they feel overwhelmed by the larger challenge of finding insights within the data. Others have worked with, or considered working with a technology partner, but were turned off by the “black box” approach to data, or hesitated because they believe any useful technology platform requires big budgets.

The problem is, by doing the same thing, companies are putting themselves at a competitive disadvantage. We recognize that the rules of the game have changed, and will continue to change. That’s why we built the Brillio Data Platform, designed to help enterprises adapt to this new world of constant change.

We do this with:

  • An open, integrated and end-to-end platform approach that brings in massive streams of unstructured and structured data for simultaneous analysis.
  • A technology stack that is pre-configured, to keep costs reasonable, but customizable and adaptable enough to meets specific customer needs.
  • The right tools, technology and techniques that help take data analytics to the next level.The right people and expert skillsets that range from technology to business.

The pace of technology and growth in data is not slowing down — in fact it’s growing at an astounding rate. It’s only with the right partner, platform, people and processes that companies can implement a continuous learning model that drives actionable insights and business innovation at the speed required in today’s world.To find out more about how the Brillio Data Platform addresses key big data challenges and enables high confidence decision making, click on the below.