Our experiences, over the past decade or so, working with the Business Intelligence solutions and later “data discovery” technologies, made it easy to discover the evolutionary thread in the BI discipline.

What makes today’s big data challenge different from traditional large database challenges is that besides an order of magnitude increase in the data size the new applications need to incorporate a large volume of diverse rapidly changing data.

The traditional solutions to big data analysis involved separating the analysis layer from the storage. This is typically done by organizing data into the analysis “cubes” almost requiring that the user knows the answers before starting the solution. One would need to make certain assumptions about the data, then develop the ETL (extract, transform, load) logic to populate the analytics database – that was typically based on a relational database, and later develop an appropriate interactive querying front-end using visualization techniques and often comprised of dashboards and reports that would help “uncover the stories hidden in the data.”

While this method worked, this approach broke when there was limited knowledge about the underlying data assets and since the data was often stripped of any “unknown insights” during the ETL process, the effectiveness of the BI tool was limited by what we already expected to know about

Our consultants have been working on the modern big data technologies such as Hadoop, Hive, Sqoop, Flume or Pig – to make available the expanded power of analysis for within reach and budgets of an average small and medium enterprise.

Our consultants have helped clients:

  • Manage and analyze large volume of data coming from a variety of sources like the device data ( cyber security, switch maintenance, network traffic).
  • Integrate internal application data with e-commerce and social engagement applications for sentiment analysis, targeted marketing analysis.
  • Recalibrate internal Data Warehouse / Analysis strategies and applications by leveraging Hadoop processes on commodity hardware to implement a solution that has a right balance of cutting edge technology and everyday practical solution that is cost efficient at the same time.

Our consultants and solutions frameworks can help discover how/ if Big Data Analytics tools, technologies and processes can deliver promised benefit client organizations. You can leverage our expertise to :

  • Maintain speed, functionality, and flexibility—additional architecture allows for exponential increases to “3 V” processing power.
  • Greatly extend the life of your DWA technology investment by accommodating newer user demands.
  • Place data in the appropriate data store for the intended use – avoid overspending and overstressing high performance analytic environments with unused or extraneous data types.

Strategic partner on key projects at :