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Zoomdata 2017 Predictions: The End of Standalone BI Applications

VMblog Predictions 2017

Virtualization and Cloud executives share their predictions for 2017.  Read them in this 9th annual series exclusive.

Contributed by Ruhollah Farchtchi, CTO of Zoomdata

2017: The End of Standalone BI Applications

We're seeing the end of standalone BI applications, hastened by the rise of big data and volumes of information that have simply overwhelmed legacy vendor products. Those vendors built solutions for a standalone BI tool on a relational database that was the world of yesterday. Today customers want to bake analytics and visualization into their applications and services so users have this information ready at hand as part of the standard user experience. Accelerating the demise of the standalone BI stack, we see three key trends in 2017 that put users more in control of their information for rapid, real-time insights so they can make better data-driven decisions for their business.

1. Interactive exploration on the freshest data

Traditionally, BI and analytics has delivered limited static or relatively limited interactive exploration capabilities on data that was often out of date due to batch update and data warehouse ETL processes. In 2017, users of BI and analytics will increasingly demand free-form data discovery and exploration on data that is completely fresh and up-to-date.  Additionally, users will expect their BI application to observe their usage patterns and self-optimize to provide speed-of-thought analytics by predicting future data exploration requests.  

2. The end of static data models

Until today, BI tools have required considerable work by the user before delivering useful results of any kind. You have up-front data modeling, ETL processes to blend data into data marts and warehouses, and semantic metadata modeling.  This limited the scope of data available and constrained the kinds of questions end-users can ask and answer.  In 2017, we'll see increasing adoption of modern BI platforms that can be pointed by end-users directly at new data sources, without all of these up-front processes, and with the ability to virtually fuse data from multiple sources on the fly.  The new data warehouse will be more a collection of loosely integrated federated data sets rather than a set of relational tables with referential integrity definitions and constraints mapped out and defined.

3. Search-based analytics will gain greater traction

Traditionally, unstructured data has been analyzed using search tools such as Elasticsearch and Solr, with a completely separate infrastructure and user interface from BI tools used by the organization, limiting access and use by end-users.  In 2017 BI tools will increasingly be directly integrated with search engines, enabling speed-of-thought quantitative analytics on massive volumes of unstructured data, enabling end-users with increased flexibility in the range of questions they can answer, and without forcing organizations to pre-process unstructured data into fixed structured data marts and warehouses.

I recently gave a webcast where I discussed these predictions in more detail. Check it out here.


About the Author

Ruhollah Farchtchi is CTO of Zoomdata

Ruhollah is responsible for the Zoomdata technology stack and Zoomdata labs. He has over 13 years of experience in applying advanced architecture and design methods to help organizations turn data into actionable intelligence for decision making. He brings forward his deep expertise in Big Data, Data Science, Data Analytics, Information Extraction, Data Architecture, and Data Management from years of consulting with BearingPoint, Booz Allen Hamilton, and Unisys. At Booz Allen and Unisys, he led teams across multiple engagements and business domains to bring bleeding edge and emerging technology to the enterprise. 

Ruhollah Farchtchi 

Published Friday, December 16, 2016 9:05 AM by David Marshall
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