OpenBI: Data-Driven Intelligence to Discover New Possibilities

Steve Miller, Co-founder & President
Having taken a BI consultancy public in 1999, the then future founders of OpenBI shared dreams of helping companies become evidence-based and data driven. Chicago-based OpenBI was the culmination of that dream. Founded as a data warehousing and business intelligence professional services company, over a span of 8 years OpenBI has gradually expanded its portfolio to include Big Data analytics and data science.

“The company’s ‘bullseye’ is at the confluence of BI and data science. We’re able to bridge the BI-data science divide—combining the accumulated wisdom of BI with the get-it-done urgency of data science,” affirms Steve Miller, Co-Founder & President at OpenBI. Miller sees data science as the ‘raison d’etre’ of many companies that OpenBI works with. In contrast to BI, which revolves on performance management, data science focuses on data products for new and existing businesses. “If these companies don’t get Big Data/analytics right, they’re out of business. We help them turbo-charge their product development,” says Miller.

OpenBI’s Big Data offerings are driven by technologies such as Pentaho Data Integration (PDI), MapReduce, Pig, Hive, Spark/Shark, R, Python etc. that help engineers be productive, while promoting maintainable code and an integrated approach to managing Big Data and data warehouse content. The company’s Big Data architecture includes new high performance analytic databases like Vectorwise, Netezza, Vertica and Greenplum that support a SQL-based capability of summarizing billions of rows of structured information. Miller notes that OpenBI has evolved from its early open source-only roots with BI software companies Pentaho and JasperSoft to now partner with Big Data/analytics vendors Cloudera, HortonWorks, Tableau, Actian and Alteryx.

“With Big Data as a catalyst over the last 4 years, OpenBI’s business has expanded from its DW/BI beginnings to now include analytics, visualization and data science,” said Miller. The company serves both large companies with established intelligence infrastructures and start-ups driven by data. edo, a provider of tailored, measurable and scalable card-linked platforms to help marketers, merchants and banks increase customer loyalty, contracted OpenBI to recommend and execute a comprehensive Big Data and business intelligence solution.
The ever-increasing data volumes processed by edo mandated an infrastructure that would be able to keep pace with the company’s initiatives to grow its customer base. edo’s operational and analytical databases were suffocating from data; reporting processes were lagging; and data build process times couldn’t meet their allotted windows. After first developing a roadmap, OpenBI collaborated with edo as part of an integrated team to implement the two-phase project: first enabling basic BI, and then facilitating Big Data processing. The joint effort delivered the foundation of an expanded analytics infrastructure powered by a Hadoop cluster to ingest and process data. The migration to the Hadoop environment allowed edo to expand their analytics horizon and provided the ability to identify and explore new opportunities to benefit their customers.

“Our customers like the fact that our ‘projects’ tend to be short—3 to 4 months—and our infrastructure proposals are generally less costly than big-vendor solutions,” states Miller.

Responding to market demand, OpenBI’s also extending its business working with OEMs to embed BI/analytics in their existing SaaS offerings

Envisioning a fundamental change in data warehousing in coming years, Miller believes SQL-based Hadoop will soon challenge the traditional data warehouse and that next generation Hadoop solutions will be much more productive than today’s. He notes the excitement surrounding BDAS (Berkeley Data Analytics Stack) that will provide more accessible and comprehensive solutions for Big Data /analytics.


Chicago, IL

Steve Miller, Co-founder & President

Professional services firm focused on helping customers extract maximum value from their growing data assets.