In an Informatica blog post last November: “Data Warehouse Optimization: Not All Data is Created Equal” I talked about the importance of Hadoop in optimizing data warehouse infrastructure for cost and scalability. To help organizations get started saving up to millions in infrastructure costs, Informatica teamed up with Cloudera to define a reference architecture for data warehouse optimization. We also published a white paper to help guide those interested in learning more: Data Warehouse Optimization with Hadoop: A Big Data Reference Architecture Using Informatica and Cloudera Technologies.
Recently Informatica released Informatica 9.6 which includes new capabilities in support of Kerberos and HBase. The majority of customers over the last year that purchased the PowerCenter Big Data Edition on Cloudera actually start off by optimizing their data warehouse. These customers move data and processing onto Hadoop that was previously consuming too much capacity in their traditional data warehouse environment thereby extending their IT investments for BI reporting and analytics.
Data warehouse optimization is just the beginning for these customers. While the initial and ongoing cost savings are very significant they now have a powerful data platform in place to realize the promise of big data. For example, a large global financial services and communications company implemented an enterprise data hub using Informatica on Cloudera. This customer is using Informatica to store and process data on Cloudera from more than 18 data sources including relational transactions, mainframe data and web logs that normally would consume the capacity of their data warehouse. Now that the enterprise data hub is in place, this company is minimizing the risk of fraud and optimizing their business to create a more personalized customer experience across multiple products and service delivery channels. A high-tech customer is using Informatica with Cloudera to build an enterprise data hub as a central source for cross-company data analytics to better serve customers. And a large healthcare government agency is creating an enterprise data hub to improve fraud detection and support healthcare initiatives. Now is the time to start saving on IT infrastructure costs with data warehouse optimization and putting in place an enterprise data hub to support big data projects.
John Haddad is Senior Director of Big Data Product Marketing at Informatica Corporation. He has over 25 years’ experience developing and marketing enterprise applications. Today, he advises organizations on Big Data best practices from a management and technology perspective. Prior to Informatica, John was Director of Product Marketing and Management at Right Hemisphere (acquired by SAP) and held various positions in R&D and Business Development at Oracle Corporation. John holds an AB degree in Applied Mathematics from U.C. Berkeley.