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Ross Serven

Associate Director, Technology Solutions Group, Data Integration Competency Lead
Ross Serven

Ross has over 12 years of experience in database systems. He currently leads the Data Integration Competency at Merkle. His core focus is designing and building marketing database solutions using a component based architecture. He has extensive experience on multiple data management platforms including SQL Server, Netezza, Oracle, and Hadoop. His extract/transform/load (ETL) tool knowledge consists of Informatica, DataStage, SSIS, DMExpress, as well as custom built ETL products. Before joining Merkle in 2008, Ross was Business Intelligence (BI) Consulting Manager for an enterprise resource planning (ERP) solution provider. His role was primarily focused on data warehouse and BI analytics for multi-channel retail companies.

Ross's Articles, Blog Posts, Webinars and More

No, Not That Data, the Other Data

Data Integration revolves around the ability to handle all types of data. However, some of the most important data we deal with might not be what you'd expect. In a quest to build more efficient processes, one of our top priorities today is to create and consume rich and powerful metadata, which is basically “data about data.” While many people might know its definition, not everyone understands its value. There are five main types of metadata: business, structural, navigational, analytical, and operational. Each plays a large part in the building of data integration components.

The ETL Tool: Hello, Old Friend

In the world of data integration, the need for an ETL tool is back in full force. It’s still solving the same problem as in the 1990s, but the equation has gotten a lot more complex. No longer are we only extracting data from mainframe systems, flat files, and other relational databases.