Getting Data Right

Chapter 6. Data Unification Brings Out the Best in Installed Data Management Strategies

James Markarian

Companies are now investing heavily in technology designed to control and analyze their expanding pools of data, reportedly spending $44 billion for big data analytics alone in 2014. In relation, data management software now accounts for over 40 percent of the total spend on software in the US With companies focusing on strategies like ETL (extract, transform, and load), MDM (master data management), and data lakes, it’s critical to understand that while these technologies can provide a unique and significant handle on data, they still fall short in terms of speed and scalability—with the potential to delay or fail to surface insights that can propel better decision making.

Data is generally too siloed and too diverse for systems like ETL, MDM, and data lakes, and analysts are spending too much time finding and preparing data manually. On the other hand, the nature of this work defies complete automation. Data unification is an emerging strategy that catalogs data sets, combines data across the enterprise, and publishes the data for easy consumption. Using data unification as a frontend strategy can quicken the feed of highly organized data into ETL and MDM systems and data lakes, increasing the value of these systems and the insights they enable. In this chapter, we’ll explore how data unification works with installed data management solutions, allowing businesses to embrace ...