Modern retailers collect data from a multitude of consumer engagement channels, including point of sale systems, the web, mobile applications, social media, and more. They hope to use this data to derive greater customer insights, promote increased brand engagement and loyalty, optimize pricing and promotions, streamline the supply chain, and enhance their business models.
Data from the retailer’s transactional systems has historically been stored in an enterprise data warehouse (EDW) or other database, but these traditional data repositories are not well suited for the newer, unstructured data types like log files, social media updates and information from in-store sensors.
Apache Hadoop helps retailers store and manage data from these new sources more cost effectively, and lets them combine it with data they already have from traditional sources to create new efficiencies, opportunities and insights.
Anu Jain, director of enterprise architecture at Target, shares some of Hadoop’s effect in her organization at a Hadoop Summit North America panel. “Companies like Target—bigger companies—we are used to traditional ways of thinking, but [the Hadoop] ecosystem is bringing to the forefront new kinds of possibilities and opportunities.”
On Monday September 22 at 10am Pacific time, Greg Girard, program director for omni-channel analytics strategies at IDC Retail Insights and Market Ledbetter, vice president for industry solutions at Hortonworks, will host a webinar to explore some of these “possibilities and opportunities.”
This Hortonworks white paper explores more of the popular use cases driving the rapid adoption of Apache Hadoop in retail enterprises, including: