Big Data Imperatives: Enterprise ‘Big Data’ Warehouse, ‘BI’ Implementations and Analytics by Soumendra Mohanty & Madhu Jagadeesh & Harsha Srivatsa

Author:Soumendra Mohanty & Madhu Jagadeesh & Harsha Srivatsa [Mohanty, Soumendra & Jagadeesh, Madhu & Srivatsa, Harsha]
Language: eng
Format: epub
Tags: Computers, Data Processing, Information Technology
ISBN: 9781430248729
Publisher: Apress
Published: 2013-06-26T04:00:00+00:00

Figure 5-7. Big data: MDM interactions

Big data represents many things. For some, it’s the technology we use to store, retrieve, and manage petabytes of data that we create each day. For many in enterprise technology, big data means using sophisticated techniques to analyze the large and growing volumes of transaction data in order to improve business decision making.

In big data and analytics scenarios, instead of being constrained to just intra-domain customer hierarchy dimensions following traditional MDM implementation styles, we will need a multi-domain MDM approach to view transactional data and external data entities through different data domain relationships (as shown in Figure 5-8). Sales could analyze data by customer, territory, and geography. Marketing could see the evolution of the buying process by campaigns, social media interactions, and click- stream analysis; finance can get a view across suppliers and sales, and marketing can also get an insight into the brand reputation and sentiments by looking at external data.

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