Authors: Martin Oberhofer, Eberhard Hechler , Ivan Milman, Scott Schumacher and Dan Wolfson
Publisher: IBM Press
Pages: 272
ISBN: 9780133509809
Print: 013350980X
Kindle:B00OM1MBKA
Audience: Technical managers
Rating: 3.5
Reviewer: Kay Ewbank

The subtitle of this book is Using Social MDM (Master Data Management) to Drive Deep Customer Insight, and it takes a formal, big business, look at social media and how it fits with a classic data management strategy.

You get the feeling middleware is these guys’ middle name, which is either off-putting or attractive, depending on your viewpoint. If you have loads of CRM, ERP and ecommerce systems and you’ve been asked to make social media fit in as part of it, this is an excellent read. If the phrase ‘use case’ gives you the shivers, you’re best off avoiding this book.   

The book starts with a chapter introducing social MDM. This gives a good explanation of how master data management is used to clean and standardize disparate data into a single master data system, then goes on to explain how social data from ‘observed’ sources such as Twitter, blogs, or by collecting purchasing history or website navigation. They then go on to look at how social MDM can be used for improved target marketing and better customer experiences.

Chapter 3 introduces a capability framework for social MDM, or to put it another way, a definition of what you should be able to do to your data, and how it should fit together. Having set out what capabilities you need, the authors then go on to set out a social MDM reference architecture, where they discuss the components that should form the framework, then in the next chapter reach the topic of which software will give you the features you need.

A chapter titled ‘social MDM and customer care’ looks in detail at how to use social MDM to make your customers happy by analyzing your social and other data, linking it to MDM, then using it to deliver a more tailored customer experience. Marketing is next to be tackled, with examples of how you can create targeted marketing campaigns, and how to identify influencers.  

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There’s a chapter on mobile MDM that has some interesting observations, and that then goes on to look in detail at IBM’s MobileFirst strategy (the authors are all data management specialists at IBM). The book ends with a bit of crystal ball gazing in a chapter on future trends of MDM, where the authors look at semantic MDM. This is the technique where data is mixed with semantic graphs to show links and connections. The chapter ends with a look at privacy and ethics.

I wasn’t sure about how useful this book was going to be when I began reading it, but having finished it I felt the authors had made a lot of useful points. If you work in the sort of company where you need a strategy for managing social data, this book would give you the tools to create one.  

For recommendations of Big Data books see Reading Your Way Into Big Data in our Programmer's Bookshelf section. 

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