Welcome to another installment of Inside the Data Reading Room, a regular feature of this blog where I take a look at some of the recently published database- and data-related books. In today’s post we’ll examine a book with a unique spin on data governance, a book on MDM and Big Data, and an A to Z guide on Business Intelligence.
The first book we’ll examine inside the Data Reading Room is Non-Invasive Data Governance by Robert S. Seiner (2014, Technics Publications, ISBN 978-1-835504-85-6). This book offers an insightful and practical approach for embracing data governance best practices by evolving existing data governance activities. The premise of the book, as Bob so aptly states early on, is that “(a)ll organizations already govern data. They may do it informally, sometimes inefficiently, often ineffectively, but they already govern data. And they all can do it better.”
The book does a wonderful job of explaining the trademarked phrase that is the of this book, “non-invasive data governance,” as well as to guide the reader along the path of formalizing and improving existing data governance practices. The key, according to Seiner, is not to start from square one, but to build upon the data responsibilities that are already being performed within the organization.
If your organization is planning to embark on a data governance project, is looking for help for your existing data governance practice, or simply desires a useful, non-invasive method of managing and governing your data, look no further than Seiner’s informative Non-Invasive Data Governance.
Next up is Beyond Big Data: Using Social MDM to Drive Deep Customer Insight by Martin Oberhofer, et al (2015, IBM Press/Pearson, ISBN 978-0-13-3505980-9). Written by five IBM data management professionals, this book offers up new ways to integrate social, mobile, location, and traditional data.
Even with all of the new big data and analytics books being published this book is worth seeking out for its unique perspective and focus. Covering IBM’s experience with using social MDM at enterprise customer sites, the book provides guidance on improving relationships, enhancing prospect targeting, and fully engaging with customers.
In Beyond Big Data you will be introduced to a not only the basic concepts of master data and MDM, but its role with social data. By combining social and master data the book shows how to derive insight from this data and to incorporate it into your business.
Along the way the authors help to explain how social MDM extends fundamental MDM concepts and techniques, method of architecting a social MDM platform, using social MDM to identify high-value relationships and more. The book even tackles thorny issues like the ethics and privacy concerns of gathering and using social MDM.
What the book is not, is another tome attempting to describe Big Data; what is, is a useful approach and roadmap to exploiting a new Big Data niche – social MDM.
And last, but definitely not least, we have Rick Sherman’s impressive new book Business Intelligence Guidebook: From Data Integration to Analytics (2015, Morgan Kaufmann, ISBN 978-0-12-411461-6).
This 500+ page tome highlights the importance of data to the modern business and describes how to exploit data to gain business insight. Throughout the course 19 chapters describes the requirements, architecture, design, and practices that should be used to build business intelligence applications. The pratical advice and guidelines offered within the pages of Sherman’s book will help you to build successful BI, DW and data integration solutions.
The overarching theme that business people need to participate in the entire process of building business intelligence application is incorporated into the entire book. Each of the seven (7) parts that the book is organized into provides useful and actionable knowledge covering the following areas:
- Concepts and Context
- Business and Technical Needs
- Architectural Framework
- Data Design
- Data Integration Design
- Business Intelligence Design
By deploying the information contained in this guidebook, you should be able to successfully justify, launch, develop, manage and deliver a highly-functioning business intelligence system. And do it on time and within budget.
A companion website includes templates and examples, further discussion of key topics, instructor materials, and references to trusted industry sources.
All in all, we have three recommended new data books that are well worth your time to seek out and read. Doing so can only help to improve your data knowledge and employabaility.
Other Books of Note
- Developing Analytic Talent: Becoming a Data Scientist by Vincent Granville, Ph.D.
- Data Smart: Using Data Science to Transform Information into Insight by John W. Foreman
- Social Data Analytics: Collaboration for the Enterprise by Krish Krishnan and Shawn P. Rogers
- Practical Cassandra: A Developer’s Approach by Russell Bradberry and Eric Lubow