Data Offices now can worry less on propelling Organization's growth enablers: Book Review

Data Management and Governance Services

The book’s front cover

Tejasvi Addagada

Tejasvi bio pic

Dattamza, an emerging leader in Data services, is pleased to announce reviews of the book, "Data Management and Governance Services, following the release.

Tejasvi Addagada is a leader in the data management industry, with over 10 years of experience, assiting banks setup chief data offices. He worked with fortune 50 banks with their several challenges.”

— Anvitha Mikkilineni

BANGALORE, INDIA, July 11, 2017 /EINPresswire.com/ — Over the past decade, most organizations have started to realize the importance of managing their data as an enterprise asset for their growth, though some are far from embracing the cultural change driven through data. It is nevertheless a fact that most people do not trust the data they regularly use. With the emergence of disruptors such as Internet of Things (IOT), machine learning, semantics and big data; firms have now started to realize that fit-for-purpose data is needed to derive powerful insights. Incidentally, based on a recent survey, 33% of such firms are actively governing their data today. Most of these firms embracing active data management culture, are also directly aligning themselves to a strong corporate governance.

There is no doubt in the firms, on the immediate and cumulative benefits from actively managing and governing the data. The focus now should be on differentiating data management from governance and standardizing them into services, to achieve the benefits. Further the focal point is gradually shifting from having to mature data management capabilities to monetizing direct and indirect benefits of data.

Tejasvi says that re-discovering and standardizing data management as services, is a major enabler to get past many barriers in adaption. The standardization, as listed using multiple examples in the book, is helping firms explore their capabilities further, to find efficiency, consistency and scalability in their data operations. Along with that, the recent drivers such as “managing data as a meaning”, “customer excellence” and “actively managing data risk” is pushing the need for alignment of data quality and metadata management to risk management and corporate governance principles. This is increasing the need for interoperability between data, business and risk functions. And thus, there is a need for operating models that consists of discrete functional modules that collaborate through service calls. The book is availabe for purchase in the stands, https://goo.gl/wHXN74

Quoting from the book, "Robin could not come to pick me up at the airport as her daughter was getting engaged the same day I traveled to Rancho. As the sun stood high, we started discussing the approach to analyzing the data strategy, over some sushi in a nearby restaurant. I was intrigued by the sous chef's ownership of having to sculpt the fish to prepare my sushi plate. Later, I came to know from Robin that the restaurant showed standards in sourcing the catch, cooking rice, cooling it, adding vinegar, and maintaining it at the perfect room temperature while he assembled the plate delicately. I was rather amused by the communication between the head chef, the sous-chef and the rest of the restaurant kitchen staff. This reminded me of the outcome that I was expecting from the data quality strategy as well as the importance of a communication plan during service set-up. Strategy analysis focuses on defining the current state and leveraging the same to define the future and transition states. For a data management and governance strategy, the emphasis is equally spread across people, technology and process capabilities contrary to the belief that it is only technology capabilities"

Ramesh Dontha, Managing Partner at Digital Transformation Pro, says that the book stands out for three reasons: It’s practical, It’s simple to understand and follow, It broadens the appeal to a larger audience. His review further states: "It’s practical: There are lots of really good books on theory of data management and governance, but enterprises are looking for guidance on practical steps. This book focuses on key components such as establishing a standardized metadata service and running a data quality service in almost a step-by-step fashion. I could see myself following the steps outlined in the book to set up data management and governance completely.

It’s simple to understand: Tejasvi leverages his practical experience to convey intricate concepts in an almost folksy manner to relate to everyday experiences. Let me give an example with discussion on data ownership in this book. Data ownership is a tricky item in data management and data governance. This book breaks that topic into 10 steps that anyone can understand and relate so it becomes easy to implement.

It broadens the appeal: One of the challenges with data governance is that few people understand its scope and importance. The benefits of data governance will multiply if more people in organizations can internalize the principles behind data governance, Tejasvi’s book accomplishes that objective by focusing on the most important features of data management and governance and explaining them in simple but practical terms. Ramesh's complete review is now available at https://digitaltransformationpro.com/book-review-data-management-governance-services/

While Doug Laney, a distinguished analyst from Gartner, quotes that the book is a solid guide and reference to standing up and managing a data governance and quality function. Doug further quotes: "Addagada acknowledges many of the challenges in doing so and how to overcome them. His examples are fun and informative, and frameworks are useful. Although I strongly oppose the notion of a "data owner" (due to this concept encouraging data silos/hoarding and inhibiting information's status as an *enterprise* asset), the accountabilities and responsibilities he lays out are legitimate and comprehensive.

The book discusses the difference between data value and data management value, and includes a value-risk framework model, I would have liked to see more depth in Chapter 7 – Assessing Value from Data Management and Governance, in particular a discussion of the various data valuation models available today and how they could be used to justify/prove the benefits of data management and governance." Doug's complete review is available at http://dattamza.com/bookstore

Tejasvi, the author, as interviewed says that his book provides step by step simple and effective approaches to set up and operationalize data management services that will realize the benefits of leveraging valid, accurate and meaningful data. A target state control environment embraced throughout the book should help simplify the data landscape and manage data as a crowd sourced meaning that reduces the total costs and enables growth through data capabilities.

Tejasvi Addagada
Dattamza
91-9581555727
email us here


Source: EIN Presswire