Big Data MBA - Driving Business Strategies with Data Science

Bill Schmarzo

Published by





Reviewed by

Len Keighley FBCS CEng CITP


9 out of 10

The book is aimed at the business community involved with the delivery of business benefit by the use of Data Science and Big Data. It covers a range of benefits and is not restricted to just increased revenue. Following an introductory section, the book contains 4 major parts and 15 chapters.

The content takes the reader through the stages of establishing a “Business Strategy for Big Data” rather than the more commonly seen approach of developing a “Big Data Strategy”, i.e. the use of Big Data without a business purpose to guide its delivery. The author is quite clear that the latter is not as advantageous as the former. In fact, it is also clear from the book that for Big Data to be a successful service to the business, the Business Strategy is key, and that the Business must take a more central role in the Big Data operation. This is emphasised in the book by the statement that, in the past, the Business handed over responsibility to IT for Data Warehousing, with the implication that, for Big Data, the same is happening.

There was recently an article on LinkedIn which presented the view that “Hadoop is Failing” whether this is correct or not is not relevant to this review but a lot of the facts being presented in the article seemed to be raised and answered by the contents of the book. Perhaps this highlights the need for businesses to take on board the concepts raised by the author.

This is the second book written by Bill Schmarzo with the first being aimed at an IT audience, but he felt that there were potentially bigger winners in the Business community and hence this second book. This focus on business can be clearly seen in the four main parts to the book, P1 - Business Potential for Big Data, P2 - Data Science, P3 - Data Science for Business Stakeholders and finally P4 - Building Cross Organisational Support.

Part 1 - Business Potential of Big Data, takes the reader through building the foundations of a business strategy that uses Big Data, rather than a Big Data strategy, for the organisation, therefore, paving the way for whether the dog wags the tail or vice versa. As part of this the Big Data Business Model Maturity Index is introduced and explained. This is a five-step index which places a business along the path of using Big Data to, at step one, monitor the business and at the top, step five, to undertake a metamorphosis of the business. The three intermediary steps take the business through insight, optimisation and monetisation (the creation of new sources of income).

Part 2 - Data Science, is a scene setting section to the data science concept as a precursor to moving the reader into the utilising those concepts from a business perspective. This is done by introducing several different analytical algorithms and when/where they might be appropriate to use. This is demonstrated by utilising a dummy company on which the algorithms can be deployed. The final chapter introduces the Data Lake and how this has allowed businesses to expand the data they can analyse, while being able to reduce the cost of storing the data in a usable form. This can be viewed in another way by comparing the storage capabilities and costs of the Data Warehouse against those of the Data Lake.

Part 3 - Data Science for Business Stakeholders, this section builds on Part 2 by enabling the business stakeholders to think like data scientists and identify what data and algorithms are fundamental to the business, and the decisions that the business must make. This is done by providing a framework that enables the business stakeholders to communicate and work with data scientists, by using a common understanding of the data and algorithms. In simple terms, it is not just about ‘more data’ but also understanding what the business could get from the ‘correct analysis’ of that data.

Part 4 - Building Cross Organisational Support, this final part of the book provides a foundation for transforming (metamorphosis) of the business, to better integrate Big Data, in its widest sense, into that business from both an organisation and cultural perspective. Including those of a human, procedural and roles/responsibilities nature, thus allowing that business to achieve the fifth step of Business Metamorphosis. The final chapter of this part, and of the book, is ‘Stories’, a section on Big Data deployment that, it is hoped, inspires the reader, perhaps allowing them to draft their own stories that fit their own organisations.

Further information: Wiley

February 2017