Data Strategy: How to Profit from a World of Big Data, Analytics and the Internet of Things

> Available 04.28.2017 > DATA STRATEGY : How To Profit From A World of Big Data, Analytics And The Internet of Things. > Author, Expert, etc. > ( Twitter @BernardMarr ) > ( 11+ Chapters, 186+ Pages ) > ( About The Author, Acknowledgements ) > 01.Why Every Business Is Now A Data Business. > 02.Deciding Your Strategic Data Needs. > 03.Using Data To Improve Your Business Decisions. > 04.Using Data To Improve Your Business Operations. 05.Monetizing Your Data. > 06.Sourcing & Collecting Data. > 07.Turning Data Into Insights. > 08. Creating The Technology & Data Infrastructure. > 09. Building Data Competencies In Your Organization. > 10. Ensuring Your Data Doesn't Become A Liability : Data Governance. > 11. Executing & Revisiting Your Data Strategy > INDEX > ( Acquired By Michael GreenGold 09.06.2017 )

I think this is a really good book to get people thinking about how they can use big data to generate value in business.There are only three reasons I didn't give it 5 stars. First is that the impression I had that readers would come to the conclusion that working with internally generated data, much of the structured data that you need to integrate with big data to make sense of it, should be easy. My experience has been that internally generated data, even internally generated data that businesses have had for years, is anything but easy to work with. Most businesses have duplicate copies of data that get out of sync with each other. They also have applications and databases built in functional silos that don't integrate well with each other. Particularly if a business has grown by acquisition, then it is going to end up with lots of incompatible IT systems and databases that contain similar data that could be very difficult to integrate to get a whole view of the business. That integration is really hard to do. For example, Gartner estimates that fewer than 25% of master data management implementations (a data integration technology) are successful.The second reason is that I think the division of the ways to use data into separate categories of making better decisions, improving operations and monetizing data is a little too simplistic. Making better decisions and improving operations based on data will result in financial benefits - i.e. monetization. I think that connection needs to be drawn. In addition, you can really only monetizing data by selling data, or products containing data, to customers if those customers will see value in using it to make better decisions and improve operations of their own. So monetization of data all starts with better decisions and operations enabled by the data. Its misleading to draw such a distinction between them.Third, I think it places too much emphasis on using data to make all decisions. You really want to apply data when the risk and cost of making a bad decision by intuition or experience is worth the cost of obtaining and analyzing the data. Cloud-based data services do make it cheaper to obtain and analyze data than it has ever been. But there still is a cost to do so, especially if you need to integrate big data with internally generated data that is currently not well integrated. You want to focus on the data and analysis for decisions where that cost is justified. "How to Measure Anything" by Douglas Hubbard has a really good discussion of the economic value of data in making decisions that would be good to refer to.But, all in all, it is a very good book whose time has come. All businesses need to take data seriously in the 21st century. Those who don't, ignore it at their peril. This book should help them determine how data, especially big data, can be used to add value to their businesses.

Interesting topics and trends were covered by the author, making a great reading experience as well as a source for interesting insights.

The author could have put real depth behind the examples, but they were high level to the point you could find from googling around. This is a short, superficial book, that nevertheless may be a good intro to the topic if you have not looked into it.

Bernard Marr is an authority in this field, therefore it is easy to understand how Data Strategy will play its role in business.

Every Consultant should have a copy.

Data has become an integral part with most, if not all, aspects of life. Bernard Marr shares how far data has come in regards to product development, the health industry, supply chain, social media, politics and many other important sectors. He also shares there is so much more that can be captured by the use of Big Data, Analytics and the Internet of Things.While data can help with efficiencies in so many areas, Big Data users must be cognizant of the notion that too much data is not always a good thing especially when it will not be used as intended. While I agree with this to a certain extent, analysts would much rather have more data available to them than not enough data. The most important objective to remember is how does an individual plan to use the data provided to them.I tend to work more with internalized structured data which is easier to work with. It is usually processed into the databases and tables with the appropriate columns needed for me to conduct analytics as I see fit.It was reassuring to see the importance of data and how much more that can be done with it, depending on its intended use. I highly recommend this book to anyone wanting to understand the overall importance data plays in strategy. There are some instances where I wish the author would be more detailed, but still a very good read!

Very good book.