By Bill Franks

Very few businesses today reject the idea that being data driven and making use of analytics is critical to success. However, many do a poor job of actually becoming data driven and developing the analytics required to do so. One reason for the difficulty is the complexity and scale of the data and analytic processing required to achieve success. It is no small task to successfully capture, analyze, and act upon all of the data available to inform business decisions today.

The methods that were widespread early in my career have proven to be insufficient in today's world. Without taking advantage of the latest tools, technologies, and analytic techniques, it simply won't be possible to realize the goal of being a truly data-driven company. That certainly sounds like an intimidating thing to say, but it needn't be. The fact is that many companies have already successfully adapted to, and implemented, today's best practices. It is also possible for you and your organization to do so as long as you take the time to educate yourself on the options. By reading this book, you've taken a good first step.

In the book, Tho Nguyen provided some very detailed descriptions of the life cycle of data, several key technological and architectural options for analyzing data, and how to tie them all together to achieve success. As Tho made clear, there is not a single “right” answer that covers every type of data, every analytic need, and every business problem. That is simply an unfortunate fact of life when pursuing today's highly complex and massively scaled analytics. However, saying that there is no single “right” answer doesn't mean that it is hard to find an answer that will work for you. By assessing your needs and using what you've learned in this book, you will be able to draft a solid set of plans that will work for your organization.

One thing that the book goes out of its way to do is to provide some examples of organizations that have utilized the various approaches discussed. The examples make the technical points seem much more tangible and help to illustrate the strengths and weaknesses of different approaches. I have always found that the best way to understand how a technical or architectural approach actually works is to review how it was put to use in a real-world setting. By providing the numerous examples, Tho was able to provide important context to the key points he made.

While it has made life more difficult in some ways, the complexity of today's analytical environments has freed us in others. As Tho rightly pointed out, the right solution for any given company will likely contain several different platforms and processing methods working together to get the job done. In-memory processing won't solve all problems today, nor will in-database processing, nor will cheap disk farms. Each of those has a place, depending on the type of analytics required, the volume of the data involved, and the value of the problem being addressed. Rather than making an either/or decision, organizations must stitch together several technologies and approaches and then proceed to harvest the best each has to offer.

In the end, it isn't the technology that matters nor is it the data. What really matters are the results that are successfully derived from them both. This is where the real value of the book is found. As the examples in the book illustrated, incremental gains in analytic power and performance aren't what will be enabled by adopting the approaches in the book. What will be enabled is a quantum leap in performance.

The opportunity is not to take current analytic processes from many weeks to a few weeks or many days to a few days or many hours to a few hours. That would be interesting and possibly even compelling enough to get you to take action. However, such gains are still incremental in nature and in most cases won't fundamentally change the scope of what is possible. What you should be most excited about is the ability to take those many weeks down to just hours, or those many days down to just minutes, or those many hours down to just seconds.

That level of performance improvement enables an entirely different depth, breadth, and frequency of analysis. Just the type of improvement needed to become data driven in fact! The gains discussed in the book are real. I've seen them, and Tho could have added example after example had there been space. He didn't focus on a few extreme examples to artificially inflate his case. He simply picked a representative sample of a much broader set of success stories. With a little research, you'll be able to find many more yourself if you desire.

If you want your organization to maximize its success and become one of the companies that successfully implements a data-driven strategy, you'll need to seriously consider adopting one or more of the approaches in this book. The approaches have been developed, tested, and proven successful by some of the world's largest, most complex, and most successful companies. Tho has been lucky enough to have a front seat to witness what many of them have done. Take advantage of the view he's provided you from his seat as you move forward from the book. Both you and your organization will be well served if you do.

Bill Franks
Chief Analytics Officer, Teradata Author of Taming the Big Data Tidal Wave and The Analytics Revolution