Category Archives: Infosphere Streams

Just finished reading: Customer Experience Analytics

This is another excellent free ebook from IBM that renders well on a kindle. This book can be down loaded from the IBM Information Management Book store  or the direct link here.

Overall like the Understanding Big Data book I reviewed last time I think it is a good introduction to the subject matter giving you a quick way to get up to speed with some of the concepts involved and the evolution going on around the social sphere and customer experience. The book is again split up into sections, this time three: Part One: The CEA Opportunity, Part Two: The Customer Experience Analytics [sic] Solution and Part Three: How to Package a Customer Experience Analytics [sic] Program.

Part One: The CEA Opportunity covers a few case studies of how various industries use customer experience to fuel decisions that affect the business and the customer.   It then moves on to how that our societies are moving toward increasingly automated way of interacting during the sales and marketing processes makes collecting the data for CEA a lot easier and quicker to act upon. The third chapter in this part looks at the evolution of the customer decision making process, and how a single customers influence on the wider world can (should) affect how a business deals with them. This raised some interesting thoughts in that basically people that are “listened” to (facebook, twitter, text messages in a social group) should be treated differently when they have a complaint than those that “listen” and do not contribute back, pushing “stardom” down onto those that are not famous, but are popular in a social group. The final chapter in this section looks at the “bazaar” of data that exists for CEA and touches on big data concepts again.

Part Two: The Customer Experience Analytics [sic] Solution is a slightly technical, but more theoretical look at with out pushing any particular products how you would go about creating you CEA solution. It covers Master Data Management (MDM), Stream computing, Predictive Modelling and a couple of other topics, but not to a depth to make you a master of these areas but at least enough to let you in on the conversation.

Part Three: How to Package a Customer Experience Analytics [sic] Program is basically how you would put together a business case for CEA and the conclusion of the book. The business case for CEA varies from needed to stay in business (mobile phone compaines) to currently only done on an Ad-Hoc basis and needs to be built up in the company or the industry.  It would be hard to place the company that I currently work for on this scale as I am un-aware of what and if anyone else does in the sector that we are in, but I think it has legs and should be something that we should be pushing, would defiantly like to get involved in the technical side.  I also think what we do have in place is to rigid in the way it carries out its current matching and we really need to be pulling in or getting the social sphere of the customer somehow.

Just finished reading: Understanding Big Data: Analytics for Enterprise Class Hadoop and Streaming Data

I have just finished reading this book, I was excited about the IBM offering and the concepts around big data at IDUG, but after reading the book I want to find a project I can try this out on. The book can be downloaded from here: Understanding Big Data: Analytics for Enterprise Class Hadoop and Streaming Data.

The book is in two parts, Part 1: Big Data from the business prospective and Part 2: Big Data from the technology prospective. The first part of the book as it suggests does not touch on the technical aspects of big data only the benefits to businesses and how we all are already part of the Big Data world. The second part of the book explains at a high level all the different parts of the Hadoop cluster and how you get data in and out and process data in there. The second part also explains the IBM offering into this marketplace in the form of IBM InfoSphere BigInsights and Streams.

The as a high level description first part introduces the concept of the three V’s of big data, Volume, Velocity and Variety, the uses of these V’s in a number of different scenarios all of which are very interesting and I can easily see how it would bring you competitive advantage (probably the point of the case studies). The second part is for the techies explaining what Hadoop is and all of the different parts that make it up with MapReduce, common components and the file system. Also explaining all the other technologies surrounding Big Data such as Hive, Flume and Jaql.

So this is just a very light overview of the book, and well worth a read. I did it on my kindle, sometimes the text varies from page to page as it gets resized but overall it was fine.