Taming The Big Data Tidal Wave: Finding Opportunities in Huge Data Streams with Advanced Analytics (Wiley and SAS Business Series)

Getting a read on the trends of what people are saying across social media outlets or within customer service interactions can be immensely valuable in planning what to do next.

When asked about the value of incorporating web data, a director of marketing from a multichannel American specialty retailer replied, “It’s like printing money!”

There are e-mails, text messages, tweets, social media postings, instant messages, real-time chats, and audio recordings that have been translated

made? A great analysis will include recommended steps. If option #2 outperformed option #1 by 10 percent, then include the statement that option #2 should be implemented. In a simple case like this, that is pretty obvious. Many analyses will be more complex, however. In those cases, guidance on what action the results imply will be immensely helpfu

Common touch points today include web sites, kiosks, mobile apps, and social media.

To read semi-structured data, it is necessary to employ complex rules that dynamically determine how to proceed after reading each piece of information.

popular use of text analysis today is what’s known as sentiment analysis. Sentiment analysis looks at the general direction of opinion across a large number of people to provide information on what the market is saying, thinking, and feeling

Today, organizations need to be collecting newly evolving big data sources related to their customers from a variety of extended and newly emerging touch points such as web browsers, mobile applications, kiosks, social media sites, and more.

The reason is that the process of executing social network analysis requires taking already-large data sets and using them in a way that effectively increases their size by orders of magnitude.