Thursday, January 5, 2012


There has been a lot of talk about “big data” in the past year, which I find a bit puzzling. I’ve been in the data warehousing field for more than 15 years, and data warehousing has always been about big data. So what’s new in 2011? Why are we are talking about “big data” today? There are several reasons:

Changing data types. Organizations are capturing different types of data today. Until about five years ago, most data was transactional in nature, consisting of numeric data that fit easily into rows and columns of relational databases. Today, the growth in data is fueled by largely unstructured data from wWeb sites as well as machine-generated data from an exploding number of sensors.
Technology advances. Hardware has finally caught up with software. The exponential gains in price/-performance exhibited by computer processors, memory, and disk storage have finally made it possible to store and analyze large volumes of data at an affordable price. Organizations are storing and analyzing more data because they can.!
Insourcing and outsourcing. Because of the complexity and cost of storing and analyzing Web traffic data, most organizations have outsourced these functions to third- party service bureaus. But as the size and importance of corporate e-commerce channels have increased, many are now eager to insource this data to gain greater insights about customers. At the same time, virtualization technology is making it attractive for organizations to move large-scale data processing to private hosted networks or public clouds.
Developers discover data. The biggest reason for the popularity of the term “big data” is that Web and application developers have discovered the value of building a new data-intensive applications. To application developers, “big data” is new and exciting. Of course, for those of us who have made their careers in the data world, the new era of “big data” is simply another step in the evolution of data management systems that support reporting and analysis applications.

Analytics against Big Data
Big data by itself, regardless of the type, is worthless unless business users do something with it that delivers value to their organizations. That’s where analytics comes in. Although organizations have always run reports against data warehouses, most haven’t opened these repositories to ad hoc exploration. This is partly because analysis tools are too complex for the average user but also because the repositories often don’t contain all the data needed by the power user. But this is changing.
• Patterns. A valuable characteristic of ““big data”” is that it contains more patterns and interesting anomalies than “small” data. Thus, organizations can gain greater value by mining large data volumes than small ones. Fortunately, techniques already exist to mine big data thanks to companies, such as SAS Institute and SPSS (now part of IBM), that ship analytical workbenches.
• Real-time. Organizations that accumulate big data recognize quickly that they need to change the way they capture, transform, and move data from a nightly batch process to a continuous process using micro batch loads or event-driven updates. This technical constraint pays big business dividends because it makes it possible to deliver critical information to users in near- real- time.
• Complex analytics. In addition, during the past 15 years, the “analytical IQ” of many organizations has evolved from reporting and dashboarding to lightweight analysis. Many are now on the verge of upping their analytical IQ by implementing predictive analytics against both structured and unstructured data. This type of analytics can be used to do everything from delivered highly tailored cross-sell recommendations to predicting failure rates of aircraft engines.
• Sustainable advantage . At the same time, executives have recognized the power of analytics to deliver a competitive advantage, thanks to the pioneering work of thought leaders, such as Tom Davenport, who co-wrote the book, “Competing on Analytics.” In fact, forward-thinking executives recognize that analytics may be the only true source of sustainable advantage since it empowers employees at all levels of an organization with information to help them make smarter decisions.
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