You might have lots of data on lots of customers, but imagine if you could suddenly add in a huge dollop of new, highly informative data that you weren’t able to access before. You could then use analytics to extract some really important insights about these customers, allowing you to improve the goods and services they receive from you leading to stronger customer loyalty and higher business revenues.
But how might this happen? It’s probably easiest to explain what’s now possible which wasn’t possible (or practical) before by giving you a simple example.
Consider an insurance company that provides household insurance to particular customers, and an estate agent that was used to selling that property to the current owner. Now, think about the data an insurance company will typically hold in relation to this property. It will be basic information about the property, its location, number of bedrooms and the usual data about the homeowner(s) and their claims history.
Now consider all the rich, textual information – the unstructured data - held by the estate agent. This data is openly available but to date unused. It will contain lots of additional information describing particular aspects of the property, such as the layout, access areas, recent extensions or renovation work – and all of this information can create an altogether different picture for the insurer when it comes to rating the property for house insurance premiums.
It is now possible to ingest all that additional estate agent data into a big data Hadoop environment, taking advantage of the cheaper storage and faster processing speeds that Hadoop offers. SAS Data Loader for Hadoop is designed to make it easy to get data into and out of this environment and to transform and check the quality of data in Hadoop. It essentially removes the complexity of getting the right data into the right format to get going with visualisation or analytics on your data.
So, it’s one way around the skills problem that exists in many organisations when it comes to data management. You can even run an easy-to-use solution like SAS Visual Analytics on all the data which has already been quickly and easily loaded into Hadoop.
The SAS Data Loader for Hadoop leverages technologies such as Oozie, Sqoop and HiveQL through a point and click interface that drives the environment. It also adds some SAS smarts that let you do data profiling and other key tasks that none of those technologies provide.
SAS Data Loader for Hadoop is still available to download for free as part of a 90-day trial. So why not see what it can do for your business?
You can also find out more from our report Bringing the Power of SAS to Hadoop, or read more on the Data Roundtable Blog:
