Businesses today understand that data is an important enterprise asset, relied on by employees to deliver on their customers' needs, among other uses of data such as making business decisions and many others. Yet too few organizations realize that addressing data quality is necessary to improve customer satisfaction. A recent Forrester survey shows that fewer than 20% of companies see data management as a factor in improving customer relationships. This is very troubling number.

Not paying attention to data quality can have a big impact both on companies and the customers they serve. Following are just two examples.

True to its iconic logo, Hadoop is still very much the elephant in the room. Many organizations heard of it, yet relatively few can say they have a firm grasp on what the technology can do for their business, and even fewer have actually implemented it successfully at their organization.

Forrester Research predicted that Hadoop will become a cornerstone of the business technology agenda at most organizations.

As customer expectations rise, delivering personalized experiences that improve customer loyalty, increase customer acquisition and optimize efficiency is increasingly more challenging to achieve. It is very important to engage customers in their preferred channel and to minimize the overall effort of that engagement.

A key to minimizing the customer effort is to deploy a knowledge management platform that crosses all channels, presents accurate content from multiple sources, maintains, relevance, and captures feedback for continuous improvement. Oracle Knowledge is a complete knowledge management solution which provides personalized cross-channel service and support.

Today's post focuses on how knowledge management adds an essential layer of value to customer facing systems, which ultimately drives improved customer experiences.

Two sweeping trends have emerged in recent years: the proliferation of customer channels and the resulting explosion in the amount of data produced.

Customer relationship management has done a great job of providing a strong framework for these multi-channel interactions. Knowledge management (KM) has done an equally remarkable job by providing the brains behind the increasingly diverse network of customer contact points.

Our view of data often doesn't extend further than numbers. When you think about it, data means a percentage, a total, or something to which those numbers are attached. Furthermore, we want to act on those numbers with familiar math.

We don't act on data, we act on information, and we only act on information when it creates knowledge in our minds that enables us to make informed decisions. We might call this customer insight, but in the reality it is - data, information, and knowledge.