Big Data

Data complexity in companies can be a big obstacle to achieve efficient operations and excellent customer service.

Companies are broken down into various departments. They have hundreds, thousands, or even hundreds of thousands of employees performing various tasks. Adding to the complexity, customer information is stored in so many different applications that wide gaps exist among data sources. Bridging those gaps so every employee in the organization has a consistent view of data is possible and necessary.

Big Data is everywhere. But to harness its potential, organizations should understand the challenges that come with collecting and analyzing Big Data. The three values that are important in managing big data are volume, velocity, and variety. These three factors serve as guidance for Big Data management, highlighting what businesses should look for in solutions.

But even as organizations have started to get a handle on these three V’s, two other V’s, veracity and value are important as well, if not more so.

Big Data is an ever-evolving term which is used to describe the vast amount of unstructured data. Published reports have indicated that 90% of the world’s data was created during the past two years alone.

Whether it’s coming from social media sites such as Twitter, Instagram, or Facebook, or from countless other Web sites, mobile devices, laptops, or desktops, data is being generated at an astonishing rate. Making use of Big Data has gone from a desire to a necessity. The business demands require its use.

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.