Showing posts with label data management. Show all posts
Showing posts with label data management. Show all posts

Have 'Big Data' Sand Boxes Become Sand Traps?

Virginia Rometty, CEO of IBM aptly stated that “data is the new natural resource.”

With 2,500,000,000,000,000,000 bytes of data we create every day, has Big Data become a become mess? Have sand boxes turned into sand traps?

Big Data is still a vague concept for businesses, a concept they sort of understand. Most companies have either no idea or a partial understanding of what big data is and what it does, let alone managing and capitalizing on it.

Many organizations have initiated pilot projects to manage and utilize Big Data. However, in almost all cases, it hasn’t gone any further. While they begin with great energy, procure tools and create sand boxes to learn and understand how to make the most of unstructured data, they eventually lose their way, diminishing the value of the project. What’s missing is end-to-end data management to protect assets and enable compliance. Many companies fail to use the right processes and tools to manage huge volumes of data collected from various sources.

The solution as per the experts is to manage the beast of Big Data by harnessing its power, with a shift in culture, attitude and discipline. What is required is a combination of traditional and new and advanced data management capabilities.

While Big Data is a big market,
Let it not become a Big Mess,
Manage it before it manages your business!

25% of Your Data Goes Stale Every Year! Get to Know if it Stinks?

As MarketingSherpa states, 2.1% of contact details change every month. 

Regular data verification and quality control is essential in measuring relevancy, analyzing effectiveness, optimizing strategies and maximizing revenues and ROI.

http://bit.ly/Uv1htX
Characteristics of Quality Data 
Accuracy – Contact details such addresses and phone numbers actually exist and are associated with the person or business in the record.
Freshness – Information reflects current details of the person or business.
Completeness – All records are complete making it valid for relevant usage.
Uniqueness – There is only one record per person or business and duplicate records are merged or deleted.
Standardized – Information recorded follows a set format and standard.

Want to know why your emails are undelivered? 
Would you like to maximize ROI on data purchased? 
Would you like to spend marketing dollars on customers that count?

Get to know if your data stinks with this Data Quality Checklist!