Every business under the sun has a burning desire to accomplish more with data. Customer analytics is a rapidly growing field, as companies are realizing that the more information they have about their patrons, the more they can analyze it and find actionable truths about sales and marketing buried within.
Of course, getting the most out of this potential requires top-notch practices for database management. Any company that has data is also going to need data governance. Who's in charge of your business' analytics blueprint? Who is coordinating how data is collected and stored? Who's looking out for important considerations like data quality?
All of these questions matter. Without good answers at the ready, you're likely to find your analytics program in shambles before long. According to TDWI Onsite Education, governance is a key ingredient of success. Data expert Philip Russom warns that it's an essential step toward fostering a collaborative business environment:
"The barriers to data governance are erased when an organization adopts the techniques and best practices of data quality and the closely related practice of data stewardship," Russom stated. "That's because the business-to-IT collaboration established by quality and stewardship practices is also required of data governance. In fact, quality and governance practices are similar, except that the needs of governance are broader, encompassing both enterprise data standards and business issues relative to data, such as compliance, risk, and privacy."
There are numerous things your business can do in order to better take care of its data. The following are four prime examples.
Oversee data in real time
The moment a piece of customer data is collected, you want to be able to look it over and assess its accuracy, relevance and how it can help your business.
Remediate for quality and compliance
When you do find errors in data quality, you want to have procedures in place for fixing such problems in a quick and painless fashion. This is where data governance comes in.
Use metrics for data quality
What you want is to show slow and steady gains in data quality over time. To demonstrate this improvement, you need clear metrics that will gauge and show it. Who will be in charge of this effort?
Align data with long-term goals
What are the long-term goals of your business? Do you want more exposure? More profits? Whatever your intent, do what you can to make sure data plays a part in it.