Manage Learn to apply best practices and optimize your operations.

Data provenance and the profitability of well-governed information

According to frequent SearchCompliance contributor Jeffrey Ritter, companies can use information governance processes to tap into readily available business intelligence. But first, they must understand data provenance -- that is, where it came from, who created it, who altered it during its lifecycle.

In part two of a recent webcast, Ritter explored the importance of understanding company data provenance, and outlined a six-step mission to create wealth from well-governed information.

Ritter's mission has six points:

1. Data mining requires data conforming to the rules

Ritter says that the quality of information must first be validated.

Data needs to be compared with the available rule inventory in order to judge whether or not it may move through the filter and, "into the analytics engines that are being operated," Ritter says.

2. Where are the sources of new intelligence?

Those sources, according to Ritter, include warehouse data, graph data, text data and multimedia data. Event record logs are also an important part of information governance.  

With data, we care very much [about provenance] because the information is more valuable when we understand its provenance.
Jeffrey Ritter

Every machine and application creates records of how they perform their function--record logs. Ritter says that these records are vital in that they allow information governance experts to see what has taken place with the data itself. Records can hold important information such as who used what device to type specific keystrokes, and what, "authentication sequences" were carried out on the information.

3. Gain a seat at the table on defining the rules for event logs

According to Ritter, the governance process should move to the, "front end." He says it is important for information governance experts to be involved in making the rules for governing information and handling data provenance.

Systems today are too often designed and engineered without the realization of how to utilize their output --their performance data and event logs, to create a new stream of income, Ritter says.

4. The provenance of data proves alignment with the rules

Data provenance, according to Ritter, is, "The records of the entities, people and processes involved in producing a piece of data."

Ritter says that data provenance can prove important to businesses because it allows information to be more easily identified as being what it purports to be.

Gold miners of the California gold rush didn't care about their gold's provenance -- they only cared that it was real gold. "With data, we care very much because the information is more valuable when we understand its provenance," Ritter says.

5. Provenance chains together to improve the value of data for analytics

Data provenance improves the value of intelligence by eliminating excess validation, Ritter says.

"We basically have to prove that an apple is the apple, and that there are no worms. The validation exercise requires the "data about the data." It chains together, and so the net result is that the outbound data coming through systems that have been properly enhanced with information governance is more valuable because it's more easily validated to be what it purports to be," Ritter says.

6. Effective information governance requires engineering the information lifecycle

According to Ritter, this last point is beneficial to the improvement of the business' efficiency.

Ritter says that, when the demand to let information governance be part of the engineering lifecycle is met, opportunities rise for discussing each data asset's revenue opportunity.

Watch part three of this webcast to learn more about how information governance can boost the company bottom line. Then visit SearchCompliance to view part four, where Ritter continues his discussion about the business benefits of big data mining.

View All Videos