In their ongoing coverage of the MIT Information Quality Conference, Dave Vellante and Paul Gillin speak with Willa Pickering, Senior Fellow and Information and Data Architect for Lockheed Martin. The three discuss important issues in data management, analysis, quality and risk.

Pickering explains that new focus for those interested in data is how to handle massive amounts of data (such as zettabytes and beyond) at rapid speed. One of Pickering’s earlier positions involved managing data storage on hard disks. She notes the storage capacity has since changed tremendously to handle all of Lockheed Martin’s data.

Pickering suggests managing unstructured data has become a business strong suit. Now, the aim is to delve more into semantics, context and meaning. She suggests, we’re used to real time data like the kind we receive instantly when we turn on our smartphones. So, velocity is also an essential part of data discussions.

Gillin inquires about how accurate data can be if someone wants it real time. Pickering emphasizes the importance of the veracity and quality of data in such situations. Given massive amounts of data, it is really important to “separate the signal from the noise,” Pickering responds. One must also be cautious of malicious data. Given that people are making business decisions based on data, she suggests the question leaders must ask is: “What kind of risk do you want to take in using real-time data?”

Watch the full interview with Pickering below:

As the Chief Data Officer (CDO) position continues to percolate, Vellante asks, “Can someone actually have a single role to coordinate a strategy around that approach? Or should it be a distributed role?” Pickering acknowledges that no one has agreed on what the role of the CDO should exactly entail, but it is evolving. In general, she believes the role of the CDO is to look at the relevance of data to the business and decide how to best acquire and apply it. Pickering describes data analysis as the most important part of CDO activities because “that is where the value is added and that’s where the decisions have to be made.”

Gillen references IBM’s Watson as an example of technology that aggregates a large amount of data and makes it intelligible. He asks Pickering if she sees similar technologies evolving to provide data analysis. Pickering is unsure as to where all the technologies are, but predicts we will see more of them in the near future. She suggests these technologies will be efficient at examining context to help with interpretation.

Vellante inquires about the implications of open source for data quality. Pickering notes that this is an important point because by virtue of the data being open, it is risky in terms of quality. On the other hand, it opens new possibilities for analysis. Censors on your car, it can also affect how you get your insurance.

The panelists also discuss the significance of data governance. Pickering notes that data management and governance have been the top points of discussion at a recent CDO forum.