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Metadata can fix your dark data problems: Gerard Francis, Bloomberg

Soumik Ghosh | June 6, 2017
Gerard Francis, the man at the helm of Bloomberg’s global enterprise solutions, sheds light upon why metadata is the new Holy Grail in the enterprise today.

Metadata can fix your dark data problems: Gerard Francis, Bloomberg

At a time when the enterprise is grappling with immense volumes of dark data, the key to finding the right insights lies in tapping into the metadata.

A dialogue with Gerard Francis, global head, Bloomberg Enterprise Solutions, throws light on how metadata is the answer to battling cost challenges posed by dark data.

 

How do CIOs zero in on the right vendor to handle their data?
We've always had really great underlying high-quality data on the terminal, simply because we're so widely used by traders and portfolio managers around the world. And they make big investment decisions based on our real-time news and data.

We broaden that in the context of enterprise data because we don't just focus on the underlying data, we focus on giving people very accurate metadata. The metadata is extremely important, as that's ultimately what programmers use. That's how data is ingested into the organization.

In terms of CIOs and CTOs, what we see happening across the world is in the past, as data quality from different vendors wasn't that high, people opted for a strategy where they had many vendors. We lay a very high focus on making sure that the data quality matches the metadata, and that ensures that there are very few mismatches for our clients. We actually track beyond the 99.9 percent accuracy on our metadata.

Now, as data quality has gotten better, CIOs feel that they do not need as many vendors anymore. With fewer vendors, they have to do lesser reconciliation across datasets, and you end up with fewer mismatches.

So, the vendor you ought to pick is the one that's really accurate with your data.

 

What's your takeaway for CIOs to ensure data quality is maintained at the highest levels?
It all comes down to the way you use your metadata, and how you program against the metadata. Metadata hasn't always got as much focus when people talk about data.

Now when you see data managers across the world, they're focusing very intently on the quality, accuracy, and describability of the metadata.

 

What are the current challenges with respect to Governance, Risk, and Compliance (GRC)?
I think currently there's a much larger emphasis on governance. For the first time we see Chief Data Officers being appointed across many organizations, and their primary role is describing data policies and governance around the data policies.

And the chief purpose of that is both for their own internal purposes - making sure that when data is used in applications, there's a reason why that data is there. This is also very important for regulators, as they don't feel comfortable where an organization doesn't have the right data governance policies. Regulators are less likely to trust such organizations with their analyses.

 

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