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1 min read

Understanding today’s data management challenges

Understanding today’s data management challenges

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Advisor360°’s SVP, Chief Technology Officer, Jed Maczuba, discusses the many complexities of data management, including the exponential growth of information and the lack of a standardized approach to creating timely, consistent, and complete data.

Video transcript

Chip Kispert: When you're looking at reasons for a lot of these challenges that these firms are going through, what are some of the things that come to your mind from your experience bank?

Jed Maczuba: Well, it comes down to why is the problem how it is? And so you look at not only the evolution of organizations and how they managed to deal with data over the years, but even in today's world, data is a really complex thing.

So there are thousands of data providers that are out there that have really good data that companies want to ingest in order to make decisions. There's a lot of variety of data, we obviously know that's growing. So if you look at the growth rate of data, it continues to grow, I'd say almost exponentially out there. So there's a lot of variety out there.

What firms are trying to do is then, how do we take this diverse population of data, bring it into the organization, and then standardize it so they can actually consume this easily. And that's where the challenges come in because if you look at the data that's out there, not only is there intense volume or immense volume of data, but there's no standards around that, right?

And when we talk about data management, which is a general term, you think about things like data quality, which again, there's a lot of dimensions around data quality to understand things like the timeliness of data, the consistency, the completeness. I think people that don't get into the details around this, you'd like to think that the data providers, "I'll provide high-quality scrub data" but that's certainly not the case.

So it puts it on the burden of the consuming firms in order to be able to say, "How am I taking this mess of data and bringing it and standardizing and making it consistent so that they can actually make decisions?"