InetSoft Webinar: Another Data Quality Tool

This is the continuation of the transcript of a Webinar titled "Why MDM?” hosted by InetSoft. The speaker is Christopher Wren, Principal Consultant at TFI Consulting.

The last thing that people want to do is buy another data quality tool. That’s been an inhibitor. People want to buy a new MDM solution that’s been built ground up to support MDM. I have got a lot of the existing components because I have built data warehouses. Can I reuse those or do I have to scrap those and invest in who new technology? Well that’s a tough call for lot of these folks.

But I will say there is one technology component we haven’t mentioned yet that everyone has overlooked, the early adopters anyway, and I think it's because the product didn’t exist a couple of years ago. That’s cross-source data profiling. There are now tools to cut through that, and that’s a huge pain point, took lot of money, a lot of time. We now have tools to automate that.

Data profiling is identifying the relationship between tables and systems. In some respects what you want is an MDM framework or architecture that allows you to bring in, if you have already got a data profiling tool, fine, bring it in and plug it in. If you don’t have one, then maybe you want to buy one or something like that.

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It allows you to use the existing technology which you already have, ETL tools, data profiling, data quality, on and on and on it goes. Can I plug them into these various places and use them within my master data management framework and not have to buy yet another set of technologies that duplicates whatever you have?

There is advantage to the platform data profiling vendors who are out there who have emerged. Then there are also companies who already have existing data profiling tools that they have used like a SAS data profile or Teradata. The key component is that you are not forcing them to do with one or the other.

You give them the flexibility. I have that data profiling tool, can I plug that in and do it in my development environment and leverage that data profiling tool, or can I leverage that within my runtime environment as well. So I am not just stuck in that single box where I have to go one or the other. Flexibility is key.

Flexibility, sounds good. Let’s talk about the short and long term outlook of master data management as a practice, as a technology discipline. Short term, I think that many organizations are starting master data management from their business intelligence environments because again, I think that’s where a lot of the expertise resides and also, a lot of the recognition that gee, as I just clean up my master data, life becomes a heck of a lot easier.

So I think in the short term, we are going to see a lot of MDM projects springing out of the business intelligence environment. Having said that, I think in the long term, master data management doesn’t belong to business intelligence. It also doesn’t belong to business operations. I see it as its own environment and ultimately, being able to interface or see business operations and business intelligence equally.

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So I think if we can get to that level of maturity, I hope we do, in the next three to five years, I think the technology will support that. It also means that we really do have to look long and hard at something called service oriented architecture because they will immediately become almost a mandatory part of this world where we are now calling master data management or bi analytics or operations and services to do workflows.

That’s an interesting question. I think master data management is a much more diverse area than data warehousing. So I think in some ways, it's hard to predict where that market will go. I am sure we will see on the vendor side, the usual validation, such as through the acquisitions that we have already seen.

I think in the short term we will see the growth of MDM really being driven by the BI sector and the data warehouse sector because they understand it. Now even though there are going to be the operational initiatives out there, I think that there is going to be a higher percentage that are driven by that BI initiative and the value of integrating data in your environment.

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And in the long term, if the BI environment can actually understand SOA, which I think that there is a learning curve there, and MDM does grow out of that BI environment, they have understanding of SOA, that it does become that master data enabler for the enterprise. It can save organizations from building new applications, having to have localized repositories, or code specifically.

It's going to be calling a specific service, and that’s going to be that master data service. It's just going to be a consumable service just like analytics where analytical processes are going to eventually just be a consumable service within the enterprise.