Category Archives: Metadata
Why Now is the Time for an Investment in Data Management
All application managers have gotten this question at some point or another. But it could be worse. Consider if the question never was asked and that bad data caused an error in a crucial business process or transaction. The damage can be significant and it happens every day.
Let’s suppose you do bad data in an enterprise application. This raises a number of very difficult questions:
- Provenance. Where did this data come from? Is the data from the right source?
- Transformation. Was the data transformed correctly as it was moved from source to target?
- Operational. Was there an operational error along the way that caused a critical process to run only partially or not at all?
- Change Management. Did somebody make a change to the data integration / data management system that looked like a logical solution to their problem, but that cause your application to receive bad data?
Good data is the crude oil (we’re all going to hear that analogy a lot more!) that business processes run on. If you have bad (or dirty) oil, you are going to have problems with the process.
Why do application managers care? After all this is data integration, not application management. The answer is pretty straightforward:
- So you don’t get questions like the one above, questions that suck up the time of your staff. (15 hours per analyst per month from one customer source)
- So bad data does not lead to bad transactions and bad decisions.
- So that bad or inconsistent data does not damage the confidence of the users of your application, causing workarounds and lack of adoption.
So, what should be done to fix this? It is time to start thinking about data integration and data quality management as a single system rather than a somewhat random collection of expensive one-off projects. The result will be lower costs, higher productivity, and greater user confidence in your enterprise applications.
For more on this and related topics, visit our Potential at Work site for Application Leaders.
I’m glad you enjoyed my last letter explaining what data is and how people in my industry make a living managing it. After that letter, you confidently answered all data-related questions your knitting-circle friends could throw at you. But then Edward Snowden, former NSA contractor and world-renowned whistle-blower, came on the scene. Suddenly mainstream news anchors are talking about metadata.
I got your panicked voicemail and, as promised, I’m going to try to clarify what metadata is and how it relates to data. (more…)
When executing application modernization or application rationalization your focus is on supporting the business strategy by implementing systems that run critical business processes. And that is exactly where the focus should be.
The problem comes when there is a lack of focus on delivering trustworthy data for those business systems and processes. If you are consolidating enterprise applications or upgrading to new enterprise applications, the data needs to be migrated from System A to System B. This is virtually never a simple “cut & paste.” In fact, data migration projects can be fairly risky. Bloor Research has found in their latest study that 38% of these projects fail. Even worse, the Harvard Business Review reports that 17% of enterprise application projects go over budget by 200% and over schedule by 70%. There are many examples of this. The State of California has terminated their contract with their ERP vendor after spending $254 million. The U.S. Marine Corps has spent $1.1 billion on another ERP system, 10 times its original estimated cost.
So, how do you deliver the business value that your users demand? Here are four best practices to help you to deliver applications on-time and on-budget that meet the user’s needs for timely, authoritative data.
- Have an internal competence in data migration. This is a best practice identified by Bloor Research in their study on data migration. You can’t simply turn this project over to a third party. Only your staff truly knows your internal data. Another thing to consider is that your staff will also have to operate the new applications after go-live (see #4).
- Have a separate data migration team and budget. Bloor Research also recommends a separate budget and team. This is to ensure that there is a strong focus on data migration and quality and that it doesn’t become just a project detail in the larger application installation. Bloor found a very high likelihood of project failure if there is not a separate budget.
- Make sure that your business users are deeply involved. The Bloor survey found that by far the #1 success factor identified by their respondents was “Business engagement.” Unless the business side is deeply involved in requirements definition and providing business context there is a significant risk of misunderstandings that will result in a system that does not meet the needs of its users.
- Consider the new system go-live as the beginning, not the end. We have seen many organizations that view data migration as a “one-and-done” project where everybody packs up and goes home at the end of the project. An enterprise application is a living, breathing, system that needs continuing care and feeding. Once the application goes live, you will need to provide services such as: ongoing data quality management, synchronization with other operational systems, and synchronization with a master data management hub if you have one.
For more information:
Live Webinar with Philip Howard of Bloor Research. May 20, 2013. Successful Application Go-Lives: Best Practices for Application Data Migration
Application Data Migration Presentations at Informatica World 2013. We will have a Hands-On Lab and data migration presentations from Accenture and National Oilwell Varco.
Bloor White Paper: Best Practices for Data Migration
Informatica Solution Site: Data Migration Solution
Lean manufacturing, as defined by Wikipedia, is “a production practice that considers the expenditure of resources for any goal other than the creation of value for the end customer to be wasteful…Essentially, lean is centered on preserving value with less work” and is a management philosophy derived mostly from the Toyota Production System (TPS). I’ve been having discussions with Jim Harris from OCDQ Blog and Reuben Vandeventer, Director of Data Governance for CNO Financial and others about best practices for data quality management and the applicability of lean management practices as it relates to data warehousing. Click here to hear Jim, Reuben and I discuss three critical areas of data quality to focus on for building data warehouses that people actually use and trust.
Big data and related technologies such as Hadoop present significant opportunities and challenges to businesses. Nearly everybody in IT reports that they are actively evaluating big data technologies. And, just as you would expect, they are in a variety of stages of implementation. So, who has time to think about data governance when dealing with a massive change like this?
First, you have to get your hands around the new technology, right? Actually, this is exactly the right time to think about data governance for big data; before the wild, untamed data from outside the company starts getting mixed with your potentially more trustworthy, tamed, internal data. (more…)
Does your organization have a structured repository of metadata that can help a data center operator (whether they are on-site or off-shore) quickly troubleshoot a production incident related to a data integration job at 2:00 am in the morning? Or any time of day for that matter? This is just one use of metadata. A new Metadata Management whitepaper has just been published which describes the wide range of metadata types, uses and the business value derived from them. (more…)
A number of customers have asked me recently about the benefits of using a business glossary product over using a spreadsheet or Sharepoint. The discussion is worth sharing.
If you have a smaller company and all you need is a list of standard business terms to provide a common business vocabulary across the company, a spreadsheet or Sharepoint can work, …up to a point. The problem is that once your organization reaches a certain size, you are going to have trouble scaling the management of the business terms, making them available across a larger organization, and fostering collaboration based on the agree-upon business terms. (more…)
Why is it that point-to-point integration has such a bad reputation and negative connotation? We’ve all seen the infamous hairball (or spaghetti) picture of information exchanges between systems that looks something like this:
But point-to-point is not the problem – variation is. When different teams develop point interfaces without standards or re-useable components and without shared governance and controls, the result is a tangled hairball every time. (more…)
One sign that the practice of metadata management is maturing is that we are seeing it cross over from IT to the business side of enterprises, and with it the rising need for business metadata. This is core to any successful Data Stewardship or Data Governance initiative. But first, what is Business Metadata? (more…)