data management

How Bad Data Management Kills Revenue

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I’m not one to normally publicly gripe on a vendor, but a recent customer experience with an online purchase is a great example of why organizations can’t ignore data management investments.

I have been a regular user of a note-taking app for several years. All my discussions with clients, vendors, and even notes from conferences wind up here. I put in pictures, screen shots, upload presentations, and capture web pages. So it isn’t a surprise that this note-taking vendor wants to move me up into a premium version. And for $50 a year, it’s not a big deal for me to do even if it just means I’m paying for more space rather than using all the features in the premium package.

So, this morning, I click the upgrade button and voila! My order is taken and shows up in my iTunes account order history.

As this app is web-, desktop-, and device-based and the vendor is born out of the app age, the expectation is that my account status should just automatically convert. I mean, every other business app I have does this. Why shouldn’t this one?

As it turns out, my purchased premium service is nowhere to be found. To get immediate support, as only offered in premium service, you need to be able to log in as a premium customer. So instead of an easy and quick fix, I spend over an hour trying to get answers through a support site that shows the issue but an answer that doesn’t work. I also see that this is an issue going back for over a year. I try entering in my issue through “contact us” only to find that I get routed back to the support forum and can’t even log a ticket. I find an obscure post where the vendor’s Twitter handle for support is listed and fire off a frustrated tweet (which goes out to my followers as well, which I’m assuming is not something this vendor would prefer).

So let’s break down the data management issue:

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Agile Development And Data Management Do Coexist

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A frequent question I get from data management and governance teams is how to stay ahead of or on top of the Agile development process that app dev pros swear by. New capabilities are spinning out faster and faster, with little adherence to ensuring compliance with data standards and policies.

Well, if you can’t beat them, join them . . . and that’s what your data management pros are doing, jumping into Agile development for data.

Forrester’s survey of 118 organizations shows that just a little over half of organizations have implemented Agile development in some manner, shape, or form to deliver on data capabilities. While they lag about one to two years behind app dev’s adoption, the results are already beginning to show in terms of getting a better handle on their design and architectural decisions, improved data management collaboration, and better alignment of developer skills to tasks at hand.

But we have a long way to go. The first reason to adopt Agile development is to speed up the release of data capabilities. And the problem is, Agile development is adopted to speed up the release of data capabilities. In the interest of speed, the key value of Agile development is quality. So, while data management is getting it done, they may be sacrificing the value new capabilities are bringing to the business.

Let’s take an example. Where Agile makes sense to start is where teams can quickly spin up data models and integration points in support of analytics. Unfortunately, this capability delivery may be restricted to a small group of analysts that need access to data. Score “1” for moving a request off the list, score “0” for scaling insights widely to where action will be taking quickly.

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Agile Development And Data Management Do Coexist

by

A frequent question I get from data management and governance teams is how to stay ahead of or on top of the Agile development process that app dev pros swear by. New capabilities are spinning out faster and faster, with little adherence to ensuring compliance with data standards and policies.

Well, if you can’t beat them, join them . . . and that’s what your data management pros are doing, jumping into Agile development for data.

Forrester’s survey of 118 organizations shows that just a little over half of organizations have implemented Agile development in some manner, shape, or form to deliver on data capabilities. While they lag about one to two years behind app dev’s adoption, the results are already beginning to show in terms of getting a better handle on their design and architectural decisions, improved data management collaboration, and better alignment of developer skills to tasks at hand.

But we have a long way to go. The first reason to adopt Agile development is to speed up the release of data capabilities. And the problem is, Agile development is adopted to speed up the release of data capabilities. In the interest of speed, the key value of Agile development is quality. So, while data management is getting it done, they may be sacrificing the value new capabilities are bringing to the business.

Let’s take an example. Where Agile makes sense to start is where teams can quickly spin up data models and integration points in support of analytics. Unfortunately, this capability delivery may be restricted to a small group of analysts that need access to data. Score “1” for moving a request off the list, score “0” for scaling insights widely to where action will be taking quickly.

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Data Governance and Data Management Are Not Interchangeable

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Since when did data management and data governance become interchangeable?
This is a question that has both confounded and frustrated me. The pursuit of data management vendors to connect with business stakeholders, because of the increasing role busi…

Let’s Break All The Data Rules!

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When I think about data, I can’t help but think about hockey. As a passionate hockey mom, it’s hard to separate my conversations about data all week with clients from the practices and games I sit through, screaming encouragement to my son and his team (sometimes to the embarrassment of my husband!). So when I recently saw a documentary on the building of the Russian hockey team that our miracle US hockey team beat at the 1980 Olympics, the story of Anatoli Tarsov stuck with me.

Before the 1960s, Russia didn’t have a hockey team. Then the Communist party determined that it was critical that Russia build one — and compete on the world stage. They selected Anatoli Tarsov to build the team and coach. He couldn’t see films on hockey. He couldn’t watch teams play. There was no reference on how to play the game. And yet, he built a world-class hockey club that not only beat the great Nordic teams but went on to crush the Canadian teams that were the standard for hockey excellence.

This is a lesson for us all when it comes to data. Do we stick with our standards and recipes from Inmon and Kimball? Do we follow check-box assessments from CMMI, DM-BOK, or TOGAF’s information architecture framework? Do we rely on governance compliance to police our data?

Or do we break the rules and create our own that are based on outcomes and results? This might be the scarier path. This might be the riskier path. But do you want data to be where your business needs it, or do you want to predefine, constrain, and bias the insight?

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Is Zombie Data Taking Over?

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It is easy to get ahead of ourselves with all the innovation happening with data and analytics. I wouldn’t call it hype, as that would imply no value or competency has been achieved. But I would say that what is bright, shiny, and new is always more interesting than the ordinary.

And, to be frank, there is still a lot of ordinary in our data management world.

In fact, over the past couple of weeks, discussions with companies have uncommonly focused on the ordinary. This in some ways appeared to be unusual because questions focused on the basic foundational aspects of data management and governance — and for companies that I have seen talk publicly about their data management successes.

“Where do I clean the data?”

“How do I get the business to invest in data?”

“How do I get a single customer view of my customer for marketing?”

What this tells me is that companies are under siege by zombie data.

Data is living in our business under outdated data policies and rules. Data processes and systems are persisting single-purpose data. As data pros turn over application rocks and navigate through the database bogs to centralize data for analytics and virtualize views for new data capabilities, zombie data is lurching out to consume more of the environment, blocking other potential insight to keep the status quo.

The questions you and your data professional cohorts are asking, as illustrated above, are anything but basic. The fact that these foundational building blocks have to be assessed once again demonstrates that organizations are on a path to crush the zombie data siege, democratize data and insight, and advance the business.

Keep asking basic questions — if you aren’t, zombie data will eventually take over, and you and your organization will become part of the walking dead.

To defend your business from zombie data, read:

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The Open Group San Diego Panel Explores Synergy Among Major Frameworks in Enterprise Architecture

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Following is a transcript of part of the proceedings from The Open Group San Diego event in February – a panel discussion on The Synergy of Enterprise Architecture frameworks. The following panel, which examines the synergy among the major Enterprise … Continue reading →

To Liberate Healthcare Data, Dip into Data Lakes

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Guest post by Randy Delgado The other day I was talking to a healthcare CIO about the trend of data liberation or what I like to call Open Data. Open Data is combining the abundance of external data with data from your own corporate systems to glean insights that will enable your company to grow, enhance operations and deflect disruption. I didn’t need to remind the healthcare executive how behind the trend she was. She […]

The Open Group London 2014 – Day One Highlights

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By Loren K. Baynes, Director, Global Marketing Communications, The Open Group On a crisp October Monday in London yesterday, The Open Group hosted the first day of its event at Central Methodist Hall, Westminster. Almost 200 attendees from 32 countries … Continue reading →

Open FAIR Blog Series – Five Reasons You Should Use the Open FAIR Body of Knowledge

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By Jim Hietala, VP, Security and Andrew Josey, Director of Standards, The Open Group This is the second in our blog series introducing the Open FAIR Body of Knowledge. In this blog, we provide 5 reasons why you should use … Continue reading →

Open FAIR Blog Series – An Introduction to Risk Analysis and the Open FAIR Body of Knowledge

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By Jim Hietala, VP, Security and Andrew Josey, Director of Standards, The Open Group This is the first in a four-part series of blogs introducing the Open FAIR Body of Knowledge. In this first blog. we look at what the … Continue reading →

The Open Group Panel: Internet of Things – Opportunities and Obstacles

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Below is the transcript of The Open Group podcast exploring the challenges and ramifications of the Internet of Things, as machines and sensors collect vast amounts of data. Listen to the podcast. Dana Gardner: Hello, and welcome to a special … Continue reading →