6 days ago

Data Engineers Will Be More Important Than Data Scientists

Does it seem like the ability to find, hire and retain data scientists is a losing battle? Is spending $500K+ per year for a Data Scientist worth it? What is a data scientist anyway? Those a real questions and are the markers that how you are supportin…

1 year, 8 months ago

The Forrester Wave Master Data Management: Which MDM Tool Is Right For You?

The Forrester Wave for Master Data Management went live today. The results may surprise you.

MDM tools today don’t look like your father’s MDM. No longer an integration hub between applications and DBMSs, today’s tools are transitioning or have reinvented MDM to handle the context missing from system traditional implementations. Visualizations, graph repositories, big data and cloud scale, along with application like interfaces for nontechnical users, mean MDM and master data gets personal with stakeholders.

Semantics and insight are not an outcome of MDM but an integrated part of the engine and hub. Three MDM evolutions stand out:

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1 year, 8 months ago

The Forrester Wave Master Data Management: Which MDM Tool Is Right For You?

The Forrester Wave for Master Data Management went live today. The results may surprise you.

MDM tools today don’t look like your father’s MDM. No longer an integration hub between applications and DBMSs, today’s tools are transitioning or have reinvented MDM to handle the context missing from system traditional implementations. Visualizations, graph repositories, big data and cloud scale, along with application like interfaces for nontechnical users, mean MDM and master data gets personal with stakeholders.

Semantics and insight are not an outcome of MDM but an integrated part of the engine and hub. Three MDM evolutions stand out:

Read more

1 year, 9 months ago

Do not confuse data governance with data management

Last week I participated in a roundtable during a conference in Paris organized by the French branch of DAMA – the data management international organization. During the question/answer part of the conference, it became clear most of the audience was …

1 year, 9 months ago

Do Not Confuse Data Governance With Data Management

Last week, I participated in a roundtable during a conference in Paris organized by the French branch of DAMA, the data management international organization. During the question/answer part of the conference, it became clear that most of the audience …

2 years, 20 days ago

Semantic Technology Is Not Only For Data Geeks

You can’t bring up semantics without someone inserting an apology for the geekiness of the discussion. If you’re a data person like me, geek away! But for everyone else, it’s a topic best left alone. Well, like every geek, the semantic geeks now have their day — and may just rule the data world.

It begins with a seemingly innocent set of questions:

“Is there a better way to master my data?”

“Is there a better way to understand the data I have?”

“Is there a better way to bring data and content together?”

“Is there a better way to personalize data and insight to be relevant?”

Semantics discussions today are born out of the data chaos that our traditional data management and governance capabilities are struggling under. They’re born out of the fact that even with the best big data technology and analytics being adopted, business stakeholder satisfaction with analytics has decreased by 21% from 2014 to 2015, according to Forrester’s Global Business Technographics® Data And Analytics Survey, 2015. Innovative data architects and vendors realize that semantics is the key to bringing context and meaning to our information so we can extract those much-needed business insights, at scale, and more importantly, personalized.

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2 years, 20 days ago

Semantic Technology Is Not Only For Data Geeks

You can’t bring up semantics without someone inserting an apology for the geekiness of the discussion. If you’re a data person like me, geek away! But for everyone else, it’s a topic best left alone. Well, like every geek, the semantic geeks now have their day — and may just rule the data world.

It begins with a seemingly innocent set of questions:

“Is there a better way to master my data?”

“Is there a better way to understand the data I have?”

“Is there a better way to bring data and content together?”

“Is there a better way to personalize data and insight to be relevant?”

Semantics discussions today are born out of the data chaos that our traditional data management and governance capabilities are struggling under. They’re born out of the fact that even with the best big data technology and analytics being adopted, business stakeholder satisfaction with analytics has decreased by 21% from 2014 to 2015, according to Forrester’s Global Business Technographics® Data And Analytics Survey, 2015. Innovative data architects and vendors realize that semantics is the key to bringing context and meaning to our information so we can extract those much-needed business insights, at scale, and more importantly, personalized.

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2 years, 1 month ago

Are Data Preparation Tools Changing Data Governance?

First there was Hadoop. Then there were data scientists. Then came Agile BI on big data. Drum roll, please . . . bum, bum, bum, bum . . .

Now we have data preparation!

If you are as passionate about data quality and governance and I am, then the 5+-year wait for a scalable capability to take on data trust is amazingly validating. The era for “good enough” when it comes to big data is giving way to an understanding that the way analysts have gotten away with “good enough” was through a significant amount of manual data wrangling. As an analyst, it must have felt like your parents saying you can’t see your friends and play outside until you cleaned your room (and if it’s anything like my kids’ rooms, that’s a tall order).

There is no denying that analysts are the first to benefit from data preparation tools such as Altyrex, Paxata, and Trifacta. It’s a matter of time to value for insight. What is still unrecognized in the broader data management and governance strategy is that these early forays are laying the foundation for data citizenry and the cultural shift toward a truly data-driven organization.

Today’s data reality is that consumers of data are like any other consumers; they want to shop for what they need. This data consumer journey begins by looking in their own spreadsheets, databases, and warehouses. When they can’t find what they want there, data consumers turn to external sources such as partners, third parties, and the Web. Their tool to define the value of data, and ultimately if they will procure it and possibly pay for it, is what data preparation tools help with. The other outcome of this data-shopping experience is that they are taking on the risk and accountability for the value of the data as it is introduced into analysis, decision-making, and automation.

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2 years, 2 months ago

Data Governance and Data Management Are Not Interchangeable

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…

2 years, 3 months ago

Let’s Break All The Data Rules!

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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2 years, 4 months ago

Is Zombie Data Taking Over?

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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4 years, 10 months ago

Questions for the Upcoming Big Data Security Tweet Jam on Jan. 22

Last week, we announced our upcoming tweet jam on Tuesday, January 22 at 9:00 a.m. PT/12:00 p.m. ET/5:00 p.m. BST, which will examine the impact of Big Data on security and how it will change the security landscape. The discussion will be guided by these six questions… Continue reading