Author: Danny Sandwell

Over the past 9 months, the erwin Modeling team has been busy shouting from the mountaintops about our entry in the Data Governance space.  In April of 2015, we released a new edition of our modeling portal, erwin® Web Portal Data Governance Edition, and we have focused on explaining the key capabilities and value that this solution delivers in support of an organization’s data governance efforts.  Built on a foundation of erwin DM models, we naturally refer to our approach as model-driven data governance.  This is an apt description in that we support data governance controls and processes through and by leveraging data models.  However, I think in our natural inclination to focus on what’s “new,” we are relegating a key element of our data governance solution to the shadows.

The act of data modeling, when done correctly, is by definition a data governance activity and a key enabler for success for any data governance initiative.  A high-value output of any well-executed data modeling process is a set of standardized, business-aligned, and multi-contextual data definitions: “standardized” in that they conform to a reusable set of data definition requirements; “business-aligned” in that they capture business rules and regulatory requirements; “multi-contextual” in that they encapsulate metadata that represents both a business and a technical or infrastructure perspective.  They are also generally derived from a collaboration of business and IT stakeholders.  If the data modeling practice is mature, the models and the definitions they contain were created under some form of versioning control, review, and approval processes and industry-standard notations and methodologies.  In other words, the data modeling process is governed in its own right which naturally dovetails into and supports data governance at the enterprise level.  So it’s not good enough to say that data modeling supports data governance because, truth be told, data modeling and data definition through modeling is a key pillar of data governance.

Being the leader in data modeling, erwin Modeling has been delivering valuable capabilities in support of data governance for years.  It’s in the form of reusable templates, naming standards, use-defined properties, and support for other standards. It’s the relationships between the entities that capture the business rules and constraints inherent in our businesses and reflected in our data assets.  It’s the sound model management practices that promote collaboration and enable traceability.  Similarly, as data modelers, you have been living, breathing, and evangelizing data governance within your organization with every model you create.

As a heads up, I will be participating in a panel discussion on this very topic at DATAVERSITY’s EDGO conference on January 27th.  I would recommend attending this valuable virtual conference for anyone interested in this topic or data governance in general.

As an old grizzled data modeler (who asked to remain nameless) asserted in a conversation on the rise of data governance as a topic of interest and inquiry, we have been practicing data governance for decades.  We didn’t need a fancy name, we just called it good data administration.  Just another example of data modelers being ahead of the curve and leading the charge.

In this new year of 2016, make sure you resolve to hug a data modeler.  They deserve it more that you realize.

Have a great year!!!

One of the analogies I used at the time leverages my own experiences over the years in IT. In the late 80’s, the rise of distributed computing threatened to take over from the mainframe. Over 25 years later, it still is “threatening,” but the mainframe is alive and well. Why? Because both have their purposes, and every large IT shop these days lives in a hybrid world.

Skip forward a number of years to the start of virtual computing. I recall speaking with a large customer who loved using the leading virtualization tool for testing and QA duties but “never for production.” A chance follow-up meeting a couple of years later revealed that, indeed, they were now putting VMs into production “where and when it made sense.” They’re living in a hybrid world.

Finally, I thought about cloud computing and how things were a few years back. Everyone was setting up private clouds and using SaaS applications (i.e. public cloud); I was leading an initiative at erwin around assessment and management of hybrid cloud environments – whether workloads should be placed in private or public clouds. Today, customers that I speak with on this topic confirm that they look at both options. They live in a hybrid world.

This leads us back to the topic at hand – the hybrid nature of data.

I’ve spoken with data architects, data modelers, and other database professionals who have built their careers with SQL & structured databases. It’s clear by looking at market trends that there will still be an increasing demand for these skills and products to help them in the future. Companies, however, are getting interested in Big Data and what value it has to bring business insights into seemingly unrelated (and previously unavailable) data.

One of the major analyst firms publishes an annual graphic showing emerging technologies and where they fit with respect to perception vs. reality. For the first time in 2015, Big Data is no longer present on this list, which proves that it’s no longer a promise. It’s reality. By my estimate, somewhere between 10 and 15% of large organizations have some sort of NoSQL/unstructured initiative in full production. Many more are in various stages of exploration and exploitation of Big Data.

The challenge that we at erwin see is that the practices, procedures and levels of governance with “small” data don’t yet fully exist with “big” data. I saw this same thing with distributed vs. mainframe computing, virtual vs. physical computing, and cloud vs. on-premise computing. Similar challenge, similar problem.

Big Data initiatives to date have been largely focused on the “why” and “what” and not so much the “how” – how they will manage them. Govern them. That’s why we released our Data Governance edition of the erwin Web Portal; you can look at all sources regardless of the modeling tool used. Ultimately it’s not about “big” data vs. “small” data, it’s just data.

There is a French saying: “plus ça change, plus c’est la même chose.” It means “the more things change, the more things stay the same.” I’ve found this to be true of IT as well. Rather than Big Data becoming a disruptive force and a replacement for small data, it’s a complement to small data. There’s ample room for both.

So, it’s time to stop questioning where we’ll end up. We’re living in a hybrid world with a lot of opportunity for data management professionals. Good times are ahead!

The 10th Annual MDM & Data Governance Summit, held in NYC earlier this week, was somehow different. It was cathartic and in many ways an eye opener in terms of how MDM/Data Governance and, by extension, the practice of Data Management has matured and morphed over these many years. Before I begin “waxing philosophical,” I would like to thank Information Management and the MDM Institute for a thoroughly enjoyable, well-run and germane event.

My colleagues and I have always been consistent in our belief in the following: Data represents the true value of what IT delivers to the business and is truly a strategic asset. As such, it is imperative that data be managed and measured just like any other strategic asset. While IT professionals are critical in this endeavor, the business needs to be an equal and active partner in data management. Data models (metadata visualization) add significant value to most if not all data management initiatives and are critical to enabling business stakeholders to take their place at the table.

I am being brutally honest when I say that, over the years, there have been times where I felt like I may have been barking at the moon.

Which brings me to my experiences at the summit this week in New York. The event was not an awakening so much as a confirmation to the changes taking place in this space.  There is plenty of research, anecdotal evidence, and success stories from analysts and pundits available out in the ether.  But nothing takes the place of seeing, hearing, and feeling and seeing the excitement and satisfaction of real people, who are making real progress, confident in their ability to make a real impact on the success of the organizations they serve.

The value and importance of data is now accepted. It no longer takes the back seat to the infrastructure and “cool” apps. Data management is moving from an IT-driven infrastructure management exercise to a business imperative that is owned, driven, and funded by the business. Attendees in my session (65+ ☺) and the event in general were, for the most part, business people. They are sponsored, funded, and focused on what’s needed to achieve their goals. Additionally, the perceived value of data models and metadata is on the rise, not as a tool for IT to answer the annoying questions of the business, but as a true enabler for and by the business.

A perfect example of this shift in approach is “Big Data” and how it’s being adopted. In the past, new technologies have been driven by IT as an answer to a physical problem (i.e. performance, scale) or because it is a “cool” new toy. While elements of a technology driven approach still exist around “Big Data,” the majority of attendees I spoke to were taking a much more mature and business-oriented approach, focused on managing and integrating this new technology out of the gate to ensure they can realize the true “return on opportunity.”

Finally, as the leading data modeling provider, we are no longer trying to convince people that we can add value to these strategic data management initiatives and non-traditional (from a data modeling perspective) roles. Organizations are demanding it.

As a part-time musician and child of the 1960’s and 70’s, I should probably quote Bob Dylan and say “the times they are a-changin’.” Instead, I will break with convention and quote a band from the (yikes!!!) 80’s, Timbuk3: “the future’s so bright, I gotta wear shades!”