Data Professional Introspective: EDM Education – Part 1 Why, What & Who

In my previous column, “Piloting the Plane – EDM Program and Project Management,” I explored perspectives, structures, cultures, approaches and activities needed to establish and successfully manage an organization-wide Enterprise Data Management (EDM) program.

In Part 1, we are going to focus on why EDM Education is needed, what learning objectives it should deliver, and who needs it.

In Part 2, we will address when it is needed, creating an education plan, discipline training and associated metrics, certifications, and how education should be conducted, including learning techniques and tips to help make your courses interesting and effective.

Bob Seiner of KIK Consulting and the Publisher of reminded me that the basic distinction between ‘education’ and ‘training’ should be clarified. Although we often use the term ‘training’ generically, as Bob succinctly stated, “The aim of education is to familiarize people with concepts; training is what and how to do something.” For these columns, the emphasis is conceptual learning and we’ll briefly address skills and technology training.

Why is EDM education needed? Because if the prevailing attitude is ‘do what we’ve always done’ then the result is ‘get what you’ve always gotten.’ When an organization has evolved to value its data and is committed to improve the definition, quality, and access to data,[1] it’s a mistake to believe that this foundational transformation will be as easy as flipping a switch (‘Eureka! We’re all Data People!). Many executives (in all industries) want to believe that they can simply direct their staff to ‘go forth and do!’ without a clear strategy or providing commensurate learning opportunities., Our answer, however, comes from the philosopher Bertrand Russell– “To understand the actual world as it is, not as we should wish it to be, is the beginning of wisdom.”[2]

However, most organizations are crystal clear about the fact that developing, integrating, maintaining, and sharing accurate, timely data is critical to their business goals and objectives. The challenge is how to achieve understanding and unanimity of purpose, direction, motivation and action. As George Leonard, founder of Esalen Institute, stated, “Ultimately, human intentionality is the most powerful evolutionary force on this planet.” Data management education is the engine of empowerment[3] and enlightenment.[4]

Even in successful organizations, a significant percentage of staff has yet to grasp that “data is a thing,” according to Jeff Wolkove, Arizona Strategic Enterprise Technology, the EDM leader for the State of Arizona, who has established a State-wide EDM program for 100 agencies. They’re accustomed to managing items like computers, desks, and networks, but the concept of ‘asset’ isn’t typically generalized to data. For example, people intuitively know that they should enter correct data into a system, but they usually aren’t considering impacts on business processes or decisions if the data is incomplete or wrong, so they may not validate as thoroughly in the interest of speed.

In my last column, I claimed that “for data governance to succeed in its three main functions–building, nurturing,[5] and controlling the data assets–you have to find a way to win the hearts and mind of each participant.” EDM education accomplishes that goal by equipping staff to conduct collaborative analysis and decision-making with focus and enjoyment.

Consider your staff as your customers. Instead of purchasing your products and services, you want them to perform energetically in creating and improving your products and services. Education fosters both intrinsic motivation and know-how. Staff time is a precious resource, so you to maximize that time by creating favorable conditions. You want your ‘customers’ to achieve satisfaction and want to continue in their role–job satisfaction is a major factor in retention (the others are growth in responsibilities, and of course, compensation).

Conceptual education about enterprise data management–how the many disciplines of data management work together to evolve the desired target state for the organization–supplemented by discipline-specific learning. For example, how to create a quality rule, how to define a business term, how to work with IT for a new application, etc. enables individuals to accomplish three learning goals:

  • To expand their perspective beyond a specific area of action and influence, like an astronaut’s first voyage into space and seeing the whole earth–the “aha!”
  • To communicate effectively about data with colleagues and management through a common conceptual schematic and shared terminology
  • To organize concepts and skills that they may already know and act upon, but haven’t yet put together in a comprehensive structure, like being able to clearly see the pattern of the strands in a spider’s web.

My teaching experiences have taught me that conveying key concepts is essential, but they don’t become ‘sticky’ if they remain abstract. They must be brought to life, illustrated by practical, real-world scenarios. Like many of my esteemed industry colleagues, I make extensive use of case studies, sample scenarios, hands-on individual and group exercises, and hundreds of implementation examples.[6]

For example, I’ve taught Building EDM Capabilities, a three-day course leading to the Enterprise Data Management Associate certification, many many times. All attendees (whose job roles encompass a broad range, such as business analyst, data governance leader, technical data steward, data architect, auditors risk leader, and Chief Data Officer) emerged with a broader viewpoint and renewed enthusiasm for participating in their organization’s EDM projects. The bulk of the feedback received is that the course enhanced their understanding of:

  • Why all data management disciplines are important
  • How they are mutually interdependent across the organization
  • What the benefits are to the organization of performing them competently
  • How to address implementation obstacles.

Another strong argument for why EDM education is necessary is illustrated by Jeff Wolkove, Arizona Strategic Enterprise Technologies, the EDM leader for the State of Arizona. Without any state-wide mandates for EDM, he determined that ‘driving change through implementing policies is the key.’ With a multi-agency governance group (cultivated, recognized, and rewarded) he obtained approval for and rolled out a Data Governance Organization Policy, a Data Governance Operations Policy, an Interoperability Policy, and a Data Technology Policy. A State Data Quality Policy is about to be released. [Shorthand–an implemented policy is included in State agency audits–creating a ‘stick,’ as in ‘You don’t want to be in non-compliance, do you?].

So, he led the horse to water, but how was he going to get them to drink? With 100 different agencies, each operating separately, and no previous state-wide emphasis on data management, each had significant divergences in data management concepts, terms, capabilities, and approaches. Championing a number of DMM Assessments, Jeff raised awareness of improvement plans and roadmaps across the state and determined that he now needed a tasty ‘carrot’ to bring the majority of employees into the fold. [Back to ‘winning hearts and minds,’ as in ‘Why should I care?’ and ‘How are you going to help me?’]  

As George Leonard stated, “Mastery is not about perfection. It’s about a process, a journey. The master is the one who stays on the path day after day, year after year.” Jeff sponsored several EDM certification courses for his governance group, and then directed development of a full suite of computer-based training (CBT) for the entire state government[7], which has been taken by over 6,600 state employees to date, with an expected target of 20,000 employees. [8]  Since the ability to comply with policies requires a minimum knowledge base, the carrot/stick construct Jeff envisioned and implemented is clearly demonstrating its effectiveness.

Moving onto What, highlights of useful educational content are summarized in the table below.

Is this everything? No, not by a long shot, but it will get us started.

I spoke with Deborah Henderson, Managing Author of the DMBOK 1.0 and the driving engine for most of the DMBOK 2.0[9] for this column. From her extensive teaching experience, she has observed that “most people have no perception of data as such; they think in the context of systems, screens and reports.” Down to bedrock here, and I think we all agree that this is the usual scenario in many organizations. Deborah recommends that spotlighting the importance of data through clear definitions of terms and concepts is important for everyone who uses or produces data, clarifying how data is separate from applications.[10]

Starting at the bottom of the list, let us outline some suggested topics to address in a Data Awareness course, intended for all staff who either produce or use data or reports–from the summer intern to the CEO.

Since you are aiming at a very broad audience, the recommended format is CBT, and the recommended length is 15-20 minutes–a condensed elevator concept pitch with examples relevant to the organization. Ideally, your top data executive will make this course mandatory. (More about planning and rollout in the Education Plan in Part 2). The minimum everyone needs to understand includes:

  • Systems (screens, business rules, and reports) are built to capture, store, and modify data–data is the POINT, not a by-product of features
  • Everyone who uses and produces data should help to ensure good data
  • Correct data entry is important–follow procedures, validate and be consistent
  • Quality data begins with you–if it is broken, help to fix it
  • Participate in a data working group–work with peers to solve problems
  • Elevate data issues to management.

The Data Lens course is aimed at technical data stewards and those responsible for designing data stores and interfaces (bulk or point to point), migrating data, integrating data, technical evaluation of vendor products, and capturing, storing, and publishing technical and operational metadata. The rationale for a course targeting this audience is to harmonize what IT does with what business line data governance and the EDM Program strategy is trying to accomplish.

Throughout my career, I have worked with over a hundred IT project teams. These teams have been in roles including ensuring data standards compliance, reviewing data models against system requirements, instituting data design best practices, training on data requirements, and mapping custom data structures to vendor products. This education has focused on mentoring developers and development DBAs about ‘what to do with the data part of the solution.’

Bottom line, IT is perennially BUSY. They are always marching to schedule and budget, most of their projects are under systems lifecycle phase requirements and approvals (whether waterfall, agile, or a hybrid approach), and their mission in life is to satisfy the business owner who is paying the bills. Therefore, IT is often the LAST group in the organization to come on board the data train (sad, but true).[11]

Since it is difficult to get executives to mandate changes in IT itself (they worry about those deadlines and budget constraints) education is the second line of defence. If we can reach all those developers, etc., we’ll have a fighting chance at getting them to read the data management policies, processes, and standards, and move towards an improved state of business-as-usual.[12] The minimum they need to understand includes:

  • Think about the data – BEFORE you select the technology, toolset or platform, BEFORE you design the database or specify interfaces, WHILE developing functional requirements, APPROVING data mappings before migration, USING the published data standards, etc.
  • Check for enterprise data – Make it your business to find out if, and where, shared data has already been defined, in business term lists, in metadata repositories, in shared data stores, in master data hubs, etc. (aka, ‘for Pete’s sake, don’t create another version of Customer, or Financial Instrument or Patient, just to meet a deadline’).
  • Improve data requirements and interface specifications – Don’t let the development DBA design the database on the fly, clearly specify data requirements, do a data model and have it reviewed, and document those interfaces and web services.
  • Expand your interactions with data management, governance, and the business lines – From the IT perspective, identify both your immediate and extended stakeholders. In other words, be proactive, don’t seek forgiveness later. (As data management, we’re playing the long game–every serious deviation adds complexity to the data assets, adds to steady state spend, makes integration more difficult, makes analytics more complex).
  • It is your problem – If the organization has committed to an EDM program, and since IT holds up half the sky, it is imperative that they get religion, or the curve of progress will be unduly flattened.
  • You’re accountable for metadata – The organization needs information about its data assets. IT needs to take responsibility for capturing, storing, and making available technical and operational metadata. E.g., you can’t do data lineage without it, etc.

The EDM Program needs to be a supporter of IT, which is often a big part of the problem. However, the program can easily become a big part of the solution. Offer them a course and encourage (if you can’t mandate) them to take it. Order pizza, bring snacks, whatever it takes.

Governance and Stewardship education is vital for equipping the organization to make effective decisions about and institute appropriate controls for enterprise data. For those who are recognized with an active role in the data governance workstream (a permanent function within the EDM Program), they need to learn their role. This includes the activities they will be expected to participate in, what they are accountable for, etc. –The programs will help people become familiar with key concepts, learn how governance interacts with the rest of the organization, and have a comprehensive understanding of data impacts and how they can help improve the organization’s data. Topics include:

  • Governance structure – The goals and objectives of the data governance in the organization and the hierarchy of governance components it has established.
  • Governance policy and processes – The organization’s data governance policy, and the business processes that are carried out by governance actors in the established hierarchy. This includes data definition, domain identification of data sets, business metadata, decision processes, issue escalation processes, granting data access, workflow management, etc. 
  • Governance Interaction model – How data governance interacts with other organizational units, such as business lines, IT, data management, etc. (ideally beginning with a high-level diagram which is decomposed and parsed in the course)
  • Responsibilities – What the individual’s designated role implies for expected tasking, estimated time commitments, types of work, accountability, etc. Ideally the course would include, for participants at each level, the specific type of collaborative decisions they are expected to address in multiple data management processes as they arise, e.g., data quality, data architecture, metadata, data requirements specification, etc.[13]
  • Span of decision authority to whom they report for governance activities, to whom they may delegate, with whom they seek input on shared data decisions, when they are the sole decision authority, etc.
  • Business / IT collaboration – How a governance participant interacts with IT for technology selection, vendor product migration, data store design, data integration affecting their data set(s), approvals, etc.
  • Data literacy – Deep dive on data impacts pertinent to reporting, modelling, and analytics, and how this expands the governance knowledge base and role.

In Part 2, we’ll address skills training that is very useful for business and technical data stewards and data domain leaders, including:

  • How to read (and review) a data model
  • How to write data requirements
  • How to write quality rules
  • How to determine quality thresholds and targets
  • How to analyze business processes for data implications
  • How to define business terms
  • How to determine the business metadata you require
  • How to engage in external data source selection
  • How to work with IT on projects
  • How to lead data-focused teams
  • How to determine security and privacy requirements
  • How to engage in policy development efforts, etc.

World-class data stewards must have familiarity with these skills and techniques. It makes the job more fun, because mastery of any skill is intrinsically enjoyable (and we want governance participation to be both energetic and sustained over time). As George Leonard expressed it, “The essence of boredom is to be found in the obsessive search for novelty. Satisfaction lies in mindful repetition, the discovery of endless richness in subtle variations on familiar themes.” E.g., ‘Now that we all agree on the definition and values for ‘Customer Role Type,’ we can move onto ‘Customer Activity Code’ and it will be a faster process–we rock!’

Jumping the line here in the Content Highlights chart, let’s talk about what an organization’s senior executives need to learn to be informed advocates of the EDM Program. Having interviewed hundreds of executives in this context, I have several general suggestions:

  • Executive time is even more precious than staff time, so keep it short, no more than 3-4 hours in length.
  • Rehearse your course / workshop facilitation to the letter–when they take out their cell phones or start answering emails, you’ve lost their attention.
  • They analyze and green-light decisions based on the business strategy, goals, and KPIs. Make sure that your materials address how EDM contributes to the success of key planned or in-flight initiatives (representing funding they’ve already committed, and for which they expect bang-up results).
  • Research their key data challenges and opportunities in advance as far as possible–this is priming the pump.
  • Don’t contradict them–find another way to shape the concept or augment their point of view.
  • Finally, the course should consist of at least 50-60% elicitation of their perspectives and concerns about the organization’s data (they talk, you listen and engage the attendees to respond). So include important discussion questions aimed at discovering what they view as persistent data problems, as well as their business aspirations.

The content (your portion) should include:

  • The importance of active executive engagement to implement and sustain the EDM Program–proposed leadership/interaction suggestions that have proven to be effective
  • Leading by example to demonstrate that the data assets are critical–what it means to be a data-driven organization.
  • How a focus on data and implementing solid data management policies, processes and practices enables the whiz-bang, cool solutions that the vendors want to sell them–data lakes, machine learning, artificial intelligence–enhanced ability to discover patterns and trends.
  • How an EDM Program will result in cost savings over time–show them a well-reasoned return on investment.
  • A reasonable timeframe and estimated staff effort–what it will take to build a great program that meets their business needs.
  • How organizational factors can accelerate or impede the EDM Program
  • Factors for prioritization of data-centric business cases.

Since we’re recommending that the content be customized to the organization, you can add other topics that are appropriate. For example, if they have just launched an EDM Program, you can address the rationale for critical workstream dependencies, ask them to give their impressions about the scope of enterprise data, etc.

If you design the executive course / workshop well and deliver it confidently, you will not only create advocacy for EDM (a consummation devoutly to be wished), but you will emerge with considerations for enhancing the EDM Strategy and refinements to the EDM Program. If you make the most of this opportunity, it has the potential to benefit many initiatives and raise the profile of EDM in the organization.

The purpose of Building EDM Capabilities education is to accelerate the progress and enhancement of the EDM Strategy and corresponding EDM Program. It should be de rigueur for all data management staff and data management leadership, as it provides both the forest–the key concepts constituting EDM and defining the scope of ‘enterprise data’–and the trees–the component disciplines and fundamental data management practices at the enterprise level. The complexity of data management is addressed in the context of the whole enterprise.

In essence, the course contains:

  • What the EDM Program needs to accomplish, in whole and in part
  • Why the organization needs a Data Management Strategy and what it should contain
  • Why the organization needs a Data Quality Strategy and what it should contain
  • Why each process area (or EDM component, knowledge area) is necessary to manage data assets well – as in, if you’re not doing a good job on A, B or C, here are the negative impacts
  • Business benefits of competently performing sound data management processes
  • What underlying factors are required for success
  • How to proactively anticipate and combat organizational challenges to effective implementation, adoption and organization-wide deployment.

This course can be developed and organized around the organization’s selected sound and comprehensive data management framework. The course for which I led development and regularly teach is based on the Data Management Maturity (DMM)SM Model, designed as a measurement instrument of fundamental best practices with a built-in roadmap for successive capability enablement. Its 5 levels allow an organization to determine “what good looks like” and the scoring method quickly reveals the current state of capabilities, how they are evidenced, and where progress is needed. In other words, “How are we doing right now?” and “What should we prioritize next?”   

Whatever framework is chosen, an EDM capabilities course is highly recommended for stakeholders who have an active and substantive role in creating, building, and maintaining an EDM Program, as well as major producers and consumers of data in any part of the organization. It provides a common language, is a perfect opportunity to delve into the organization’s EDM Program in a collaborative setting, and fosters enthusiasm for active engagement.

If you refer to the section on Education in my previous column “Piloting the Plane,” there is a long list of questions that a business and IT project team need to answer to plan and execute successfully in a sample scenario: building a Product data warehouse. These questions are not often proactively addressed in advance, which can lead to less-than-hoped-for results, schedule delays, and budget overruns. Attendees of an EDM capability building course would automatically consider these questions and plan the project effectively.

In the chart below, EDM Education Role Identification, the highest organizational value from this course can be achieved by training three groups: Domain / Business Leaders, Domain / Business Data Stewards, and IT Data Technology staff. (As in, if you have a key role in the success of the EDM program, you should attend this course). The chart below summarizes WHO needs EDM education, by type and sample employee roles. This chart can be mapped with the Content Highlights chart to give you a good start on the EDM Education Plan explained in Part 2.

In sum–a great EDM Program requires education, education, and more education. In addition to formal courses, learning can be fostered by lunchtime presentations, overview presentations (live or recorded) and deep dives on newly implemented data management policies and processes.

In Part 2 of this column, we’ll describe an EDM Education Plan (WHEN) and metrics, discuss the rationale for skills and specific technology training. In addition, we will address in detail the many methods and techniques that you can employ (HOW) to ensure that learning happens, that perspectives are broadened, and that each individual experiences that “Aha!” moment.

[1] The unmistakable signpost of this commitment is establishment of an organization-wide EDM Program.

[2] This seems self-evident, right? So why is the predilection for fantasy thinking so prevalent in our culture?

[3] Knowledge provides confidence, which in turn engenders enthusiasm and successful accomplishments. Therefore, as the sages say, knowledge is power.

[4] Here, enlightenment refers to ‘the state of being well-informed and guided by rational thought [in this case, about data and corresponding responsibilities].’

[5] Aka, ‘sustaining,’ in a caring and devoted manner.

[6] Part 2 of EDM education will focus on instructional techniques and methods which have proven successful for data management, drawn from educators’ experiences. The proof of the pudding, and all that.

[7] Based on the DMM, “Noninvasive Data Governance,” and Jeff’s learned experiences from working to elevate data management in the State and encourage stewardship.

[8] Jeff should win a ‘Doing More with Less’ award, the operational efficiency concept of this age, as explicated by Forbes, Tony Robbins, Entrepreneur, and Reader’s Digest, and every MBA program.

[9] Her certifications, awards and achievements would make an article in themselves; had to leave some out. Her autobiography might be titled “My Life in Data Management: 40 years Before the Mast” (sorry, Johnny Depp). Deborah’s contributions will also be featured in EDM Education Part 2.

[10] Today, producers and consumers–tomorrow the world. My fondest wish is to deliver one of the final hour-long guest speaker slots at the major business schools, to impress on future CEOs that ‘Data First’ should be one of the key strategic elements of their startup companies.

[11] Have you ever tried to lobby for insertion of data considerations in the systems development lifecycle? Like requiring a logical data model for custom applications, and a compliance review of the model alongside the functional requirements? Or adding data-specific position descriptions for contract staff to RFPs? I’ve found that it’s almost impossible to penetrate the fences surrounding IT business-as-usual dictums.

[12] And folks, why not make it easy for them with an easily accessible EDM library, with work products applying to IT in a crisply identified package for project managers and their designees to find, and hopefully put into effect.

[13] For example, in the DMM, 25% of the 414 functional practices require governance engagement. There are tasks everywhere–which is why, when I propose that an organization stand up data governance, I recommend starting with one high profile project. If you told them everything that you want them to take responsibility for immediately, they might run away screaming down the street. Baby steps, building on successes.

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Melanie Mecca

Melanie Mecca

Melanie Mecca, CEO of DataWise Inc., an Enterprise Data Management Council Partner and Authorized Instructor for DCAM certification courses, is the world’s most experienced evaluator of enterprise data management programs. Her expertise in evaluation, design, and implementation of data management programs has empowered clients in all industries to accelerate their success. As ISACA/CMMI Institute’s Director of Data Management, she was managing author of the DMM and has led 35+ Assessments, resulting in customized roadmaps and rapid capability implementation. DataWise provides instructor-led courses leading to DCAM certification, as well as for data stewardship and the proven Assessment method that she developed. DataWise offers a suite of eLearning courses for organizations aimed at elevating the data culture and providing practical skills to a large number of staff. Broad stakeholder education is the key to data management excellence! Visit to learn more.

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