Can Software Help My Data Governance Initiative?

This is a question that never came up very often the first few years I was a Data Governance Consultant but these I am being asked it much more frequently.  I think that the increase is due to the fact that there are good data governance tools available now and that data governance is getting much more focus than previously.

In the last couple of years, I have seen a move away from companies implementing data governance because they are in an industry where their regulator requires it, to organizations starting data governance purely because of the benefits they can achieve. That also includes companies looking to extend what they had put in place to meet regulatory requirements across more of their organization.

Before I answer the question, I think it is important to emphasize that despite having the word “data” in the title, data governance is more about people than data.  Most of the work you will do when designing and implementing a Data Governance Framework is around organisational and cultural change.  It is about the roles and responsibilities around data and the processes that these roles will follow.

It is for this reason that when Data Governance tools first started emerging I have to admit that I was skeptical about whether they could really help.  In fact, if you search the internet hard, you may even be able to find some comments I’ve made in the past along those lines!  After all, in the early stages of a Data Governance initiative I seldom find myself sitting at a desk using any type of software (data governance or otherwise); I am meeting and engaging stakeholders.

However, over recent years, having seen these tools evolve, I have revised my opinion and will happily say that yes, they can help you do data governance, but when I say yes it does come with a caveat.  In order to add value to your Data Governance initiative, they must be used in the correct manner and at the correct time.

Data Governance Tools Can Only Facilitate

The tools out there can be fantastic enablers and facilitators but they cannot do your job for you.  On more than one occasion I have heard of companies who have purchased such a tool and thought that that was it – job done.  However, it soon became clear that the tool “was not working.” Upon investigation, it became obvious that the tool was not the problem.  The business believed that it would do everything for them, which clearly it cannot.

If your whole data governance initiative centres around a tool, it is unlikely that your business user will ever engage, because they will be under the mistaken belief that the tool will do all the work for them.

You will still need to get stakeholders engaged in the process because without their buy-in, the whole initiative is likely to fail. The tool won’t work unless the whole business is signed up to data governance in the first place. Tools do not relieve them of any responsibility. Instead, tools should be positioned as enablers that make it much easier for people to execute their data governance responsibilities.

Remember: it’s not the tool that causes a data governance initiative to hit the rocks. The initiative fails when too much attention is focused on the tool, and too little attention is focused on getting stakeholder buy-in and change management.

Do Not Deploy Too Soon

Another reason I’ve seen problems arise around the use of tools is when they are deployed too early in the Data Governance initiative and the organisation is not mature enough to know how it wants to use the tool.  Without fully understanding what Data Governance is, the scope of their initiative, or the functionality of the tool, it is naive to rush into using one.  A company can expend significant time and resources on setting up a Data Governance tool only to find that they have set it up in manner that does not facilitate their Data Governance initiative or meet their requirements!

So What do Data Governance Tools do?

So let’s be clear on what such tools can do. Primarily, they provide data glossary functionality; they can automatically create data lineage diagrams and have workflows that send proposed changes in data definitions or data standards to the data owner for approval.  They can also be used for logging and monitoring the resolution of data quality issues. So they really can facilitate and help embed Data Governance into your organization.

How to Use Data Governance Tools Successfully

I hate to recommend it, but I firmly believe that as you start to create and build a data glossary, your early version should be created on an excel spreadsheet.  The reason I say that is that they are easy to adapt and change as your organization matures and your business users work out what they want and need from a tool.  When you are reasonably clear what is wanted and how it should be structured, that is the time to introduce a tool into the mix.

Remember, you are trying to change how people behave in your organisation. This is not something that can be achieved by only thinking in terms of technology solutions. It is going to involve a lot of soft skills: communications, influencing, and even hand-holding as they start to embrace Data Governance.  And let’s face it: computers and software are not known for their people skills.

Tools can be very powerful facilitators, especially in larger organisations where perhaps you do not know or even know how to find out who a data owner is or what data is available; but they only facilitate and support the hard work that you need to do in person.  There really is no way to avoid it… You are going to have to go and talk to people!

Thinking that software tools are the answer is just one of the top data governance mistakes that I’ve seen organizations make.  If you want to find out what the others are (and how to avoid them), you can download a free report here.

What is the Difference Between Policies and Standards?

This question is one that I have been asked a lot over the years, and has led to some interesting debates! But before I dive into my thoughts on the matter, I think that there is another question that needs to be asked (and answered first):

Why the confusion?

Why do these two terms cause so much confusion? After all, they are commonly used business terms. It’s not as though they are specialist data management jargon. The Oxford English Dictionary defines these two terms as follows:

Policy: A course or principle of action adopted or proposed by an organization or individual (Wikipedia elaborates this further saying that: A policy is a deliberate system of principles to guide decisions and achieve rational outcomes. A policy is a statement of intent, and is implemented as a procedure or protocol.)

Standard: A required or agreed level of quality or attainment

The way I use these terms in the context of data governance pretty much follows the above standard definitions. However, confusion arises as many people use the term policies when I would use standards, so whereas I would say that in data governance terms an organisation will have one Data Policy and many Data Quality Standards, I know that a lot of practitioners say that an organisation will have many data quality policies. So to clarify, the definitions I use are:

Data Policy: a formal document that describes an organization’s approach to managing data quality i.e. what will be done

Data Quality Standard: The standard that a certain field or data set needs to achieve e.g. that a field must always be completed or the value sit within a defined range.

Conclusion

So which should you use? Well I believe that it is fine to use them how you wish (and whichever fits best with your organisation’s culture) as long as you define what you mean and communicate that definition with your audience. As with most things, confusion only arises when no explanation of what is meant is provided and those on the receiving end of your messages are left to make their own (varied) interpretations.

Not defining terms is a common mistake or omission that many organisations make, but although it causes frustration and confusion, it is not the biggest problem you will face and it is easily rectified.

Do We Have to Call Them Data Owners?

17234575_m.jpg

I spend a lot of time helping people become successful Data Governance practitioners, so it is not surprising that I get asked lots of questions about Data Governance. A very common one is about naming the Data Governance roles..  Many people worry about whether it is necessary to use standard or best practice role titles when implementing Data Governance.  By this I mean titles such as Data Owner or Data Steward.

Before I dive into my thoughts on this issue, I’d like to remind you of a quote from Juliet in William Shakespeare’s Romeo and Juliet:

“What’s in a name? That which we call a rose. By any other name would smell as sweet.”

You don’t have to have studied Romeo and Juliet or even seen the play to know the saying “a rose by any other name…” As with many Shakespearean quotes, this one gets used in our everyday lives, and this particular quote resonates with me whenever I get asked the question about role titles. I often find myself involved in such discussions when I start working with new clients.

If you are implementing a Data Governance Framework and have done any “Google” research, you probably have come across a numbers of role titles that you may want to include: Data Owners, Data Stewards, Data Custodians, Data Champions, Information Owners, Data Librarians, Data Producers, Data Consumers, and a host of others, I’m sure.

Personally, I favour a fairly straight-forward set up with Data Owners, Data Stewards, Data Consumers, and Data Producers as the primary roles. However, throughout the numerous Data Governance initiatives that I’ve been involved in, I’ve learned not to be precious about it.

Through my own personal experience and from watching others, I know how emotive job or role titles can be.  You don’t have to be egotistical to desire the “right” label; it’s human nature to desire recognition for the work we do.

Of course, when we are implementing Data Governance, we are not recruiting and appointing new staff into new roles.  We are identifying the correct existing people to take on some data governance responsibilities.  Remember, however, that even additional responsibilities which do not ostensibly change a job title need to have a descriptive name that fits with company culture. You might be the Finance Director, but you can also say that you are the Data Owner for Finance data.  It is then easy for other people to understand your additional responsibilities.

Role titles are neat things. They enable you to deliver a message about what you are responsible for, succinctly and quickly, so it is no wonder that people like and use them. But what happens if you have the wrong titles? Well, that depends on the culture of the organization, and the individuals concerned. At best, it could lead to confusion and make implementing and embedding your data governance framework more challenging.  At worst, I’ve seen it delay the implementation of the data governance initiative as people waste time in endless debates over what the roles should be called.

What I’ve learned through experience is quite simple: the name is important to a degree (don’t insist on one set of titles if they really aren’t going to work in your organization), but it is critical to define what that role is responsible for and what you need the role holders to be doing in order to make your data governance initiative a success.

My advice is to start with the list of things you need done and work out how best to group those responsibilities together in a way that fits your organizational structure. Try some of the “usual suspects” out and test their reactions. If they like Data Steward – go with it; if they don’t, try something else. It doesn’t matter if they aren’t called a Data Steward as long as they act like one.

As with all things Data Governance, pragmatism is vital: so in my view, “that which we call a Data Steward by any other name could work just as well…”

Data Governance Interview - Alex Leigh

alex_leigh.jpg

Alex has worked with over fifty UK universities, most of the sector agencies including University and Colleges Admissions Service (UCAS), Higher Education Statistics Agency (HESA) and the Quality Assurance Agency for Higher Education (QAA) and a host of practitioners in the Higher Education (HE) sector. Alex designed and developed the HEDIIP data capability framework, led the team to create the HESA in-year collection model and designed both a sector level and a HESA instance of a best practice data governance approach; and is currently working with universities to develop and implement their Data Governance frameworks,

How long have you been working in Data Governance?

I was working in DG before anyone really called it DG! Around fifteen years via data architecture and running data management teams.

Some people view Data Governance as an unusual career choice, would you mind sharing how you got into this area of work?

My route in was via developing and implementing Enterprise Architecture frameworks while I was working in Deloitte UK consulting practice. There was a lot of maturity around the business, infrastructure and application architecture but data felt very fragmented between the technology of building warehouses and databases and the link to the business objectives.

So I focused my efforts on creating frameworks and approaches to pragmatically align how data was managed to how it was used. That was fifteen years ago and I’m still trying to change the perception around data.

What characteristics do you have that make you successful at Data Governance and why?

Passion for the right outcomes, resilience when I can’t achieve them and an ethos for openness, transparency and showing everyone why doing things differently isn’t just about the organisation, it’s about helping them.

Are there any particular books or resources that you would recommend as useful support for those starting out in Data Governance?

I’m a big fan of John Ladely and use his books as my primary source of reference. Bob Seiner has some great ideas about implementing DG and I’m an avid reader of TDAN. I also carry around the latest DMBOK which is a big improvement on the original in terms of applicability.

There’s so much good stuff online now. I’d encourage any new practitioners to read and research lots of different ideas, as no one size fits all.

What is the biggest challenge you have ever faced in a Data Governance implementation?

Believing everyone was as passionate, sold and committed as I was to doing things differently. So losing support once the initial enthusiasm had lapsed. Both from those working with data every day and those who had the budget, resource and will to help change the way data was governed.  Now I am very careful to make sure everyone is starting in the same place, and make far less assumptions around priorities.

Is there a company or industry you would particularly like to help implement Data Governance for and why?

I love working in Higher Education (HE). It’s collaborative, desperately in need of the professionalization of its data assets, and – finally – ready to make some of these changes. I’ve worked in 7 industry sectors, but I’ll never move out of HE. If I can help make a difference to this sector, it feels a really important thing to do. Having kids about to enter the HE environment makes this personal as well as important.

What single piece of advice would you give someone just starting out in Data Governance?

Don’t try to fix everything at once. At the heart of good DG is changing behaviours of many people. This is not a simple thing. Talking about frameworks or technology and the like early in a DG initiative is not helpful. Find some people who share your passion for data, look for quick wins where doing things differently makes a measurable change and communicate way more than you think you need to.

Finally, I wondered if you could share a memorable data governance experience (either humorous or challenging)?

I once asked an attendee at a workshop why she looked so glum. Her reply was "This is how I feel about data. I work in planning and I know at the top of the ‘data mountain’ it is sunny and lovely and all the data is perfect.  The data gets to me in this dark valley at the bottom of the mountain via a stream that all the sheep has wee’d in. That’s why I look so sad"

It was an amusing anecdote but made me realise that you really have to show people how things can be better, before actually asking them to do something about it. 

Data Governance Interview - Dr. Irina Steenbeek

irina_steenbeek.jpg

Irina is a dedicated Senior Data Management, Financial and IT Professional with 15+ years of extensive experience in data management, software implementation, financial and business control, and project management. During the past year, she has also immersed herself in data science. She sees that big data and data science have a huge potential for business development. These areas are crucial for the development of data management, including data governance.

How long have you been working in Data Governance?

It has been over 7 years now, since I first started working in data management. During this time, I have also engaged a lot in Data Governance, mostly through hands-on experience in SMEs and large international organizations.

Some people view Data Governance as an unusual career choice, would you mind sharing how you got into this area of work?

For me, this career path started quite organically as a result of several challenges in related areas. The first challenge was to create an automated solution for management accounting reporting within an organization. During the development of an organization-wide reporting system, I came across various issues, such as massive numbers of non-reconcilable Excel reports and the presence of three separate reporting platforms. This lead to the implementation of a data warehouse in this company. This implementation also highlighted data quality issues. This was not all, but it started a long journey towards the management of the data.

What characteristics do you have that make you successful at Data Governance and why?

I think that well-developed communication skills always come in handy. Establishing a common business language between your colleagues and partners, as well as clear communication with the stakeholders helps a lot if you want to set up a good data management structure. A data management function connects various departments of a company, and it is great if you can get practical support of top management, or work in an environment and culture that can enable you to execute your function in the most effective way possible.

A while ago I have written a blog on this topic: ‘Am I a successful Data Manager’ Feel free to consult it for more tips that I have to share.

Are there any particular books or resources that you would recommend as useful support for those starting out in Data Governance?

Recently I came across The Practitioner’s Guide to Data Quality Improvement by David Loshin, published by Morgan Kaufmann in 2010. I think this book is quite useful for DQ professionals.

But in general, from my practical experience of working closely with business stakeholders, I have reached one conclusion: people are not interested to know what they need to do. They are eager to know how to do what is expected from them.

At an early stage of my professional development I used DAMA DM-BOK as my main reference point. And of course, I have done a fair share of internet browsing and analyzed the materials I could find, originating from numerous sources. So far, I haven’t been able to find any practical guide that could help starting data management professionals.

This experience brought me to an idea to write my own ‘The Data Management Cookbook’, a brief summary book on Data Management, which is here. The extended ‘Do It Yourself’ Data Management guide will be available in June 2018.

What is the biggest challenge you have ever faced in a Data Governance implementation?

There were several, it is difficult to say which one was the biggest or most important. The first one is finding your own way to implementation of data management, and figuring out where to start. The second one is convincing data owners that they have to take on responsibility for their data. And the third one is more technical: the investigation of data quality issues caused by applications.

Is there a company or industry you would particularly like to help implement Data Governance for and why?

In my career, I have worked in all kinds of companies, large and small. All in all, I think I prefer small and medium businesses to large and famous multinationals.  Why? I know it doesn’t sound very ambitious. Smaller companies feel more like a ‘family’. And I appreciate this a lot, as this feeling creates a great work environment. You know everyone and you can get things done quickly and efficiently. It is easier to involve your colleagues in all the processes, which is crucial for successful data management. Even if the resources are limited, you can still deliver tangible results in a short period of time.

What single piece of advice would you give someone just starting out in Data Governance?

You do not set up data management just for fun. You do it because you have certain

needs, a certain goal will drive you to do it. GDPR or data quality are the best examples.  My advice is to first get a clear picture what your goal, your driver is. As soon as you know the direction you should be working in, it will be easier to figure out which components will need most of your attention and in which order you should proceed.

Finally, I wondered if you could share a memorable data governance experience (either humorous or challenging)?

When implementing data management, you have to ensure collaboration between various stakeholders. These are people with different interests, needs and tempers, and you are the one who has to combine them all into one effective working system. One of the most memorable moments in my career was a question of one of such stakeholders: ‘Where do you get so much patience to permanently stay calm, have good relationships with all of us and still keep going?’. I guess only a data manager would know. :-)

Data Governance Interview - Matt Becker

MBecker-Headshot-300x300.jpg

 Currently, Matt serves as the Managing Director of Sullexis’ Enterprise Data Strategy and Solutions practice. He has spent 18+ years creating and implementing strategies that drive client performance through technology adaptation in areas ranging from big data to enterprise data management to business intelligence and analytics.  He enjoys delivering the value gained by implementing solid information management principles, thereby reducing inefficiencies and gaining insight into overall operational performance.

How long have you been working in Data Governance?

I spent the early part of my career helping to design and implement various data warehouses and analytics for the Energy Trading & Risk Management industry.  Because of the regulations involved in ETRM projects, starting around 2005, I started incorporating data management procedures and reporting requirements to identify, verify, and track the adherence to the data regulations associated with those DW initiatives.   In fact, every data project that I now oversee, has had some sort of DG set of deliverables.

Some people view Data Governance as an unusual career choice, would you mind sharing how you got into this area of work?

It was a combination of by accident and necessity.  Because of the reporting and visualization work I was doing on various BI / Data Warehouse implementations for the Energy industry early in my career, I started seeing a pattern emerge.  The data quality after the go-live of the data warehouse was usually very high but quickly degraded.  Many times, this was a result of the tools being used and the people involved not following a standard approach or adhering to an agreed set of guidelines to maintain the availability, usability, integrity and security of the data.

So, I typically became the person that would build that data quality discipline into the project, usually in the form of a roles and an accountability matrix.  This matrix would define the data requirements and standards needed for ongoing support and maintenance.  Over time this evolved into working with a number of clients on specific DG initiatives helping to provide a framework and a playbook for the overall management of data to drive quality, consistency, and usable insights.  

What characteristics do you have that make you successful at Data Governance and why?

Good blend of having been a business analyst, developer, tester, architect, and project manager. Having done all of these roles throughout my career has given me valuable exposure to all aspects of a solution lifecycle (planning, design, architecture, code development, testing, implementation, and deployment).  Understanding of this framework for a typical project enables you to apply a similar framework and approach for Data Governance methodology (i.e. planning of roles needed, design of the roles and processes to be used, active communication and coordination across both IT and Business functions).

In addition, deep domain knowledge is an added plus in helping to shape the data governance priorities between the IT systems and the business operations.  For example, I have spent quite a few years in the Upstream Energy sector, where Well Data mastering is a significant challenge.  Too many times, companies focus on just throwing technology at the problem to try to solve their data availability and reliability issues.   However, the issue was that the data in system A did not match to system B because the data wasn’t properly defined (i.e. a Well Legal Name vs. Well Short Name, or Spud Date vs. Drill Date) resulting in more expense and time than what was really needed.  In these situations, the company in question has not prioritized their efforts to first develop a common Well language, using DG standards, to ensure a foundational understanding of the data.  Too often, when this step is done first, portions of the existing technology and solutions available in-house can typically be repurposed, saving on the overall expense and allocating those funds to more prescriptive technological solutions needed.

In fact, at Sullexis, we have a section of blogs on our website (http://sullexis.com/blog/) that talk about combining the right data practices with technology to improve such things as data migrations and on-going data quality through practical DG practices.  One of our most recent blogs focuses on creating a common data language to ensure there is a mutual understanding of core concepts central to the company’s operations.

Are there any particular books or resources that you would recommend as useful support for those starting out in Data Governance?

  • DAMA’s DMBOK v2 – A fundamental guide to data governance
  • Manager Tools.com (https://www.manager-tools.com/) – you have to understand how to manage teams, individuals, projects, and processes in order to be effective in implementing data governance.
  • https://www.nicolaaskham.com/ - your website has a lot of great articles and blogs that serve as a very good aggregator of data governance knowledge from a broad and varied set of sources.
  • Practical Data Migration (Johnny Morris) – great book for working data migration efforts, which is many times how Data Governance gets introduced into an organization.
  • Visualization and Reporting Tools:  Tableau, Spotfire, Business Objects, MS Power BI – understanding how reporting and analytic tools function, are implemented, and how end users utilize them to properly is important to know how to combine their use with DG methodology.

What is the biggest challenge you have ever faced in a Data Governance implementation?

The big challenge is the same one I face at almost every client I work with where Data Governance is a new concept…understanding.  There are many companies that don’t realize that one of their most valuable and key assets is their data.  If you think of data as a garden, one needs to take the time to remove the weeds (bad data), clean out the clutter and debris (duplication), till and care for the soil (managing your technology stack), and properly feed and water (define and execute your roles and procedures).  These on-going activities (data governance process) result in the garden yielding a good crop (high quality, reliable data).   I like to take the time to engage and educate the right levels in the organization to solidify their DG understanding and ultimately gain their support.

Is there a company or industry you would particularly like to help implement Data Governance for and why?

Oil and Gas/Upstream Energy – first this is where I have spent quite a bit of my career, but secondly, many of the newer technologies (Big Data, Cloud, IoT, etc.) are just now being implemented, and there is an explosion of data and the need to better govern its use.  Executives are realizing the need to treat data as an asset and with that you must have the right governance and coordination between people, process, and technology to keep your employees safe, your solutions effective, and your operations competitive.

What single piece of advice would you give someone just starting out in Data Governance?

One of the best bits of advice that I received from my very first project manager about a year after I graduated college was "I want you to be the 'Go-To team member'."

Be the one who is willing to do the task nobody else will. Dig in to the details of the data processes and the business users that use them on a daily basis.   

Be the one who may not know the answer but will go do the work to find out.  Get into the weeds of the data issues or challenge so that you understand the root cause.  This will help you identify the data governance approach to employ to accounts for those issues.

Be the one that others will look to for a good attitude, a positive outlook, and assurance the job will get done and get it done well.  You will be amazed how well people will respond to you if you are positive to them…and many times when dealing with data issues, you need to stay positive!

Finally, I wondered if you could share a memorable data governance experience (either humorous or challenging)?

I was at a recent data visualizations conference and many of the sessions were focused on technology improvements like better leveraging IoT technologies in daily operations, no-SQL solutions for data aggregation and consolidation, and new visual modeling techniques using R-based tools.  But the most heavily attended session was about a company’s data governance journey and how they changed their culture and their methodologies to focus on data as the cornerstone of their operations.  The questions that I heard after that session warmed my heart.  So many times, it takes a large undertaking just to get people to understand why data governance is so important, but now the conversations were focused on the how and not the why or the what.  Everyone wanted to know how they could go about implementing data governance in their organization.  I think that is representative of a movement in global corporate community…this increased focus on data.  I think this is just the beginning of a data governance revolution!

 

Data Governance Interview - Suzanne Coumbaros

suzanne_coumbaros.jpg

Suzanne is a fellow DAMA UK committee member and a data management professional with many years of experience in data management including governance, architecture, data warehousing, business intelligence, data quality, data development and data strategy. Originally a computer programmer, statistician and mathematician from Cumbria UK, she has worked for many government led organisations and well-known public and privately own companies both across the UK and Africa. Her background comes from having created data management teams in different organisations and countries.

How long have you been working in Data Governance?

I have worked in data management roles for the last 20 years and specifically in Governance lead roles for nearly 10 years.

Some people view Data Governance as an unusual career choice, would you mind sharing how you got into this area of work?

Having spent many years solving corporate and law enforcement agencies data issues, I designed a number of data warehouses and began to investigate best practice data management. I came across DAMA and soon their DMBOK became all I read. It resonated with all the areas of data management I had already fulfilled and I was intrigued by the central function of Data Governance which binds these altogether. As I learnt more about this area I worked hard to put what I had learnt into practice with my first governance role. It was a great learning curve as I quickly understood that changes in an organisation’s people, processes and technology, not to mention the regulator changes, mean this role never stops. I then secured a Data Officer role in financial services where I was able to quickly implement data governance and begin working with the development team to use this to enable the development of a single client view.

What characteristics do you have that make you successful at Data Governance and why?

Patience is key. Knowing that data governance may not be the organisation’s number one priority means that you may have to wait your turn to be heard. Following on from that, having empathy for the management and executives in the organisation will help you appreciate their responsibilities and other commitments. This will ensure governance is not forced, but is ready when they are. Finally having sales skills will be essential. Governance is not for everyone and will not sell itself; regulation has helped make it a topic for organisations but it should be driven as an enabler and not just a tick in a box for the regulators.

Are there any particular books or resources that you would recommend as useful support for those starting out in Data Governance?

Without a doubt the best and most important book you should have by your desk is the DMBOK from DAMA. They recently published volume 2 and it is my “go to” resource for all data management queries

What is the biggest challenge you have ever faced in a Data Governance implementation?

When I was brought into one organization I joined because I was told of the huge investment they were making into data management only to soon find out that the executive sponsor was leaving and the governance function was now only a ‘nice to have’ rather than the key focus for the organisation.

Is there a company or industry you would particularly like to help implement Data Governance for and why?

I really enjoy helping others and so working for an organization that does this is important to me. I have had the privilege of working in a variety of organisations dealing with different types of data. By far the most rewarding was helping law enforcements and government agencies manage their data to ultimately help solve crimes. I also enjoy the enormous challenges of financial services and the huge importance of governance that the regulations place on these organisations.

What single piece of advice would you give someone just starting out in Data Governance?

I would suggest getting a mentor. Someone who has experience in governance and is able to help you.

Finally, I wondered if you could share a memorable data governance experience (either humorous or challenging)?

Discovering that South Africa had 11 valid address types and 11 official languages… a data governance dream or nightmare :-)

Data Governance Interview - Jan Lenders

jan_lenders.jpg

Jan started his professional career as a bookseller and made the obvious switch to IT in 1986, working as an application programmer for a data centric application for the financial industry. From 1990 onwards, he focused on database design and later moved into data integration. In 2007, he decided to switch to a non-profit organisation and specialise in data integration. Since then, he has been working for a university of applied sciences in Arnhem, Netherlands.

In 2015, he obtained a MSc degree in IT at the University of Liverpool. For his dissertation project he researched the mutual effects of choices in Data Integration and Propagation areas on Master Data Management (MDM) and Data Governance (DG).

How long have you been working in Data Governance?

Although I do not have Data Governance as part of my official job title, I have helped to initiate DG initiatives and projects in our organisation. I learned from you that DG should not be an IT-led initiative. However, since our university did not have any official DG policies, IT as a provider of master data interfaces, was confronted with virtually all data issues. The only way to provide data with a reasonable level of quality was for IT to lead the initiative. As I have now learned from you, this is a textbook example of Mistake #1 of the 9 biggest DG mistakes, but we had to make a start.

Some people view Data Governance as an unusual career choice, would you mind sharing how you got into this area of work?

Throughout my career in IT I have been involved in managing data. While data has gained a dominant position in the IT landscape and data volumes are growing rapidly, I do not think DG has grown at the same pace and its importance is being underestimated. So as an IT guy, my involvement in DG arose from the lack of it in the organisational units where it should actually be allocated since we try to deliver qualitative good data.

Are there any particular books or resources that you would recommend as useful support for those starting out in Data Governance?

Any IT worker involved in data management should visit IRM UK’s Data Governance conference and MDM summit at least once. For me, the books written by Alex Berson and Larry Dubov, as well as David Loshin’s books have been very helpful to understand DG. But I honestly learned a lot from your report "The 9 biggest mistakes companies make when implementing data governance". We seemed to make most of these mistakes in our organisation, but we currently are working on solving the worst of them.

What is the biggest challenge you have ever faced in a Data Governance implementation?

That would be the underestimating of DG's importance by the business units and overestimating the quality of their data. For instance; we did not have one dedicated source system for organisational units. As a result, codes, abbreviations and names for units were kept and maintained in virtually each system without consensus. This had never been a real problem until data was being exchanged between these systems.

What single piece of advice would you give someone just starting out in Data Governance?

Spend half a day in each business unit with the people who are actually browsing, searching, entering and changing data to understand what is happening to their data and in particular why.

Finally, I wondered if you could share a memorable data governance experience (either humorous or challenging)?

Data quality issues are likely to become painfully visible when data is exchanged between systems. To illustrate the understanding and importance of DG in general and data quality in particular I often make a comparison with traffic and traffic rules:

In France everyone drives on the right side of the road. Because there are agreements that are maintained, there are relatively few problems in traffic.

In England everyone drives on the left side of the road and again there are few problems.

The real problems only manifest themselves when cars leave from the mainland go to England or vice versa. This can only work if good agreements are defined and enforced.