What is Data Custodianship?

Data Governance is full of jargon and terminology. And the interesting thing about it is that it is all subjective. Different people use different terms, well, differently within Data Governance. This is usually because of the culture within a particular organisation. The way the various terms are applied within organisations can vary their meaning. And that’s ok - but you should also be wary of it.

It’s important to make sure you fully understand the meaning of the terminologies within the context of the organisation that you are working with so that there are no crossed wires. Don’t make assumptions about the meanings of particular terms - and if you are ever in doubt, then ask. 

Now, the reason I am telling you this is it’s a very important thing to understand when we’re discussing data custodianship and what that is and means - especially if you are googling terms and looking for their meanings online. So, if you come across someone who also uses this term then ask them what and who they mean so you can be sure that you are on the same page and can have meaningful and useful conversations. 

So, what do I mean by the term ‘data custodian’? 

Well, when I talk about data custodian’s I talk about IT. This makes it fundamentally different from other roles we’ve discussed in previous articles - like data owners and data stewards - because they’re all about the business. The businesspeople who have to step up, take roles and play a part in managing and understanding the quality of their business data. But that doesn’t mean that IT is off the hook - they have a very important role to play, and that is where the data custodian role comes into play.

Very simply, they're responsible for maintaining data on your systems in accordance with the businesses requirements. Now, that sounds quite simple but quite often in an organisation before data governance has been introduced, the business may have the wrong impression that IT own the data because it is on their systems - and they may even expect IT to make decisions on how to move data from one system to another or perhaps how to transform it as it is loaded to a new system. But I don’t believe this is the role of IT.

IT can certainly advise on all these tasks, because they have the technical expertise that, as business users, we don’t have but it shouldn’t be up to IT to make these decisions by themselves. 

This can sometimes be a hard concept to grasp, especially if you’ve never implemented data governance within your organisation before, as people don’t traditionally think of the business owning the data and they’re also not very good at articulating their requirements to IT, which leaves IT having to do the best they can with what they’ve got. 

This often leads to IT being blamed for things, which I think can be unfair, when they’re just doing the best they can with very poor requirements from the business. 

So, in short, being a data custodian is all about maintaining data and systems, moving data between systems, aggregating and transforming data in accordance with the business requirements. 

The benefits of identifying IT as your data custodians.

When I work with IT departments my clients are always really pleased about this, because it helps IT get clear requirements from the business stakeholders and agreed people to go and talk to about making decisions about the handling of data. 

So, if they have a data owner within the business the data custodian (IT) can talk to them and ask them what they want, rather than second guessing and asking the only person in the business they know of that might happen to know something about the data set. 

This is a really good way of starting to break down some silos and starting to get the business to understand what happens to the data when it is on systems. This isn’t anything new either. IT have previously done all this stuff, it’s just that they’ve done it without the input from the business that they should have had. 

Having a data governance framework in place and identifying IT as the data custodians is a really good way of starting to improve the communication between departments and making consistent, holistic decisions about the data. 

One last thing

The final point on data custodianship, which I feel is important to mention, is that generally when we assign data governance roles (i.e. data owner, data steward), we always try to have a named person. However, this is not the case with a data custodian, in fact, the opposite is true.

I would say the whole of your IT department are your data custodians, because within your IT department you will have many different areas of expertise or disciplines. No single person will know absolutely everything about that system - but collectively they have the know-how.

Don't forget if you have any questions you’d like covered in future videos or blogs please email me - questions@nicolaaskham.com.

Or you’d like to know more about how I can help you and your organisation then please book a call using the button below.

How do I get a career in data governance?

Most people do not get into data governance deliberately, I certainly did not. It often happens by accident. You are involved in some related work and you suddenly have this realisation about how beneficial data governance actually is. People then tend to choose to stay into that pool, but what if you are not doing this sort of work at the moment, and you want to get into data governance?

You need some experience

If you are applying for a data governance manager or lead role then most employers will be expecting you to have some relevant data governance experience, but it is ok if you don't have any. What you do need is some relevant skills that you can bring to the table which will naturally make you a good candidate for a role in data governance, and then other relevant, if not direct, experience. For example, if you have been a project manager or a business analyst in the past then you will have transferable skills you can bring to data governance.

I have seen people come from a change management background, or even from IT. I have seen people very successfully come from IT roles like reporting, analytics and data architecture, because they really enjoy working with data, but they want to get more involved with the ‘people’ side of things and therefore they have successfully transitioned to data governance.

If you are also not working in any of those areas at the moment, then I would really encourage you to try and get some experience in data governance by volunteering to work in projects already ongoing in your organisation. I always say that this is the best way to get your very first data governance role. It is always easier to try and do something in your existing organisation and try to use what you already know to get some relevant experience before you start looking elsewhere for purely data governance roles.

Network, network, network

As well as getting relevant experience, you should also consider joining a professional organisation. To be completely transparent, I'm on the committee of DAMA UK, which is the UK chapter of The Data Management Association. Therefore, I am obviously going to recommend that you join your local chapter, but not just because I am on the Board but because I genuinely believe that there are really good opportunities for learning and education that will help you to get some the skills that you will need to do the job.

DAMA UK also has a mentoring scheme for its members. That means if you want to get into data governance, they will pair you with a mentor who will be able to advise you and help you. Along with that there are also the networking benefits of belonging to a professional organisation. They will hold events; have webinars and you will start getting to hear a lot more about the topic.

‘It’s not what you know, it’s who you know’

Along with networking as part of a professional organisation, I would also recommend joining any other networking groups and events that you can. This means you get to meet, hear and talk to other data governance professionals. For example, last year I set up a Data Governance Meet Up group with a couple of data governance friends and within the group we have people with all sorts of different levels of experience. We get together to talk about a data governance topic once every couple of months and we share experiences, examples and people help each other. Quite often the conversation turns to ‘oh, I'm recruiting at the moment - does anybody know anybody’ and somebody within the group will then apply.

There is that old adage that ‘it’s not what you know, it’s who you know’ and this is very, very true, especially if you are relatively inexperienced in Data Governance at the moment. You are much more likely to get hired by somebody who has already seen you and knows that you are really keen on the topic than somebody you just randomly send a CV to.

And if you are looking for Data Governance Analyst jobs, you can check them here.

Don't forget if you have any questions you’d like covered in future videos or blogs please email me - questions@nicolaaskham.com.

Or you’d like to know more about how I can help you and your organisation then please book a call using the button below.

Do Data Governance Initiatives Age Out?

It’s very rare that I’m able to give a definite answer to a Data Governance question, more often than not my answer is: it depends. So many aspects of Data Governance are nuanced and depend very much on your organisation's objectives and what you hope to get out of implementing Data Governance.  However, this is not one of those times.

You will have heard me say many times that Data Governance takes a long time and you've probably experienced this for yourself. And therefore, I suppose it is reasonable that you will be asking yourself ‘will I ever get to the end of this data governance initiative?’ 

Now, this may not be the answer you are looking for, but I can tell you from my many years’ experience… I'm not sure you ever get to the end. They should never age out.

If you've ever watched any of my videos or read any of my other blogs, then you'll know that I'm a huge advocate of doing Data Governance iteratively. You cannot put Data Governance in place over all the data in your organisation to the same extent, at the same time. The only way to do it successfully is to do it incrementally. That means it is going to take you a long time and you are going to be focusing on one particular domain or function or system at a time. It is going to take you quite some time to work your way across the whole organisation.

I think it's only fair to assume that during that time your organisation will evolve and change - it's what happens. You need to be constantly reviewing your organisation, reviewing your corporate strategy, and checking the Data Governance framework you have now is fit for purpose. If your organisation is changing around you, it would be wrong to assume that your Data Governance framework didn't need to adapt and evolve to keep up with that.

So, in my opinion, no. I don't think Data Governance initiatives do age out. I do think it would be wonderful to get to the stage where it is so embedded into the business that people think about their data and question it and do the right things with it. But, in my opinion, we're probably a long way away from that.

Even if you do achieve that utopian goal of truly embedded Data Governance, I still think that you will always need some central Data Governance support, making sure that principles never get forgotten.

There will always be some change that needs to be taken into account. The one thing that anybody who has done any of my training courses will know is that I am very clear that Data Governance is not a project. Data Governance doesn't go away. It doesn't stop.

If you’d like to know more about how I can help you and your organisation then please book a call using the button below.

What is Data Ownership?

We are going back to basics in this blog with a simple question that I’ve been asked quite a lot recently, and that is: ‘What is Data Ownership?’

Now, I think the reason this question is popping up a lot more frequently at the moment is that people are confused. They think that data ownership and data governance are different disciplines and that there are different things you have to do for both. This causes problems when trying to work out how to do either data ownership or data governance. However, we must have a good understanding of both concepts in order to effectively implement our Data Governance initiatives.

If we go back to the real basics of what a Data Governance framework is made up of, then we need to think about a few different things. First of all, we need a policy that tells you what you're going to have to do to implement your Data Governance Framework. Then, you will need some processes so everybody does the same thing consistently and - most importantly of all - you will need to decide and agree on roles and responsibilities.

This is one of the most important aspects of implementing a Data Governance initiative, because if we don't agree on who is going to do something then it may never get done. Even if everybody agrees it is a really good idea, if someone doesn’t take responsibility for getting it done you may find yourself in a situation where everyone passes the buck because they thought someone else was going to do it. For example, if you say to somebody, ‘we should have better quality data for our organisation’, you're going to be hard-pressed to find somebody who says, ‘no, that's a stupid idea’. However, everybody will think that somebody else will do the job. And let’s not forget, if your job title has anything to do with data, data governance, or data quality in it, they're going to think you will be doing everything!

No one person in an organisation can understand everything about the data and manage it accordingly. So, we need to get business users involved. One of the key roles in a data governance framework is that of the Data Owner, and hence the term data ownership, because you're not going to have one person owning all your data. As we’ve just laid out, you're going to have several people (but not too many). Otherwise, you'll have problems there too.

So, you're going to have to have a small number of people - maybe between 15 and 20 - who own all the data in your organisation, and they're going to be accountable for the quality of that data. When people talk about the concept of data ownership, they really mean just this key role in the data governance framework. They're not the only roles in a data governance framework, but they are the senior people who are going to make your data governance framework work.

In short, don’t get confused about data ownership. And also, don't get uptight if your organisation doesn't like the term ‘data owner’ or ‘data ownership’ - call them what you like, whatever will make it resonate and fit for your organisation!

If you’d like to know more about how I can help you and your organisation then please book a call using the button below.

How Does a Mastermind Work?

You might have heard the words ‘mastermind’ being thrown around a lot (especially by me!) and thought, what’s that?

In the realm of personal and professional development, there exists a potent yet often underestimated tool: the mastermind.

Originating from the mind of Napoleon Hill in his seminal work "Think and Grow Rich," masterminds have since become a cornerstone of success for countless individuals across various fields.

But what exactly is a mastermind, and how does it work its magic? Let's delve into the mechanics and benefits.

What’s a mastermind?

At its core, a mastermind is a gathering of individuals who come together regularly to support each other's growth and success. These groups typically consist of like-minded individuals with diverse skills, experiences, and perspectives. The premise is simple yet invaluable: by pooling their collective knowledge, resources, and energy, members of the group can achieve far more together than they could on their own.

What are the mechanics of a mastermind?

• Clear Objectives: A successful mastermind begins with a clear set of objectives or goals. Whether it's personal development, career advancement, or business growth, members should align on what they aim to achieve collectively.

• Open Dialogue: Central to the effectiveness of a mastermind is open and honest communication. Members are encouraged to share their successes, failures, aspirations, and concerns without fear of judgment. This environment of trust fosters deep connections and facilitates meaningful collaboration.

• Collective Brainstorming: One of the most powerful aspects of a mastermind is the collective brainstorming sessions. When faced with a challenge or opportunity, members can tap into the diverse perspectives of the group to generate innovative solutions and strategies.

• Accountability: Accountability is key to driving progress within a mastermind. Members hold each other to high standards and provide support and encouragement to stay on track toward their goals. This mutual accountability fosters a sense of responsibility and commitment among the members.

What are the benefits of joining a mastermind?

1. Access to Diverse Perspectives: In a mastermind, members benefit from the collective wisdom and experience of their peers. This diverse range of perspectives can spark new ideas, challenge assumptions, and broaden horizons.

2. Support and Encouragement: Building success in any field can be a lonely journey, but it doesn't have to be. In a mastermind, members find a supportive community of like-minded individuals who cheer each other on, celebrate victories, and provide solace during setbacks.

3. Personal Growth: Through reflection, feedback, and accountability, members of a mastermind experience profound personal growth. Whether it's overcoming limiting beliefs, honing leadership skills, or expanding one's comfort zone, the journey of self-improvement is accelerated within the nurturing environment of a mastermind.

4. Networking Opportunities: Masterminds often serve as grounds for networking and collaboration. Members have the chance to forge meaningful connections, explore synergies, and even form partnerships that can propel their careers or businesses to new heights.

A study by the American Society of Training and Development found that people have a 65% chance of achieving their goals when they commit to another person. This number increases to 95% when there’s regular communication with an accountability partner to discuss progress being made. For this reason, mastermind groups are a great way of ensuring you reach the goals you set. (as cited in Leaders).

How to join a mastermind?

Navigating the realm of Data Governance often feels like being stranded on a desert island, isolated amidst the vast sea of data challenges. That's precisely why I run my very own 1 Day Data Governance Mastermind. 

Throughout the day, we foster a dynamic environment of networking and mutual support, where every participant has the opportunity to both seek and offer guidance. Each individual takes centre stage in the "hot seat," sharing their unique challenges and experiences while receiving valuable feedback and solutions from the collective wisdom of the group.

We also always kick off the day with a guest speaker who delivers a talk on an interesting and relevant topic and a live Q&A. 

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I only allow a small number of attendees for my 1 Day Data Governance Mastermind and it typically fills up fast so I do have a waitlist approach. Please sign up to the waitlist and then you will be the first to know when bookings are open.

You can also use my FREE scorecard to find out whether joining a mastermind is right for you.

Data Governance Interview with Kohinoor Mukherjee

Kohinoor Mukherjee started his career as a mainframe developer before moving onto business analysis, project and then program management. Kohinoor has been working on various data specific projects, mainly with financial institutions, for the last decade, and is now presently a Data Governance Consultant with an energy company.

Apart from data, he is also an avid reader with a keen interest in financial risk management, behavioural science, history and public speaking.

How long have you been working in Data Governance?

I have been working solely in Data Governance initiatives for the last 3 years. Prior to that, I was primarily involved in Data Quality and Reference & Master Data Management. However, with every passing day I am intrigued and fascinated by the interdependence of these disciplines and how they enrich each other.

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

Probably 5-7 years back it was unusual but not anymore. With the tremendous growth of different Data Management disciplines, Data Governance is becoming increasingly relevant. I think it’s a key factor, which integrates the different data management streams, resulting in a synergy for the organization. 

My entry into Data Governance was to some extent situation driven and not by choice. While working on a data quality initiative with a bank for a regulatory program, we found that our DQ deliverables were lacking context and failed to rollup to the overall objective of the program; and the missing link was inadequate Data Governance. That’s when I got involved with this topic and eventually found it to be quite interesting.

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

a.    Resilience is a must have quality for anyone in this field, as that will be frequently tested during any Data Governance rollout.

b.    Ability to see the bigger picture and finding the intersections with other data management areas helps immensely.

c.     Having good articulation and negotiation skills are also highly desirable traits to get things moving and create an impact.

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

I regularly subscribe to the DAMA and DCAM contents (papers, webinars etc.) to remain updated. LinkedIn forums on similar topics are also enriching. Anyone new in Data Governance can consider having formal training. I took the 2-day training course offered by Nicola and found that quite good.

I found that knowledge on change management techniques and tools come quite handy in Data Governance implementation. So, it would be good to have some exposure in that area.

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

Challenges are different depending on the industry and their maturity in data disciplines. I will talk about two of them: In one assignment with a financial institution, I found weak data leadership coupled with organizational politics that rendered major data initiatives less effective. In another organization, which was new to Data Governance, getting senior management buy-in and convincing them about the business value of data governance was a big challenge. Without the blessings and active support from senior management, implementing data governance is almost impossible.

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

I would love to do Data Governance for organizations where data is not a byproduct of its business processes but the product itself. For example, the financial data vendor companies. And the reason being that probably I don’t have to spend days and months convincing the decisions makers and budget approvers, the importance and value of data governance before getting into the real work.

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

It is of course important to have a sound framework and operating model but don’t wait for them to be perfect before you start. Start implementation sooner and they will evolve and get better. Most of the time we can’t envisage the practical problems lying ahead. So, let them come and make the necessary changes to your op model and framework etc.

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

I am still looking for that humorous side of Data Governance. Every discussion and meeting on this topic get so serious at times that it won’t be a bad idea to introduce a ‘Joke of this quarter’ slide in the SteerCos. Jokes apart, I don’t have any one memorable event to share. Rather, almost every interaction with so many different stakeholders have been enriching in different ways and has helped me to develop both personally and professionally.

Data Governance on a ‘shoestring’ budget

Data Governance on a ‘shoestring’ budget - yes, it’s possible

Demand for data governance is increasing as the result of Coronavirus, and at a time where resources are scarce. There’s a huge focus on data because people want to be sure what they have is of good enough quality to make decisions about the future of their business and its survival.

However, at the same time demand’s going up, budgets are being cut. People are not spending money on data governance but, they want more of it! So, we've got this conundrum. If we're going to deliver data governance, it has to deliver some benefits. There's no point doing it for just the fun of it but how are you going to do that if you've got little or no budget? We need to deliver data governance of a shoestring budget.

So, the question I asked myself is what can we really do that's useful on that basis? Well, after 17 years in data governance I've learned that, practically, you can’t do data governance over everything and that it's also not useful to as all data is not of the same value to your organisation. We always need to consider carefully where we put our Data Governance focus on and now, more so than ever we need to be pragmatic - that’s where ‘minimal data governance’ comes in.

But what does this really mean in practice?

Well, it’s not the bare minimum to keep your regulator happy. It is not ‘just enough’ so you can say you are doing it. Minimal data governance has to deliver real value. If it doesn't, there's absolutely no point in doing it.  

But just because it's minimal it doesn't mean it's going to take less time. Data Governance takes a long time and I'm afraid the bad news is that minimal data governance also takes a long time.

Apart from anything else, you won’t get any value from it by trying to do it quickly because you won't do it properly. And therefore, you won't get the value.

So, can minimal data governance be effective?

Yes, I think it can, because I think it's probably the way I've been increasingly approaching Data Governance over recent years.  What I'm encouraging you to do is to be even more pragmatic and focused than I usually am, but I think if you do that, you should be able to deliver something on an inadequate budget that can deliver some real value to your organisation.

And, the secret to ‘minimal data governance’ is to identify one priority benefit because if you get Data Governance in place to deliver that correctly, some of the other benefits will start coming through anyway, and you'll be in a good position to then focus on delivering more of them. Benefits can include:

Improved efficiency/reduced costs

• Accurate reporting

• Facilitating compliance with regulation.

• Protects your reputation with customers and suppliers.

• Supporting your corporate strategy

• Supporting innovation i.e. AI

Once you’ve focussed on what you want to get out of your minimal approach, you will need to define your scope - are we dealing with customer data, finance data or a subset of one of these categories? Really take this opportunity to identify a very limited scope. I think the best way of thinking about it is of doing data governance incrementally. What we're doing is our first phase is just going to be very tightly defined. Then when we deliver that, we'll be in a good place to roll it out further.

So, to be truly effective, you need to bear three things in mind:

• Be very focused on your scope - you know you should never be doing Data Governance over everything, but right now, let's have a really narrow scope and focus on just know one thing.

• Do it properly - minimal Data Governance doesn't mean ‘let's just do it quick and dirty’. Do it properly - just with a very limited scope.

• Do it in a way that is planning for the future - do it to deliver some very focused benefits now, but in a way that that framework can be evolved and implemented across the organisation in the future. Make sure it's going to deliver some benefits now, but you that can scale it - because you don't want to have to revisit this and do this again.

If you want some more detailed actions on what to do when you are starting Data Governance please download this free high-level checklist.

Data Governance Interview with James Shaw

James Shaw is a Data Governance, Protection and Management professional with experience in managing data risks and assisting data transformations. He is the Data Risk Lead at esure Group.

How long have you been working in Data Governance?

I started work in Data Governance specially about 4/5 years ago, but have broader Data Management experience prior in Data Analytics and MI. Drawing on my Data Governance experience, more recently I have moved into Data Risk Management which concerns second line oversight of key risks to Data including those relating to Data Governance, Protection and Management.

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

Like a lot of fellow Data Governance, Management or Protection professionals, I started in Data analysis and reporting where I learned how to interpret and utilise data, as well as the need to manage data effectively. Through Data Analyst roles I developed a keen interest in data risk and data management specifically, and also searched for a role that was more people focused. I believe Data Governance/Management/Protection is for people who love Data, but also love people and cultural/structural change. Thankfully I was lucky enough to start my Data Governance career under Nicola Askham herself and consider myself fortunate to have had that introduction in an industry that is very young in experience.

 That Data Governance is considered ‘unusual’ is a common (and somewhat justified) view I agree, but I don’t think Data Governance as a corporate function should be as niche or unusual as it’s widely perceived. The governance and management of Data is not just desirable but essential to maintain control and discipline over any organisation just as we do with People or Systems.

If that is perceived as unusual then it is perhaps a sign that Data Governance has sometimes been boxed in as a regulatory specialism (particularly in Banking, Insurance and other highly regulated industries), or narrowly defined as data quality deficiency meditation.

 I would like to think that actually logically, the overall governance and management of Data should eventually be given as established a platform as the governance of IT assets or similar. The emergence of the Chief Data Officer and similar functions suggests that Data Governance is establishing itself in organisational Leadership and strategy plans.

How do you see Data Governance evolving over the next 5 years?

As mentioned above, I envisage the management of Data will become a high level function in it’s own right and no longer an oddity or ‘in trend’! If Data Governance/Management/Protection professionals can frame themselves in the right way, that is as persons in some capacity responsible for ensuring the integrity, availability, security, protection, ownership and understanding of organisational data, then they will be perfectly placed to deal with emerging and residual data risk, as well as supporting data transformations that seems to commonly underpin corporate strategy. If Data Governance is able to embrace this challenge, and not shrink to tick boxing or specifics in complex data regulations, then there will be an accelerating demand for professionals who can demonstrate this experience. Every year we see an increase in Data Governance/Management/Protection professionals and this of course solidifies the position of the function in its own right.

 I also expect Data Governance to develop beyond its focus on Data Quality and apply more equal weight to all aspects of data management, which will also blur the lines between the different factions of data responsibilities. For example, I imagine Data Governance working more closely with Information/Cyber Security, Data Engineering, Data Privacy professionals etc. to deliver common objectives. Which is not a bad thing! Finally, as Data Governance branches out, I would hope to see the expansion of principles embedded in Solvency II and similar quality regulations to other and all types of data, as I believe the principle that data should be accurate, complete and appropriate to be fairly universal. As too are the principles of Data Protection, in terms of understanding, protecting and using data for the right reasons, I don’t think these principles should only apply to personal data. The regulations can, potentially, establish universal principles and ethics as intended.

What are the biggest risks and threats to organisational Data right now?

Other than large scale cyber breaches and hacking incidents, which is not the domain of Data Governance, the biggest risks perhaps lie in the volume of data that is being accumulated and an organisations’ ability to control and manage it. Data volumes and input is being ramped up and the investment in Data Governance is not always keeping pace. When that data is sensitive, confidential or personal, the risks are multiplied. Challenging the assumption that more data is always better is a huge test for Data Governance because the corporate giants of today’s world and those perceived to be at the top of the pyramid consume data on a vast scale. The important point here though is that they are able to apply the equivalent resources to control and manage their data so it becomes a benefit and not a hinderance. Organisations have to be able to understand, catalog, control, and manage their data effectively otherwise it becomes polluted and uncontainable, aka. the dreaded data swamp. It should be understood that the potential consequence (other than the increased regulatory risk) of plugging in data that is not really needed, is that the data that is genuinely needed can be diluted, contaminated and harder to find. I would advocate smaller volumes of quality data that is understood, useful and manageable rather than drowning your systems in data.

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

I would say that building data related experience is a priority, but as too is developing soft people focused skills. Data Governance is about effecting organisational management and change. So whereas a MI analyst for example may be used to delivering independently, a data governance specialist needs to be effective in driving co-operation and initiatives with the wider business. Sometimes getting other people to do things can be harder than doing it yourself! I would recommend developing yourself as a rounded individual, with a balanced set of skills. Unlike some in the industry, that while useful, I would not recommend focus necessarily on developing technical computer language skills as a priority nor would I think necessary to become an evangelical in people persuasion.

 Two of the most important skills I would empathise are patience and tenacity. You have to be able to keep going until you deliver results and be creative as to achieving that – Data Governance is never going to be easy to achieve and instant results are rare.