At what level should Data Owners and Data Stewards be?

In previous blogs we’ve discussed what Data Owners and Data Stewards are and during those discussions, I’ve given you hints as to what level of seniority within your organisation these people should be, but in this article, we’re going to address it directly.

First of all, to refresh your memory, data owners are a small number of people within your organisation (maybe between 15 and 20) who own all the data in your organisation and are accountable for the quality of that data.

Data stewards on the other hand are chosen by the data owners, who delegate the day-to-day responsibility of the data to the data stewards. In my experience data stewards often tend to be the subject matter experts.

So, where do these two roles sit within the structure of an organisation?

Data Owners

I always say that data owners have to be suitably senior people. That generally means that they have to have appropriate authority and budget to be a data owner to be able to make the decisions and fund any changes needed.

Let’s look at an example of a finance department because it doesn't matter what sector you work in; your organisation will have a finance department. And most finance departments are headed up by a finance director. If you follow my logic of having a really senior person being a data owner, then you might come to the conclusion that the finance director is going to be the best person for the role. And they may well be, but what I would encourage you to do is think very practically about this.

Is this going to work in practice? In my experience, for the vast majority of my clients, the finance director has just been a bit too senior.

They might well understand data governance and support it if you could find the time to talk to them, but I think that's going to be your problem, they're just not going to have the time to support you and to take on this role.

I have seen it work very successfully at that level, but only in a very small number of organisations which have either been very flat in hierarchical terms, or very small organisations.

So, if I'm saying maybe not the finance director, we need to find somebody still who is suitably senior, and I've seen it work very well with the Deputy Finance Director or maybe even the level below that, but they've got to be somebody that's got that overarching view across all the finance data but who also has the authority to make decisions about that data.

Data Stewards

It’s not quite as easy to identify what seniority your data stewards should have, but actually in this can also make it easier to identify your data stewards because you don't have to decide what level they should be. This is down to the data owner.

Your job when implementing Data Governance is to identify who the data owners are and engage them and get them to sign up to be the data owners. Once you've done that, it is their job to nominate their data stewards. And to make their own role ultimately easier, they're going to want to nominate people who actually do understand the data and who they trust.

If we look again at the finance example, I would expect the Deputy Finance Director to choose a number of data stewards. Now, in my experience, most finance departments have multiple teams, each working in their own their own area of specialisation and what usually happens is the data owner will appoint the heads of each of those teams to be the data stewards for each of those subject matter areas or those subsets of finance data. And that works really well.

Some advice

I would say to leave it to the data owner to appoint the data stewards because if you've explained well enough what they're accountable for and their responsibilities, they will nominate and choose the right people who have the right knowledge and authority to be able to do that on their behalf.

Also, don’t be too worried if your data stewards are not all at the same level or grade within your organisation. This isn't a problem. What's more important is that the right person is chosen so you might find that the data owner chooses four people that all head up their own teams and then they choose one other person who's a little bit more junior.

This could be because they are the subject matter expert and the only subject matter expert in some very specific data. So, always consider that and don't argue back immediately. Try and find out why they chosen the different levels and you will usually find that there's a very practical reason that they are the right person for the role.

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.

What is a Data Domain?

This is a very short and succinct question, and I thought the answer was likely to be the same. However, when I was sent this question, I was very surprised to see that it was a former colleague from my very first consultancy who submitted it!

I was taken aback at first because I thought to myself ‘surely, they would know the answer to this?!’ but on reflection I realised this is yet another example of how we data professionals are actually very bad at defining things and as data governance professionals,

that's even worse because we spend our time helping others and asking others to write definitions for their data and yet we so often don't define the terms we use well enough for others to understand. 

So, I decided that this was actually an excellent question and was definitely one that I should answer.

The first thing I did was look at one of my most commonly used reference books, the DAMA Dictionary of Data Management. This is an excellent reference book for anyone in data governance and as a DAMA member I would highly recommend it. However, on this occasion, it did take me aback…

I opened the page at Data Domain and was quite surprised at the definition it gave. It states that ‘a data domain is a set of allowable values for a data attribute’. However, that is not how I use the term and I think that is the perfect example of what happens as data professionals. We start using a term and people we work with start using it, it proliferates, but we're not necessarily using it for its original intention.

While a data domain is perhaps terminology more commonly used in data modelling and in databases, we use it a lot in the data governance world, but in my view, with a slightly different meaning. We clearly don't mean ‘a set of allowable values for a data attribute’ -that's very techy and data geeky and not at all the type of langue we would want to use when we're trying to talk to business users. So, what do we mean?

Well, when I use the term, I mean a logical grouping of data - something where we can tell where it starts, and it ends. From my point of view, I'm normally trying to find identify data domains so that I can identify data owners.

For example, you might call customer data a data domain. Or finance data, HR data, product data, supplier data. These are all ideas of logical groupings of data that all relate together.

It's then the work of data governance to work out the details of what is actually included in those domains… but that is what I, and many professionals that I work with, mean when we say, ‘data domain’.

Sometimes I don't use the word data domain. I talk in terms of ‘data set’, which is any logical grouping of data and I think you can use the words ‘data set’ and ‘data domain’ interchangeably. Just make sure that you actually understand what you mean when you use the term and explain to the business users that you're talking to what it means to avoid all confusion.

So, there you have it. That’s my definition of a data domain. I hope you find it useful. If you do, please help me on my mission to help as many people as possible be successful with data governance by sharing it on your choice of social media.

I really appreciate your help in getting the message out.

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.

Data Governance Interview With Andy Lunt

My name is Andy Lunt and I’ve been working in the field of data for the last 10+ years previously for Adecco Group and more recently Carruthers & Jackson.

How long have you been working in Data Governance?

I’ve been working specifically in data governance for almost 3 years now.

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

I worked as an MI/BI manager for many years and got to see the results of poor data management in the many hours spent trying to make sense of the data coming into my team – lots of troubleshooting! An opportunity to work with a newly formed data science team as a data governance manager came up and a chance to fix the causes of many of the data problems we had was one I couldn’t pass off, so I took it!

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

I would say empathy, resilience, persistence, and self-motivation are all characteristics you need.

Empathy, because if you can’t learn to walk a mile in someone’s shoes, you won’t know what is causing them pain when it comes to data. Resilience in your approach is key, there are a lot of ‘dead ends’ in data governance so being resilient allows you to keep changing until you get it right. Persistence is needed for your message about the ‘why’ people will understand the need but it takes time and persistence to really drive the message of why bother with data governance. Self-motivation, when the chips are down and you’ve had enough doors slammed in your face that your nose appears shorter you need to find ways to keep knocking – this is where your passion for the subject, your team, and your knowledge of the ‘why’ being greater than the ‘how’ all come into play.

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

I would firstly look at getting a mentor, this helped me hugely at the start and in fact helps me to this day. We don’t expect professional athletes to stay at the top of their game or even get to the top without one and in my opinion nor should we.

Some books I read:

The Jelly Effect by Andy Bounds

Verbal Judo by George J. Thomson & Jerry B. Jenkins

Telling Your Data Story by Scott Taylor

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

Business culture/people.

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

Child social care – there is just too much critical data lost, not captured, not accessible, or not understood due to poor data management practices. It breaks my heart to think children suffer as a consequence especially as it’s within our power to change.

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

Stay positive and be the change.

Finally, I wondered if you could share a memorable data governance experience?

I once spent 30 minutes trying to work out why a full stop had gotten into a field where the data quality rule didn’t allow it…turned out to be a spec of dirt on my screen - I took a long hard look at myself in the mirror that night!

I purchased a cheap keyboard from Amazon which added an extra space in between words randomly – it was a true data governance hater! The words ‘you buy cheap, you buy twice’ were ringing in my head when the new (much better quality) keyboard turned up!

The Rocky Horror Data Show: Disastrous duplicates…

Data shouldn’t be a wild and untamed thing, but sometimes it is just that - wild… and untamed. And unfortunately for our friend Tim, he’s about to find out just how wild and untamed data can be. As this is ‘The Rocky Data Horror Show’… where the data is not what it seems.

If you missed the previous episodes, you can read them here:

The Rocky Horror Data Show - where the data is not what it seems

The Rocky Horror Data Show: Did you get what you asked for?

The Rocky Horror Data Show: Not everyone’s on board…

The Rocky Horror Data Show: Disastrous data definitions…

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Fresh from developing their data glossary, there’s been a worrying development in The Magical Wish Factory. And it has left Tim and Janet quite perplexed. Over the last couple of weeks, it has become apparent that some subscribers of The Magical Wish Factory have been getting more than their monthly quota of wishes.

Tim and Janet have been investigating the issue – which has cost the MWF hundreds of wishes and a lot of profit so far – and have discovered that a data input error has resulted in several customers having duplicate records on the system, and therefore getting double or sometimes three time more than their quota of wishes.

“This is a disaster” wailed Janet, “This has cost us so much money and there’s so many wasted wishes!”

“It’s not great” conceded Tim, “but that’s why you brought me in all these months ago, because the Data Governance here isn’t where it needs to be… and I’m sure we can get is all sorted out!”

“We need to get the data cleaned as soon as possible and these duplicate records deleted!” stated Janet, quite firmly.

“Yes, the data does need cleaned, and the duplicate records need condensed and removed… but if we clean the data without addressing the source of the issue, then we’re going to end up in this mess again in a few months – and that’s quite counterproductive, Janet,” said Tim.

“Okay – so what do you suggest then?” asked Janet sceptically.

Tim explained to Janet that the Magical Wish Factory needs to get out the habit of constantly fighting fires and get to the source of ignition and deal with that. Yes, the data could just be cleaned and fixed at the point of use, but it is fundamentally the wrong place to start.

Tim says: “If we clean and fix the data but don’t address why it is wrong and figure out why it is happening in the first place it will be clean for a day or two and then immediately start to deteriorate again.”

“I found a person in my old job who used to spend three weeks manually fixing role codes in their HR system every six months. It became a regular process to fix it because they never fixed the source of the issue, think about all that time wasted!”

Tim went on to explain further that the Magical Wish Factory needs to continue to press ahead with its Data Governance initiative first as that will ensure that you look at things strategically instead of a mentality of fixing things tactically all the time.

Tim also explained that they needed to establish a master of all wish makers and that Data Governance would help them identify and fix the source of the issue, not just the resulting data at the time you use it!

“Ah, that makes a lot of sense…” said Janet.

“Yes, Data Governance first and foremost always… that’s my wish!” replied Tim.

Stay tuned for episode six of The Data Governance Coach’s new series ‘The Rocky Horror Data Show’ and follow the adventures of Tim and Janet as they try to implement a successful data governance initiative at the Magical Wish Factory.

And if you want to chat about your Data Governance Training requirements, why not book a call by using the button below?

Do I really need data governance when I'm doing Master Data Management?

This is a question that I have been asked many times over the years and my answer is always an unequivocal “yes”! Of course that is always followed up with the question “why”? And that one is a little harder to answer…

You can easily Google and find plenty of people that will tell you straight that you need Data Governance for Master Data Management but what they won’t tell you is why. I can understand why that might be the case and I struggled myself for many years trying to describe the relationship between the two until somebody challenged me to come up with an analogy. What I came up was a comparison to how we treat our own physical health.

Value your health = Value your data

If we are really healthy people, and we eat loads of fruit and vegetables and healthy whole foods, and everything we put in or consume is of really good quality and dense in nutrients, we are going to function really well, we are going to be at the top of our performance, we're going to be in a great shape.

However, if we start consuming only crisps and snacks, sweets, fizzy drinks and food with little to no nutritional value over time we are going to start getting sluggish and tired; we're going to start getting some aches and pains and perhaps some weird and wonderful symptoms that we've never experienced before, and that doctors can't quite put their finger on. The same is true if you do master data management without Data Governance.

Consider your Master Data Management repository is the human body… if you put good, clean, healthy data into it then it's going to work really well. You are going to have the right data in the right place, the right processes will work, you will make the right decisions on the data.

However, if you feed your system with rubbish, with poor quality data or missing data parts, or perhaps the wrong data in the field then you're going to start having things go wrong. Processes fall over and you are going to upset customers or suppliers. Production lines might have to stop because you don't have the right information or the right parts. Things will start to go wrong and unravel pretty quickly.

You may be thinking that seems a little dramatic but that is based on real life experience, and I have three scenarios that I have really genuinely seen happen as a result of people trying to Master Data Management without Data Governance in place.

Scenario One

In these instances, the data migration onto your new Master Data Management solution has gone well. You've had a team of analysts on their project who have worked hard to map the data, to migrate it, to make sure it was good enough quality to go into your new system. All goes well; you have a successful go live, everything is looking really good. But what I can tell you in these circumstances, if you haven't put in place data governance to protect and proactively manage that data, over time it starts going wrong.

People will start using fields for slightly different things, or people want to change things but there's no process for agreeing to do that, and so perhaps things can't get changed and users get frustrated. Or perhaps things do get changed, because you just ask the friendly person in IT and they agree with you and change it, but you cause problems for other people because neither of you understood the downstream impact of making that change. And slowly but surely, over time, without Data Governance in place your MDM solution becomes poor quality, and I can promise you, your users will start complaining about it.

Scenario Two

The second scenario I have seen is where the data migration to begin with never even happens. It fails and you fall at that first hurdle. In this scenario, there usually hasn’t been enough engagement with business users and the business hasn’t done enough analysis, or any data quality assessment.

That means we don’t even get to your successful go live that I was describing in the first scenario. In this situation, you can't even get your data to go successfully into the Master Data Management solution.

Now, in one real life instance where I came across this, it actually was the weekend before the ‘go live’ when they had a dress rehearsal for the data migration and they found so many issues with the data either not being mapped correctly, or it was too poor quality to actually go into the target system, that they actually abandoned it and the whole programme was put on hold with only one week to ‘go live’.

If you're in the middle of a Master Data Management Programme at the moment, you know as well as I do these are not cheap programmes, and this whole programme was put on hold for 18 months before they managed to get the business case approved to restart it. They had invested a lot of time and effort and significant amounts of money, and it nearly all got wasted! And of course they had all the additional costs of the rework needed to fix the data.

Scenario Three

In this scenario, the data is not quite as bad as in the second scenario so we can actually get it into the Master Data Management solution. It has some niggles and some problems, but surely it will alright?! I like to describe this as shoehorning the data into your new MDM system. We just keep pushing and pushing the data until it will eventually load into our new Master Data Management system. The attitude is that once it's in there, the business can fix it and it doesn’t need to be done as part of the project.

Well, the business won't fix it because they'll be too busy telling you how rubbish your new system is, because not only have you got the poor-quality data from the old systems in it, but you've probably made it worse by shoving it into a system that's set up and structured differently.

I even came across one instance where I was told that they had to turn off the relational integrity of the database of the new MDM solution, because the data was so poor that it would break the system and it wouldn't run if they didn't!

These scenarios are the realities of the type of scenarios that you are likely to face if you try and do a Master Data Management Programme without Data Governance. The first one is your best-case scenario; that you do a good job to begin with, and then it's a few years down the line before you start having major problems, but you start having niggly problems quite soon on. Scenarios two and three are quite catastrophic, and you really don't want to face them.

The Business Case

So why doesn't everybody just implement Data Governance at the same time as Master Data Management? Well, it usually comes done to issues making the business case for it and often a desire within the business for things to go quicker, or just a poor understanding within the business about the importance of Data Governance.

But the answer to that is simple: if you do Master Data Management with Data Governance, what you're going to actually have is the right people from the business involved in agreeing which data is going to go into your Master Data Management solution, what the fields really mean, and by agreeing which fields are the right ones to match and merge and you're going to have data quality rules agreed.

Therefore, you can actually measure the data and improve it both before the migration into the system, and afterwards. And you'll be laying the framework, the foundations for a successful data migration, and therefore a successful starting place for your master data management solution. I really, really believe that master data management and data governance are better together.

That’s great, but where do I start?

Start with identifying the data domains which are in scope of your MDM solution. It could be customer data, product data orsupplier data, but identify those domains.

Agree who's going to support Data Governance and MDM, because you want to agree who is going to support the master data system once it's gone live and you also need to agree who is going to support data governance - it will possibly be the same team.

Go back to your data domains where you have worked out of what is in scope of your Master Data Management solution and agree data owners. And then work with those data owners to create some definitions for the data and some data quality rules, and you'll be giving yourself a really good start for your MDM initiative.

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.

What the Data and Tech Industries Are Doing to Support Ukraine

Like people and industries across the world people in data nd tech are doing everything they can to help the people of Ukraine as they face some of the worst of humanity. D.A.T.A was born out of a feeling of helplessness, and we have a very clear mission. We are mobilising the data, analytics, and technology communities to come together and raise money to help Ukrainian citizens.

We truly believe that together we can achieve more and have set ourselves the ambitious target of buying 10,000 medical kits, worth $1million in just six weeks.

So, how did this all come together? Well, we all watched on in horror as the most unthinkable unfolded in front of our eyes. On the 22nd of February 2022, when Russia invaded Ukraine, I felt shocked and powerless. Since that day I have found it difficult to watch the news as it only increased my feelings of helplessness.
I didn't know what I could do to help – but I knew that I wanted to. But what could I do by myself? So, despite feeling awful, I continued living my life, as many of us have, checking the news, shaking my head in disbelief as to what was unfolding.

Then, three weeks later, on the 17th of March to be exact, I got a message from Rob Howes. He too had been feeling the same feelings of helplessness and had come up with a plan to take action – not just on his own but with the collective data industry.

He told me how he wanted to harness the wonderful community of Data and Tech people to collectively act and do something meaningful to help to people of Ukraine and then asked if I wanted to be part of it.

I didn’t hesitate, I didn’t have to think twice – finally this was something I could do to help, and we decided to get started straight away. We quickly put plans in motion and rearranged our schedules to have a call the very next day and the following week we had the first meeting of the founding committee...

D.A.T.A (Data and Tech Aid) was born, and I am honoured to be included in this group of inspiring people.

Roisin McCarthy (a fellow Founding Committee member) described it as finding your tribe and I think she is right.  It is amazing how a small group of people can get together and make things happen, when individually it would have been beyond us. Instead of feeling helpless and despairing, I am now energised and motivated, knowing that I am now taking actions that will help the people of Ukraine.

We all wanted to take action quickly, but it soon became clear that if we want to make a significant impact then we had to plan very carefully.  We have some exciting things up our sleeves that we will be sharing in the coming weeks, but right now the most important thing we have to focus on is saving lives in Ukraine.

After painstaking research, trying to decide where would be best to direct any funds we were able to raise, we finally settled on The Kyiv School of Economics Charitable Foundation (KSE CF). KSE was established in 2007 as a subsidiary of its non-profit corporation in the United States.

Working directly with the Government of Ukraine, other funds, and multiple volunteer organizations, KSE has established itself as one of the largest humanitarian aid foundations providing vital medicines and food to those in Ukraine.

As I said, our initial efforts are focussed on raising enough money to buy 10,000 medical kits. It has become evident that the main danger for civilians at war in Ukraine is death from blood loss caused by shrapnel wounds after the shelling. It is shocking that many people are dying from blood loss before they can get medical assistance. We must change that. Thousands of lives could be saved if bleeding is stopped quickly. 

The Ministry of Health of Ukraine has confirmed to KSE the need for up to 300,000 kits so now our priority at D.A.T.A is supplying those in need with medical kits specifically to stop blood loss.

The cost of one delivered medical kit is $100 and the cost includes the price of the first aid kit from the supplier, transportation costs to Ukraine, unexpected expenses including things like customs and possible price fluctuations. As D.A.T.A we are raising money to make a difference by coming together as the strong community we are – not to just be seen to be doing good, but actually do good! At this point in time, aid is needed now. 

Doing any of the standard fundraising type activities takes time, money and effort and we have none of those things – we are not a charity ourselves – we all have day jobs and are juggling busy lives but with this desire to do good and we are absolutely sure the rest of the data, tech and analytics community feel as strongly and passionately about this as we do.

So, if you too have been feeling helpless about the situation in Ukraine and want to do something to help, please find out more about D.A.T.A on our website.

There you will be able to donate to help save lives with the medical kits and that would be wonderful. You can also keep a real-time track of how many medical kits we have been able to donate so far.

If you are unable to make a monetary donation, there are still some things you can do to help support D.A.T.A. Perhaps you have some time that you can offer to help with the many tasks involved in running D.A.T.A.

Even just following us on social media and sharing our messages to a wider audience on would be a huge help.

I have a vision of a world where everyone understands the value of data and uses it to make a positive impact. That may take some time to achieve, but in the meantime bringing the data and tech communities together to support the people of Ukraine is the right thing to do and I do hope that you will be able to support us in some way.

Thank you.

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UPDATE Thank you to everyone who has supported D.A.T.A. so far - our initial fundraising phase has now come to an end and we are now focusing on offering Round Table events. We hope to continue making an impact by showing the value of data and how it can be used for positive change. You can find more details about our upcoming Round Tables here.

The Data Governance Clinic and how it could help you!

The Data Governance Clinic is the second, optional, day of my Getting Started in Data Governance course bit is also incredibly valuable as a standalone day if you understand the theory of Data Governance but are struggling to put it into practice.

This day is all about turning theory into practical actions and you will get the opportunity to ask detailed questions about implementing Data Governance in your organisation and receive advice on how to overcome the challenges you may be facing.

It’s a workshop format where you get the opportunity to share the challenges you are experiencing with your Data Governance initiative and get pragmatic solutions. You also get the opportunity to share knowledge, insight, and network with others in a similar situation.

I’ve been getting a lot of questions about the day recently, so thought I’d answer them all here, including what it is, who it is for and what you will get out of it.

Getting Started in Data Governance

This one-day course was born out of the very strong belief I have that there's no such thing as a standard data governance framework. But what I found over the rather many years that I've been doing data governance is that there are certain key components that you must look at and address. 

If you don't do that, your data governance framework is very unlikely to be successful and sustainable for your organisation. This course gives you all the building blocks and tools that you need, and all the areas that you need to address so that you're able to confidently design and implement your own data governance framework that's right for your organisation.

Putting theory into practice
So, what do you do with all that theory from day one? That’s where the Data Governance Clinic comes in.

This workshop is for people who understand the theory but are perhaps struggling with some of the implementation of it or are coming up against obstacles. For example, they have presented their draft framework to some senior stakeholders and received a challenging response or were asked questions that they didn't feel confident or able to answer. 

One thing I found very much in the early days of doing Data Governance is I felt very lonely and very vulnerable. Like, ‘I must be the only idiot that can't convince my work colleagues that we need to manage our data better’ but actually, it's quite common. And I see that people who come to my courses really benefit not only from hearing me share my expertise and experience but talking to other people that have been in the same situation. 

So that's where the idea of a Data Governance Clinic was born. I wanted to give people the opportunity to get together with people in very similar situations themselves, and share experiences but more importantly, get answers for their challenges. 

Who is the Data Governance Clinic for?

I find that the people who attend the data governance clinic tend to be two different groups of people.

The first the people who have done my one-day training course, either immediately the day before or sometime previously, or I've even had people who've done it online and then turned up to a face to face clinic and they're normally looking for answers along the lines of ‘you taught me this in the theory and how do I turn this into a practical solution, given my particular set of circumstances?’

And the second set of people are very much the people who know they know Data Governance and feel quite comfortable that they know what it is, but when they're actually trying to implement it and roll out their Data Governance Initiative they are coming across some challenges and some obstacles. These are the people who really just need some guidance and advice, tips and tricks, anything to try to overcome these obstacles.

If either of these groups are resonating with you then this might be the course for you.

What will I get out of it?

I absolutely love the Data Governance Clinic days. I find they are very informal, but engaging days where everybody gets to bring along their questions and challenges. We sort them into themes, and we work through everything together that we can and make sure by the end of the day we have answered answering everybody's questions and they go away with very clear actions of what to do to overcome their challenges.

Everyone who attends this course will also get a copy of the actual checklist that I use when helping clients design and implement Data Governance Frameworks. This is an incredibly helpful resource, especially if you’re just starting out in data governance. There is lots of information and resources out there, but this checklist is tried and tested and has served me well through the years - it’ll keep you right too, through all your data governance initiatives.

You will gain confidence in your own Data Governance Initiative. Let’s face it… it’s one thing thinking or hoping you’re doing the right thing - it’s another to know it! And to have the confidence to sell it to senior stakeholders.

You will also get the opportunity to meet other people who are in the same position as you and will be able to connect and workshop ideas beyond the course.

It’s a great opportunity to feel a little less alone in this big data governance world - especially if you’re brand new to it or the only person in your organisation who’s remit it is. You will also just have a really good time, I promise!

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.

What makes a good Data Governance consultant?

Over the last few weeks, I’ve been trying to come up with a list of skills that a good Data Governance consultant needs. Not necessarily an exhaustive list, but a good jumping off platform for anyone thinking about a career in this field. My goal was to keep to a manageable (and achievable) list, but it was proving challenging. I decided to open the floor to my network on LinkedIn and I wasn’t quite prepared for the tsunami of replies…

It turns out that this is a very subjective subject and if you don’t believe me, I have a 150-comment long thread to back me up!

What should be a simple list of core skills, quickly turned into a long list of wishes, someone even suggested that a good Data Governance consultant was actually a bit of a Unicorn! And if I was to list every single skill, trait or attribute suggested as part of the discussion I might be inclined to agree, because truth be told, there was even one or two suggestions that do not necessarily apply to me, as someone with years of experience in data governance.

 My own list started out like this:  

·       Communication skills (both oral and written)

·       Influencing skills

·       Listening skills

·       Creativity and innovation

·       Observation skills

·       Problem-solving and strategic planning ability

·       Analytical skills

·       Flexibility

·       Ability to cope with pressure and challenges

·       Understanding the client’s business environment

One big talking point was whether or not a good data governance consultant needs industry specific experience. One connection described it as a “top requirement”. They argued that this was different from 'understanding the client’s environment'. However, I'm not sure that it should be. As a data governance consultant, your client has a company full of people who have the relevant industry specific experience for you to draw on.

Another very interesting suggestion that popped up a few times what the ability to be a good data storyteller. Other suggestions included passion, personality, a good understanding of change management, negotiation skills, being pragmatic and logistical… and even a good sense of humour!

My own list, which I already felt was a little too long, quickly turned into a very long and quite possibly unachievable list of skills.

So, what does all this mean? Is it impossible to find a good data governance coach? Or that it’s even harder to become a good data governance coach? No! But what it does do is illustrate just how hard a data governance consultant role can be.

You face the usual challenges of doing data governance, you need to be experienced in doing data governance plus you need to have a whole host of skills to do the job. Simply, it’s not for the faint hearted!

That is why I have decided to launch the Data Governance Coach Academy for Data Governance consultants and contractors. This exciting new venture will give you access to one full year of The Data Governance Coach support including access to all of my online courses; three hours of one-to-one coaching per quarter; tailored training and access to resources plus some successful candidates may be invited to join the Data Governance Coach Associate pool at the end of the programme.

More information on the Data Governance Coach Academy will be released soon, so watch out for that! And if you want to be the first to know when it is launched just click here.

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

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