Can I fast-track the creation of my data glossary by using standard definitions?

Data Governance takes a long time, and particularly in the early phases, it takes quite a lot of effort. Therefore, it is understandable that people look for ways to speed this process up. One of the ways I am often asked if this can be done is by fast-tracking the creation of items in a data glossary by using standard definitions.

However, it’s not a part of the process that can be skipped or glossed over, so to speak. Part of the reason for this is that organisations, even those within the same industry, very rarely use the same terminologies in exactly the same way. This means there is no bank of standard definitions to pick and choose from; what works for one client, will very rarely work for the next. Only by creating your own data glossary can you be sure that you have the correct definitions within it.

The best way to explain why is to give you a real-life example of a conversation I had with a client a few years ago.

This particular client had been making slow but steady progress with their Data Governance initiative and they had decided to bring forward some target dates for the completion of certain tasks, and to help with this they appointed a project manager.

This had happened in between my visits and so when I next visited, I had a conversation with the new project manager, and it went a bit like this:

He said: ‘We've got to get the data glossary built sooner and therefore we've got to find a better way of completing the data glossary than getting the data stewards to draft it and the data owners to approve the definitions.’

And naturally, I said: ‘Well, I can't think of a way that would be successful that I've seen to date.’

He replied: ‘We've got a really good idea. There's a chap that's joined that department over there. He has just come from another company in the same industry. He's got some time spare, and we've given him the fields that we need to be defined.’ 

I replied: ‘But he doesn't know what this organisation means by those terms.’

And the project manager said: ‘But they are standard terms used in the industry.’

Unfortunately, as I predicted, it was not fine.

This team member spent quite a lot of time filling in these definitions but when we shared those with the data owners and the data stewards there was a lot of confusion and back-and-forth about various terms and what they mean in different contexts.

This will almost always be the case within organisations. In my experience, where I have worked with multiple clients in the same industry, it is very rare for people to use the same jargon in exactly the same way.

Many organisations think they use terminology in the same way, but when they start comparing - particularly when people move between companies like in our example - there are always subtleties and sometimes it is even more than a subtle difference.

I would love to say that this would be a great way to fast-track the creation of a data glossary and that a bank of standard definitions is the answer to all your prayers, but I'm afraid it's probably more likely to result in confusion.

In the example above, it also doubled the workload and prolonged the creation of the data glossary. It also risks disengaging your data owners and data stewards; therefore, I would advise avoiding that approach if you can. Sometimes it is better to take the long road for a better outcome.

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 Data Governance?

(What you need to know if you are just starting out)

I’ve been writing blogs on my favourite topic of Data Governance for many years now and it only recently occurred to me that I had never written a blog covering what Data Governance actually is!  I’m not sure how that happened as I know that understanding what it is, is a vital first step. In fact, it is the first thing I cover in my training courses.  So, of course, I had to resolve that straight away and this blog is the result.

The business value of Data Governance, is often lost amongst the confusion surrounding what exactly it entails, not to mention the overlap with other relevant but separate disciplines, so it is important that we are clear what we mean when we use the term.

So what is Data Governance?

I’ll be honest it’s a topic that attracts some amount of confusion. A quick Google search will unveil a whole host of definitions and explanations that range from really useful, through confusing to downright wrong.  And I’ll be honest a lot of them are… well… a little bit boring!

The prolificacy of so many differing definitions a of source of much frustration, which I explore in more in this blog: Why are there so many different Data Governance definitions? 

One of the better definitions I’ve found online is this: 

“Data Governance is the cross-functional discipline of managing, improving, monitoring, maintaining and protecting data,” although I disagree with the “protecting” part (see the section below on what Data Governance Is Not for an explanation of why) it’s not a bad definition. It just won’t work for the business users you need to influence.  

Think about it from their viewpoint – does it sound like something that is going to help them do their job better; or more rules and regulations that hinder them from doing their job? My experience is that if you use that type of definition when first introducing the topic to them you are likely to get the latter reaction.

My experience has taught me that you need to explain why your organisation is (or should be) doing Data Governance first. The “what Data Governance is” can come afterwards once your audience have agreed that they want it

So I use the following definition that I developed years ago:

Data Governance is all about proactively managing your data to support your business achieve its strategy and vision.

How many senior stakeholders wouldn’t want to know more about something that is going to help their organisation achieve its strategic objectives?

Why Does Your Organisation Need Data Governance?

Of course, after sharing such a definition, you need to be able to explain it in more detail if asked.  So make sure you have done your preparation and know what benefits your organisation could achieve if they implement Data Governance. If you’d like to find out about determining these I recommend that you read: Why you Need Data Governance.

Are there better names to call it?

You may be thinking wouldn’t it just be simpler to change the title to better convey the benefits of Data Governance? And that may be something you wish to consider for your organisation. As I explain in Does it have to be called Data Governance? the topic is a generally misunderstood one and if changing the banner under which it is delivered, to make it suit your organisation, clears up any confusion then I’m all for it.

As long as the scope and purpose of your Data Governance initiative has been made clear from the off, a name change can be helpful in some cases. 

Of course, that can be easier said than done if it’s not already clear what should be included in such an initiative in the first place!

What do you do if you are “doing” Data Governance?

There are many activities you may decide to include in your Data Governance initiative, but it is important to remember that one blanket or standard solution won’t work across all organisations. In fact I’ve been asked so many times over the years about standard frameworks for Data Governance – that I wrote this blog to explain why one wouldn’t work: Where can I find a Standard Data Governance Framework?

You need to design a framework suited to your organisation’s needs. It’s important that you work out what your organisation needs from Data Governance. No one is going to thank you for starting a major initiative to document data lineage if there is no immediate value in doing so! You need to look at which activities will help you deliver the benefits you hope to deliver for your organisation. In What should you include in a Data Governance initiative? I cover a number of steps you can go through to work out the ideal scope of your initiative and in Do you know what is in a Data Governance Framework I provide an overview of what a Data Governance Framework consists of.

What Data Governance is not!

Now we’ve explored what Data Governance is exactly, I’d like to end this article by looking at what it’s not.

Seems like a strange way of looking at things, right? But, given that a number of the misunderstandings around the topic arise, it’s worth clarifying a few things:

Though undeniably linked to your Data Governance framework, Data Protection (also known as Data Privacy) is often confused with DG. It specifically revolves around the protection of personal information and although more recent Data Protection regulations, like GDPR, do have requirements that are more easily met if you have a Data Governance Framework in place, Data Governance is a separate discipline supported by a different expert team in your organisation.

Likewise, Data Retention, which focuses on how long you should hold onto data before deleting it, is something which your Data Owners should be consulted on but is a fundamentally different discipline.

Records Management or Information Management do bear some similarities to Data Governance, though they focus on the handling of complete records (whether they are analogue or digital) rather than electronic data which are the building blocks of records/information. 

While these separate disciplines all carry value in their own right and can (and should) be aligned with your Data Governance framework, they are ultimately separate. 

Unfortunately, the confusion surrounding the links between these different areas can feed into the misconception of Data Governance as a sort of grand, big Brother-esque surveillance program designed to watch business users’ every move with their data.

This isn’t the case at all! Data Governance is actually more about getting your business users to care about their data and its quality.

I hope you’ve found this blog a useful place to start understanding Data Governance better. If you are just starting out why not download my free Data Governance checklist here and get on the right track to developing a framework that suits your organisation’s needs and ambitions.

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.

The difference between a Data Catalogue and a Data Glossary

Data Governance is full of lots of jargon and terminology which can mean different things to different people. It’s all very subjective and 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.

 This is something I recently discussed in my ‘What is Data Custodianship?’ blog and even more recently than that I’ve noticed a lot of confusion around what a Data Catalogue is and how this differs from a Data/Business Glossary. 

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.

However, there are some distinct differences between these two things, and I am going to do my best to clear them up for you.

 What is a Data Catalogue?

A Data Catalogue is considered a core component of modern data management.

Very simply, a data catalogue uses metadata (data that describes or summarises data) to create a searchable inventory of all that organisation’s data assets. So, a Data Catalogue is a detailed inventory of all the data assets in an organisation, which is designed to help the data professionals within that organisation quickly find the data they need for whatever purpose they may need it for. It’s basically a tool to help you find that needle in your data haystack.

Data Catalogues can evolve with an organisation and over time, the metadata within a Data Catalogue can be enriched and updated to support better data discovery and governance within an organisation.

A data catalogue provides context to enable data analysts, data scientists, data stewards, and other business data consumers to find and understand a relevant dataset for the purpose of extracting business value. Data Catalogues can also support such individuals in acting upon it to realise the true value of the available data.

Functions of a Data Catalogue:

• ‘Dataset Searching’ – supporting searches for keywords, can also allow a user to check how frequently search results are used

•  ‘Dataset Evaluation’ – allows you to preview datasets to ensure you’re getting the right data you need to analyse (for instance, by previewing the data in question, checking data quality and user ratings, etc) – saves you potentially downloading the wrong data

• ‘Data Access’ – Data catalogue can aid the process of search to access

 What is a Data or Business Glossary?

A Data Glossary is an exhaustive list of all terms used across the company with definitions. It comes back to what I said at the start… organisations use lots of jargon and terminology which can mean different things to different people.

A Data Glossary defines the terminology which organisations use when discussing their processes and their data. It is purpose is to define the business/data terms within the organisation.

The Data Glossary is designed to keep everyone on the same page and using a common vernacular to ensure clarity and consistency between departments. Think of it as a dictionary for a particular organisation (but not a data dictionary – that is another thing entirely – you can read more about what that is and how it differs from a data glossary here: https://www.nicolaaskham.com/blog/2017/11/8/what-is-a-data-glossary-and-how-is-it-different-from-a-data-dictionary?rq=dictionary)

The Difference

A Data Glossary does not define the data like a Data Catalogue does. The data glossary defines the terms we use when discussing the data and who owns that data.  A Data Catalogue contain more technical metadata to help you find and locate your data.

A Data Glossary and a Data Catalogue are two different things (which can be linked to provide extra value), although both have their place and can be very useful to organisations when implementing data governance.

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 data stewardship?

If you Google ‘data governance’ you will find that the terms ‘data stewardship’ and ‘data ownership’ appear alongside the many definitions of data governance. Over the years I have found that this tends to confuse people because they think that must mean governance, stewardship, and ownership are all different concepts.

However, they are not different at all. In fact, stewardship and ownership are roles and responsibilities which play a key part in successful data governance.

Data owners are the senior people in your organisation who own your data and are accountable for the quality of it. For data governance to work these data owners need to be reasonably senior people within your organisation and they need to be the people with the authority, budget, and resources.

I recently explained the data ownership role in more depth in another blog, which you can find here: https://www.nicolaaskham.com/blog/2021/4/15/what-is-data-ownership

The downside of this is that when you start telling those who are accountable for data that they might need to write things like data definitions and that they might need to investigate and fix data quality issues they can be resistant to this.

Unfortunately, it is also the case that even if they are invested in the data, they are probably not going to be in a position to understand it in granular enough detail to oversee it on a day-to-day basis. Also, given their senior roles within an organisation, they may not have the time to deal with the data in that sort of way. This is where data stewards come in.

In practice, when I’m implementing a new data governance initiative, I will identify the right data owners with an organisation, and once I have done that I will invite them to appoint one or more data stewards to help them in the delivery of their role.

The data owner remains accountable, but they will delegate the day-to-day responsibility to a data steward. In my experience data stewards often tend to be the subject matter experts but are still reasonably senior because they have to be trusted by their data owner.

If you took, for example, a finance department, it is likely that the finance director or his deputy would be the data owner for all the finance data. Then, in my experience, finance departments tend to be made up of a number of different specialist teams all focusing on different areas - and working with different data. This means it wouldn’t be practical to have just one data steward working under the data owner.

The data owner is likely to have to appoint the head of each of those sub-teams to be a data steward for them or that subtopic.

I hope that gives you an idea of what data stewardship is and how it fits in with data governance. Don't forget if you have any questions you’d like covered in future videos or blogs please email me - questions@nicolaaskham.com.

Or 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 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.