The First Six Months of Your New Data Governance Initiative

If you’re considering starting a Data Governance initiative, you may be wondering what the first six months of work might look like - and that is a very good question because it is challenging… and even though I have done it many times before, sometimes it still surprises me exactly how involved and challenging those first few months can be!

Here I am going to set out roughly what you should expect when on your Data Governance journey – but please remember, this is just a guide based on my many years of experience, every organisation and therefore every Data Governance initiative is different.

Managing expectations

The first thing I was you to remember is that data governance is all about cultural change and therefore you're probably not going to get things within your organisation moving very quickly and one of the very first things you need to do is manage the expectations of whomever you're reporting to and what you're trying to do.

Six months down the line you're not going to have a fully embedded data governance framework, but you will have designed and begun the implementation process.

Early Days

It's important they understand why your company is doing Data Governance, and why your role is being created, because once you understand those drivers it makes it much easier to engage with and sell your Data Governance initiative to senior stakeholders. This is what you will spend some of the first month of your journey doing – establishing and selling your ‘why’.

What we’re talking about is speaking to senior people within your organisation and talking to each individual to understand what their challenges are, what their views on data at your company, what challenges have they got.

Use their feedback to build your framework and work out which bits of Data Governance you need in place and establish which parts you are going to focus on first. So, once you've designed something, the next stage is to start socialising it with the senior stakeholders and get them to really buy into it and let them think that they've helped shape it and their input into it, because it’s going to address the issues they’ve brought to your attention around data.

Once you’ve done that then you need to try and get them engaged and explain to them that it's not going to be quick - you've not got a magic wand that you're going to wave… but you're going to be able to try and put in place some frameworks and processes and roles and responsibilities that should ease the pains of some of those challenges.

Next Steps

In the next stages of your Data Governance journey, you are going to start fleshing out some of those roles and responsibilities and perhaps even start working on a data glossary. This is another great way to ensure team members and senior stakeholders feel engaged in the process, as you’ll need their input to flesh out these things to ensure everyone within the organisation is singing from the same hymn-sheet.

Appointing the wrong people to key roles can cause the wheels to come off any well thought out initiative pretty quickly. So, getting the basics right and the most effective and suitable team in place from the outset will stand you in good stead for successful data governance implementation. In order to appoint the most appropriate people to these roles, it is important to understand what they involve and what their responsibilities will be.

From the top to the bottom of an organisation, it is crucial to your data governance initiative that you identify fit and proper people to take on each of these important roles and that they also understand what role each other plays in the big picture.

Again, getting the basics right and the most effective and suitable team in place from the outset will stand you in good stead for successful data governance implementation.

Now, this blog is titled ‘What to Expect in the first SIX months of your Data Governance initiative’ and you are probably wondering why the creation of these things would take up such a large chunk of time and it is understandable that people look for ways to quicken this process up. One of the ways I am often asked if this can be done is by fast-tracking the creation of items like 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 will very rarely work for the next. Only by creating your own data glossary can you be sure that everyone fully understands the definitions within it.

Moving On

The next step may possibly be to implement a data quality issue resolution process because whilst you're doing the initial engagement, maybe creating conceptual data models, people will be starting to tell you anecdotes - their data quality horror stories - and this is a great time to start identifying where some of your biggest quality issues lie and begin logging which of them need investigating and fixing.

You're not going to solve everything in six months, but at the very least, I would start logging issue and once I've designed my process for investigating and resolving them, I would roll the process out on a phased basis for key consumers of data first.

Full Circle

You may not feel like this is very much to have achieved in six months, but trust me, from my years of experience I can assure you it is. And to bring you full circle, please remember – you MUST manage both you and your organisations expectations when it comes to the early phases of implementing your Data Governance initiative.

You're dealing with people and organisational change. It's going to take time and don't underestimate the amount of energy and effort it will take. I think a lot of people just assume that they can sit at their desk, design a framework, send it out and people will start doing things.

It takes a huge amount of effort and energy and preparation. It's a standing joke that my husband believes that what I do is go to meetings! In reality what I'm doing is meeting people and trying to influence them to change their behaviours - and I'm not going to do that sitting at my desk sending out emails.

At the end of six months, if you can have designed your data governance framework perhaps created a some conceptual data models and use that to identify and agree data owners, you'll be doing really well.

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

Data Management Disciplines - Separate Specialities or Better Together?

In today's data-driven world, organisations face the challenge of managing vast amounts of their biggest asset – data. And with so many different data disciplines, and different data teams within an organisation being responsible for such an important asset, it’s no surprise that sometimes the lines of who is responsible for what and how teams work together can get blurred.

In order to understand where Data Governance fits and how we can work together, we must first understand what Data Governance is, and more crucially, what it is not…

What is Data Governance?

Data Governance is a collection of processes, roles, standards, and metrics that ensure the effective and efficient use of information in enabling an organisation to achieve its goals. It establishes the processes and responsibilities that ensure the quality and security of the data used across a business or organisation. Data Governance defines who can take what action, upon what data, in what situations, using what methods.

A well-crafted Data Governance approach is fundamental for any organisation that works with data, and will explain how your business benefits from consistent, common processes and responsibilities. Business drivers highlight what data needs to be carefully controlled with your Data Governance Framework and the benefits expected from this effort.

Data Governance ensures that roles related to data are clearly defined, and that responsibility and accountability are agreed upon across the enterprise. A well-planned Data Governance framework covers strategic, tactical, and operational roles and responsibilities.

What Data Governance is not

Data Governance is frequently confused with other closely related terms and concepts, including data management and master data management – but it is neither of these things.

Data management refers to the management of the full data lifecycle needs of an organisation. Data Governance is the core component of data management, tying together nine other disciplines, such as data quality, reference and master data management, data security, database operations, metadata management, and data warehousing.

Master Data Management (MDM) focuses on identifying an organisation's key entities and then improving the quality of this data. However, there is no successful MDM without proper governance. For example, a Data Governance program will define the master data models (what is the definition of a customer, a product, etc.), detail the retention policies for data, and define roles and responsibilities for data authoring, data curation, and access.

So how does Data Governance interact with other disciplines?

Data quality is a fundamental aspect of effective data management. Data Governance provides the necessary structure and oversight to establish data quality standards, define data quality metrics, and monitor data quality throughout its lifecycle. By collaborating with data quality management, Data Governance ensures that data is accurate, reliable, and fit for purpose, ultimately enabling better decision-making and reducing operational risks.

By aligning data integration and ETL processes with Data Governance principles, organisations can avoid data silos, improve data accessibility, and promote a unified view of data across the enterprise and by integrating Data Governance with MDM, organisations can establish data ownership, resolve data conflicts, and ensure data consistency across systems, thereby enabling accurate reporting, streamlined processes, and enhanced decision-making.

Collaboration between Data Governance and data privacy/security disciplines allows organisations to identify and classify sensitive data, define access controls, and monitor compliance with data protection regulations. By working together, Data Governance and data privacy/security disciplines help safeguard data assets, mitigate risks, and maintain stakeholder trust.

 Better Together

Data Governance stands as a crucial bridge between various data management disciplines. By collaborating with data quality management, data integration, metadata management, master data management, and data privacy/security, Data Governance ensures the consistency, integrity, and security of an organisation’s data. This collaborative approach establishes a robust data management framework that enhances data-driven decision-making, mitigates risks, and drives organisational success.

Embracing the collaboration between Data Governance and other data management disciplines is imperative for organisations aiming to derive the maximum value from their data assets in today's data-centric landscape.

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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 with implementing a Data Glossary, Data Catalogue or other data needs then please book a call using the button below.

The 7 Potential Benefits of Having a Data Glossary or Data Catalogue

Is harnessing the power of a Data Glossary or Data Catalogue the key to unlocking the true potential of your data endeavours?

In today's data-driven world, businesses and organisations are constantly generating and dealing with vast amounts of data. This deluge of information can be overwhelming, making it challenging for employees to understand and utilise the data effectively, often leading to confusion and inefficiency.

While it may feel like a bit of a time and monetary investment, the implementation of a Data Glossary or Data Catalogue can significantly enhance an organisation's data management capabilities, leading to improved efficiency, better decision-making, and enhanced collaboration, allowing the true potential of the data to be unlocked.

Sadly, a lot of organisations implement a Data Glossary or Data Catalogue as “best practice” as part of a Data Governance initiative without really understanding the value you can get from having one.  So what are these benefits you can achieve?

Listed below are those that I have seen my clients achieve over the years:

1. Enhanced Communication and Efficiency

One of the key advantages of having a Data Glossary or Data Catalogue is the ease of communication it brings. Everyday actions like responding to enquiries become straightforward, with a simple reference to the glossary or catalogue to make sure that you use the correct data. This saves time and effort, as employees no longer have to spend significant portions of their work hours searching for data.

By providing a centralised repository of all available datasets with detailed descriptions, users can quickly identify the data they need without wasting time searching through various sources, leading to increased productivity and reduced operational costs.

2. Clarity and Consistency in Data Terminology

In the modern business landscape, confusion around data terminology is a common issue. Different departments might use varying terms for the same data elements, leading to misunderstandings and inconsistencies. With a Data Glossary or Catalogue, everyone within the organisation can adhere to uniform data definitions and understand the context in which specific terms are used. This promotes a data-literate culture, wherein employees are better equipped to comprehend data, ask meaningful questions, and draw accurate insights.

3. Improved Data Quality

A Data Glossary or Data Catalogue also acts as a repository for metadata, providing essential information about each dataset, including its source and quality metrics. By maintaining a comprehensive record of data lineage and quality assessments, data users can assess the reliability of the data they are working with. This, in turn, helps improve data quality as potential issues are identified and addressed promptly.

4. Enhanced Compliance

Data governance is crucial for ensuring compliance with many regulatory requirements. A well-organised Data Glossary or Data Catalogue can help meet regulatory requirements. It enables data stewards and administrators to monitor and ensure that sensitive data is appropriately handled and regulations are adhered to.

While Data Governance and Data Protection are not the same thing, with increasing data privacy regulations, such as GDPR and CCPA, organisations must respond to Subject Access Requests (SARs) promptly and accurately. SARs involve providing individuals with information about the personal data the organisation holds about them and how it is being processed. A Data Catalogue simplifies this process by providing a comprehensive inventory of data assets and their locations. Identifying the data relevant to a specific request becomes much easier and faster, saving time and avoiding potential legal complications.

5. Empowering Data-Driven Decision Making

Data is a valuable asset, and understanding its value is essential for making informed business decisions. Data Glossaries and Data Catalogues support data analysts by providing a detailed understanding of available datasets and their context. This knowledge enables analysts to perform more accurate and meaningful data analysis, leading to better-informed decision-making.

6. Facilitating Data Collaboration and Knowledge Sharing

In organisations with diverse teams and departments, data collaboration is vital for achieving meaningful insights. A Data Glossary or Data Catalogue encourages knowledge sharing by facilitating communication and collaboration among data users. The tool becomes a hub for exchanging ideas, insights, and best practices related to data analysis, fostering a data-driven culture throughout the organisation. 

7. Streamlined Onboarding and Training

In all organisations, data plays a crucial role, but new employees often face a steep learning curve when it comes to understanding the complex data landscape. A well-maintained Data Glossary or Data Catalogue simplifies the onboarding process by offering a comprehensive overview of data assets, reducing the time required for new hires to get up to speed and start contributing effectively.

The benefits of implementing a Data Glossary or Data Catalogue are clear: enhanced data understanding, communication and efficiency, data quality, and decision-making. As data continues to grow in volume and complexity, having a robust data governance strategy that includes a Data Glossary or Data Catalogue becomes more critical than ever. By investing in these tools, businesses can harness the full potential of their data, gaining a competitive advantage in today's fast-paced and data-centric landscape.

What do you think? Are you already benefitting from a Data Glossary or Data Catalogue, or do you think your organisation should think about implementing one? Let me know in the comments below.

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 with implementing a Data Glossary, Data Catalogue or other data needs then please book a call using the button below.

Data Governance Know How

Embarking on a journey in Data Governance can feel isolating and overwhelming. It’s very common in this field to struggle to find a sense of connection and understanding in your day-to-day work. But there are places to feel less lonely, share best practices, and meet new Data Governance friends including ‘Data Governance Know How’!

Data Governance Know How is a group that a few connections and I came together to form and is a supportive community focused on Data Governance.

When first venturing into the realm of Data Governance, many of us find ourselves navigating uncharted waters. The lack of camaraderie and shared experiences can make this journey feel solitary and discouraging. Despite attending various industry events, professionals often struggle to establish meaningful connections with like-minded peers. Plus, Data Governance can be a solitary role within an organisation, where you are fighting for change and improvements that others might not fully comprehend. This sense of isolation and the challenges it brings served as the catalyst for the creation of Data Governance Know How.

The group is a space where professionals can come together, share experiences, and collaborate. It’s a therapeutic outlet, allowing Data Governance professionals to discuss their challenges and find solace in the company of others who understand their struggles. We also try to help each other find practical solutions to the issues faced in Data Governance and cultivate a collaborative environment for our members to exchange knowledge and support one another.

Since being formed, Data Governance Know How has evolved and made a huge difference in the DG community, it’s even been described as a "big data hug!” The support also extends beyond formal events, with members readily connecting on professional networking platforms like LinkedIn and Slack.

The group's structure facilitates networking opportunities and the creation of collaborative outputs and resources, providing valuable references for individuals on their data governance journeys.

Data Governance Know How is a pure joy to organise and we all love working with people as passionate about Data Governance as we are. We all find a huge amount of satisfaction in supporting others with their career growth.

We always try to make our events interactive and engaging and try to stay away from the traditional webinar structure, involving our members and catering to their preferences as much as possible. We take topic suggestions and welcome members as speakers to share their insights. By combining practical learning elements with networking opportunities, our events provide a balanced and enjoyable experience for participants and our virtual events allow Data Governance professionals from around the world to participate and benefit from the community.

For those interested in joining, membership is accessible through our Meetup group. We actively encourage new members to join and engage with the community and we have a dedicated channel to foster ongoing conversations and knowledge exchange between events.

If you’re a Data Governance professional seeking support, networking opportunities, and the chance to contribute to the data governance community, I promise you will find a welcoming environment within this group!

What are the key components of a data culture?

Data culture is the collective behaviours and beliefs of people who value, practice and encourage the use of data to improve decision-making. As a result, data is woven into the operations, mindset and identity of an organisation. A data culture equips everyone in an organisation with the insights they need to be truly data-driven.

However, developing a data-driven culture requires a comprehensive approach that involves training and education, infrastructure and tools, organisational support, and a continuous emphasis on data-driven decision-making and learning from a senior level all the way through the ranks.

But, whilst establishing a data-driven culture can seem challenging, if a company is able to achieve it, the benefits are huge. A strong data culture can lead to better insights, improved decision-making, innovation, and a competitive advantage for organisations.

The difference between data culture and data governance

Maintaining an effective, shared data culture can feel like a balancing act between control, compliance, and data access. As data ownership rightfully moves from the exclusive hands of IT into lines of business, companies struggle to implement and enforce organisation-wide policies that balance data access with control and compliance.

Data governance is an important part of data culture because it provides the framework for organisations to balance the need for data control and the necessity of removing gatekeepers to enable data democratisation and expedite the broad use of data. But data culture itself is a far larger initiative, touching every aspect of business life and every employee and data user.

What are the key components of a data culture?

The key components of a data-driven culture are:

Data Literacy: This refers to the ability of an organisation's workforce to read, understand, and interpret data. A data-literate workforce is essential to building a data-driven culture.

Data-Driven Decision Making: A data-driven culture is one where decisions are made based on data insights rather than intuition or assumptions. Data-driven decision-making ensures that decisions are based on facts, not opinions.

Accessible Data: Data should be available to everyone who needs it in the organisation. This includes ensuring that data is stored in a centralised location and that employees have the necessary tools and training to access and use it effectively.

Data Quality: Data quality is crucial to the success of a data culture. To ensure that data is accurate and reliable, organisations must establish standards for data collection, processing, and storage.

Continuous Learning: A data culture requires a commitment to continuous learning and improvement. This includes ongoing training and education for employees on the latest data tools, techniques, and best practices.

Collaboration: Collaboration is essential to building a data culture. This includes sharing data insights across teams and departments, breaking down silos, and encouraging a culture of transparency and open communication.

Accountability: An effective data culture requires accountability. This includes establishing clear goals and metrics, tracking progress, and holding employees and teams accountable for achieving their objectives.

By incorporating these key components into their values, beliefs, and practices, organizations can build a strong data culture that supports data-driven decision-making and helps drive business success.

Benefits of a strong data culture

In an increasingly complex data landscape, a lack of data literacy, due to skills gaps or an inconsistent understanding of data across the organisation, has thrown data access and control out of balance. This is characterised by either data gatekeeping with too many restrictions hampering the use of data, or a data free-for-all with too much access threatening data quality and compliance. Either situation leads to widespread frustration across the organisation.

A strong data culture is the solution to all these problems. With a common understanding of the meaning, importance, and applications of data, the entire organisation is positioned to get the most from its biggest asset

How do you create a data culture?

There is no doubt that creating a data-driven culture is a challenge. There is no single answer or magic solution, but a successful strategy for culture change takes all the various stakeholders into account, understanding their needs and where they fall in the rollout.

When it comes to data, culture change starts with the data team, IT leaders, and the chief data officer (CDO). They need to establish the organisation-wide data strategy necessary to balance appropriate control of the data with data access that will support the business.

With a common set of expectations, a common language for data across the organisation, and a shared emphasis on the importance of data for business decisions, it’s easy for the rest of the business to follow suit.

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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 would like to know more about how I can help you develop a data culture, including data literacy training, then please book a call using the button below.

How the COM-B Model for behaviour change can be used when implementing Data Governance

The biggest mistake I see in organisations implementing Data Governance failing to address culture change as part of their initiative. This mistake is by far the most common I see and it can ultimately lead to the complete failure of a data governance initiative. I have seen situations where people have actually designed a really great framework that is ideal for their organisation, but it's been not successful because it's not implemented properly - they failed to address the culture change side of things.

The result of that is your business users, your stakeholders, just feel that data governance is being done to them and not for or with them as it should be. In this scenario, they tend to do as little as possible of what you're asking them to do, or even nothing at all, if they can possibly get away with it.

Simply, you can't start to manage your data as an asset and realise its value if you don't address that culture change.

How to avoid it

The first and most simple thing is to apply some really good change management techniques and if you are not well-versed in them, I'm sure there are people in your organisation who are, but it boils down to lots of very good quality communication with all of your business stakeholders.

This is going to be different communications for the different groups of stakeholders about their role in the data governance implementation and making sure there is good training in place for everybody in your data governance framework who has a role to play like data owners or data stewards.

It's really important that you bring these people along the journey with you because if you don't address the culture change your data governance initiative is never going to deliver the benefits you were hoping for.

The COM-B Model

One approach that can be used to facilitate behaviour change in Data Governance is the COM-B model. The COM-B model is a theoretical framework used to understand behaviour and behaviour change.

The COM-B model proposes that behaviour is influenced by three main factors: capability, opportunity, and motivation. Capability is a person’s individual's ability to perform the behaviour. Opportunity refers to the external factors that facilitate or inhibit the behaviour and motivation is the internal factors that drive behaviour.

When implementing Data Governance, the COM-B model can be used to identify the specific factors that may be preventing individuals or teams from adopting the new behaviours and practices that come with a new data governance initiative. By identifying these factors, Data Governance teams can identify ways in which to address behaviour to best support the implementation of data governance.

Capability and Data Governance

Capability is an individual's physical and psychological ability to perform the desired behaviour. In the context of Data Governance, this may include knowledge and skills related to data governance, such as data quality or metadata management. If individuals or teams lack the necessary capabilities, they may struggle to implement effective Data Governance practices.

To promote behaviour change in this area, it may be necessary to provide team training to help individuals develop the necessary skills and knowledge to succeed in the part they have to play in implementing a Data Governance initiative.

Opportunity and Data Governance

Opportunity refers to the external factors that facilitate or inhibit behaviour change. In the context of Data Governance, this may include access to resources, such as tools and technology, or organisational support.

To promote behaviour change in this area, it may be necessary to provide individuals or teams with resources to support effective Data Governance practices. This could include providing access to data management tools, such as data cataloguing tools, or providing organisational support, such as a dedicated Data Governance team.

Motivation and Data Governance

Motivation refers to the internal factors that drive behaviour, including beliefs, values, and attitudes. In the context of Data Governance, this may include beliefs about the importance of data quality or attitudes towards the role of Data Governance in the organisation.

To promote behaviour change in this area, it may be necessary to address individual or team beliefs and attitudes towards Data Governance. This could involve developing targeted communication campaigns or engagement strategies to help individuals understand the importance of Data Governance and its role in the organization.

Conclusion

The COM-B model provides a useful framework for understanding behaviour and behaviour change when implementing Data Governance.

By identifying the specific factors that may be preventing behaviour change, practitioners can develop targeted strategies to promote the adoption of new behaviours and practices.

By improving capabilities, providing opportunities, and addressing motivation, organizations can promote effective Data Governance practices and ensure the accuracy, availability, and security of their data assets.

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

Can we use Process Owners instead of Data Owners?

Today’s blog has been inspired by a debate I saw on LinkedIn where somebody had suggested that we really don't need data owners because they're really hard to find and we could use process owners instead because they already exist at your organisation.

I obviously got involved in this debate and felt it important to do a blog on to explain fully why, while I think process owners can be useful, they are not a substitute for data owners. They are not interchangeable and there are two reasons for this.

Reason One

The first one is that in my experience that some sectors and even some companies within sectors are not that mature when it comes to processes, so if your organisation hasn't got your processes documented and mapped then it also doesn't have the concept of process owners in place.

In this case, you're off to a non-starter before you even start…

Reason Two

Let's consider the opposite of that and perhaps your organisation is really good at documenting its processes and has very well-embedded process owners as a role. These are people who understand that they get to have some responsibilities around that process and the inputs into it.

When I work with clients like that I think ‘this is great; this is going to make it easier for me to find my data owners’, but I never think let's use the process owners instead of data owners.

What I do is to look at the process owners as being likely candidates to become a data owner for me and this works really well.

They're usually suitably senior. They've got the authority to make decisions about the process so then it's an easy and logical next step to get them to take responsibility and have the authority to make decisions about data.

Now my problem with just using process owners instead of data owners is that some data is only used in one process in one place in your organisation. In this case, the process owner is likely to be the data owner. However, with data that is used in multiple processes, across your organisation that then gives you multiple data owners who are unlikely to think of consulting with each other to make sure that they're making consistent decisions about the data.

This in turn will mean that you're actually no better off because you won't have any common understanding of what the data means. You'll have nobody making consistent decisions with that overview of what that data means across the whole organisation.

By all means, if you have process owners, look at them as likely candidates to be your data owners, but please, I would encourage you not to think you can abandon trying to find data owners.

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

Why is Data Governance Coaching and Training Expensive?

Unfortunately, Data Governance Coaching is not free. In fact, sometimes it can be quite the opposite… but there’s an easy answer to the question: ‘Why is Data Governance Coaching so expensive?’ Simply, it can add massive value to your organisation.

Not to mention, products and services that are “cheap” tend not to be cheap at all. They usually end up being very expensive because even though you thought you were getting a bargain you’ve just wasted your money and gained nothing from it.

It all depends on what you want to accomplish and the value you place on accomplishing it. Data Governance Coaching is no different.

If you want a Data Governance Coach with the skills, knowledge, and experience to help you achieve your business and data goals and give you all the tools you need to stay resilient and successful long after you’ve finished working with them, then you need to reframe your thinking – it’s an investment, not an expense.

If what they’re providing is the information, guidance and support that will get you where you want to go, that fee might initially seem expensive, but it isn’t really. It’s worth every penny.

Look at it this way… when you work with an effective, professional coach – someone who can add real value to you, your team and your business and help you realise your complete potential – you’re not just benefiting from the time you spend with them every week or month. You’re benefiting from all the knowledge they’ve accumulated over years of hard work and constant study.

But if you still need convincing here are my top four reasons to invest in Data Governance Coaching or training…

1.I know where you’re coming from because I’ve been there!

There’s lots of advice available online and in books, but how do you take this huge quantity of sometimes conflicting theory and turn it into something practical?  You might have tried sharing some of this theory with your senior stakeholders, but you are struggling to articulate what it means to them and your organisation.

What’s more, if you fail to convince them to support your Data Governance initiative and you don’t start to actually deliver value, the Data Governance initiative will fail, and you will be blamed. I get it. I have been there. We can work through it together. By investing it coaching, you are benefiting from the mistakes I’ve made in the past – so you don’t have to make them!

2. Real solutions to your problems!

Training gives you 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 and network with others in a similar situation.

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

During training, you’ll have the opportunity to share your questions and experiences to find the right approaches to resolve your Data Governance dilemmas, too.

3. You’ll gain confidence in your own Data Governance Initiative

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.

There is no such thing as a standard approach to Data Governance but there are some clear steps that everyone needs to follow to gain senior stakeholder buy-in and to design a framework that is right for them.

Over 20 years of designing and implementing Data Governance Frameworks I have developed a practical approach that takes you through all the steps needed to be able to successfully design and implement a Data Governance Framework that is right for your organisation.

4. Data Governance can feel lonely - let’s network!

Attending a Data Governance course or Mastermind Day gives you 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 whose remit it is.

You can find out more about my upcoming Live Online Data Governance Training and Clinic here and also my upcoming 1 Day Data Governance Mastermind Workshop here.

I hope that was helpful and 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.