Monday, September 18, 2023

Steps To Implement Data Governance

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Ensure Data Governance By Design

Tools & Techniques to Implement Data Governance Webinar [May 2020]

Governance is hard to do well when its tacked on to peoples jobs. Think about it: Everyone in your firm is already working hard, perhaps at or over capacity. Now you want to add a new data governance program and increase the responsibilities of some key staff.

Its unfortunately common in IT to launch an initiative intended to revamp how IT works. Its a sensible goal, since IT serves the business and needs to ensure its optimized for that purpose. However, great plans go awry when IT underestimates the level of involvement needed from business partners. Or even worse, things go wrong when IT needs business partners to act or behave differently, yet IT begins its transformation without the necessary conversations and commitments.

With these twin challenges in mind, lets look at how to apply data governance by design to maximize your chances of success.

How To Implement A Data Governance Initiative

A goal of a data governance initiative is to identify the principles for the team and to establish targets and direction. This template will aid you in capturing the meaning of data governance for your organization before you begin your initiative. It will help you gain sponsorship and educate the organization about your mission, vision, and goals.

Think With The Big Picture In Mind But Start Small

Data governance is a combination of people, process, and technology. To begin building the big picture, start with the people, then build your processes, and finally incorporate your technology. Without the right people, its difficult to build the successful processes needed for the technical implementation of data governance. If you identify or hire the right people for your solution, then they will help build your processes and source the technology to get the job done well.

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Challenge : People And Perspectives

Often, in organizations, the true potential of high-quality data is underestimated. Employees are often busy with the operational activities and overlook the benefits of the data governance plan in the long run.

Solution: Have a clear vision and mission for data governance.

For people to appreciate the need and benefits of a data governance plan, they should have a thorough understanding of why it is done. The mission and goals of data governance should be practical and simplerather than based on abstract terms.

Engage With Your It Team Or Outsourced Data Specialists

5 Vital Steps for Strategic Data Governance

Once the scope of data is defined, the data committee can work with the businesss IT team to develop a data governance framework. This framework sets out how data governance rules will be integrated into the businesss data systems.

There are many elements that go into ensuring data quality and integrity which contribute to effective data governance.

For example, how do you maintain accurate customer records when one system may contain data that is different to another?

To achieve unified information in a common format, your IT team must understand master data management and data lineage. Both play an important role in providing business users with a clear picture of where their data is coming from so they know if it can be trusted.

Other key elements include meta data and data scrapping. Meta data delivers clarity because it applies a consistent language to all data so technical teams can see at a glance the context of the data and what format its in.

Data scrapping is another useful element for data governance because it works to collate information that a business user may not have, but ultimately needs. For example, a car manufacturer may say that a certain model gives mileage of 7L per 100kms. But how do you know whether a specific car is achieving that mileage? In this case, data scrapping would retrieve inputted mileage details each time a car is serviced, so these insights become available in the future.

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What Are The Key Best Practices For Implementing Data Governance

What should never be forgotten in implementing data governance is to remember that data does not belong to one part of the organization but must be shared to all. It is therefore imperative to standardize the data. To do this, Christina Poirson explains the importance of a data dictionary: by adding a data dictionary that includes the name, definition, data owner, and quality level of the data, you already have a first brick in your governance.

As mentioned above, the second good practice in data governance is to define roles and responsibilities around data. In addition to a Data Owner or Data Steward, it is essential to define a series of roles to accompany each key stage in the use of the data. Some of these roles can be :

  • Data Quality Manager
  • Data Protection Officer
  • etc

As a final best practice recommendation for successful data governance, Christina Poirson explains the importance of knowing your data environment, as well as your risk appetency, the rules of each business unit, industry and service to truly facilitate data accessibility and compliance.

Let Us Now Understand The 5 Steps For Implementation Of Data Governance

Step 1:Assessment By understanding who has created, approved, and who is using the data, the purpose, relevance of whom they are using, and who owns the processes? By answering all these questions you can collaborate all the existing reports in a better way. By identifying any scope for improvements that need to be made will enable us to create more effective strategies.

Step 2: Identify Challenges and Risks Identify the issues and challenges associated with the current sources of data and share them across different departments. Spot the gaps to protect your data regarding compliance and security and make use of the right people, technology, and processes.

Step 3:Data Controls To optimize your data quality and integrity it is vital to establish relevant metrics, control and develop the report processes. Establishing mechanisms will help to identify, prioritize and resolve the data-related issues. It is important to make sure that the right experts are involved in importing, documenting, and implementing the appropriate data controls.

Step 5. Implementing policies and standards This is the final step that includes implementing policies and standards with clear communication of roles and responsibilities By following all these 5 steps you can make the implementation of Data Governance more successful and make your business become a more data-driven business

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Why Is Data Governance Important

Data is, without a doubt, an organizations most valuable asset. Data governance ensures that information is useful, available, and secure. Data governance translates to improved data analytics, which leads to better decision-making and operations management. It also aids in the prevention of data inconsistencies or errors, which can result in data integrity concerns, poor decision-making, and many organizational issues.

Moreover, data governance is also critical for compliance issues, ensuring that firms meet all levels of regulatory obligations consistently. This feature is essential for decreasing operational expenses and eliminating vulnerabilities. At its most basic level, data governance leads to greater data quality, lower data management costs, and greater data access for all users. As a result, you make better decisions, which leads to better business outcomes.

Practical Data Governance: Implementation

Tackling Implementation Challenges of a Data Governance Program

The purpose of this course is to build your practical knowledge and maximize your success as a current or future data governance professional. The lessons and materials provided will be instrumental in your planning and implementation of a data governance program. You will learn the practical steps, best practices, and templates to put together and implement your data governance program from scratch or improve the one you have.

Templates included!

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Phase : Do The Groundwork For Data Governance

As a groundwork for data governance, its essential to start from the very basics by answering the following questions:


An organization should first define the vision and mission of its data governance plan. An organization must also define the goals of the data governance programincreasing revenue, better decision-making, or transparency. Also, it should determine how to measure the success of the program. A clear vision helps employees and other stakeholders see how this data governance initiative is going to impact their day-to-day work life and how it is going to help them.


Assigning roles and responsibilities is a crucial step. This step defines who will be primarily responsible for different tasks involved in the implementation of the data governance framework. Often, organizations adopt a three-tier approach to set up data governance teams. The steering committee, data governance office, and data governance working group are three main components in this approach. Together, these groups decide the next steps in the implementation of the data governance framework.


Get Going On The ‘how’

If your data governance initiative does not establish data quality processes to better utilize your data assets, and set up integrity and business rules to create a culture of quality, it is going to fail. Empower your staff to collaborate on the how of data governance to make better-informed business decisions. Baker Tilly is here to help you along your data journey, contact us to get going on your ‘how.’

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Identify And Recruit The Early Adopters

The next step is to survey the list of intersecting priorities identified in step 2, note the accountable leaders for each and identify which of these leaders are likely early adopters of data governance. Energetic leaders who truly understand the importance of data governance should be top of mind. Once each group establishes its governance objectives, these leaders often naturally become the champions of the organizations new data governance program.

Creating a list of desired characteristics for a data governance leader launches the search for early adopters. Geoffrey

Moores book Crossing the Chasm offers valuable insights into important characteristics of effective early adopters:

  • Connections: Early adopters need to be connected to the right resources.
  • Enthusiasm: Because early adopters motivate others to get on board, they must understand what needs to be done and why and be excited to get to work.
  • A deep understanding of data governance: Early adopters should understand data governance on more than a casual level and be aware of the challenges and benefits. Such awareness fuels the drive necessary to break through the inertia early in the programs development.

As the list of candidates grows, some questions that probe each persons understanding of the benefits of data governance will help narrow down the list to those most likely to carry the data governance program across the finish line. Consider questions such as the following:

Why This Course Is A Great Option For You

What is Data Governance?

This online course is the smartest, most cost effective, and time saving option of learning how to implement a data governance program. It is developed to be a 1-stop-shop that includes:

  • Real-life examples, relevant knowledge and best practices on implementing data governance
  • Practical templates youll be able to use and adapt easily and right away to your own needs
  • An engaging and fun learning experience with George Firican, your friendly data guy, who is great at turning dry knowledge into digestible and enjoyable bites

Plus this online course is the better way of learning:

  • At your own pace
  • From the comfort of your home or office, or anywhere you want to
  • With unlimited access to the material

What would be the other options?

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Why Do Businesses Need Data Governance

Even though most organizations do have volumes of data stored digitally or physically, most of the data is in a non-standardized format. Further, organizations cannot always be sure of the reliability of data due to age, the source, etc. Employees or business leaders often hesitate to rely on this data for decision-making due to worries about data quality. Data governance is a process that makes an organizations data reliable. It also makes sure that high-quality information is available across the organization. It empowers every department to make decisions based on this data. Data governance also drives the digital transformation of a business.

S For Effective Data Governance

Data governance is the way you collect, store, access, and share your data. Effective data governance allows you to take action from your data, provides easy access to those that need it, improves or maintains data quality, and ensures your data is protected. Ultimately, effective data governance should drastically improve business operations across the board.

Data governance implementation sounds like a daunting task, but it doesnt have to be. By accurately assessing your situation and dividing the work into steps, effective data governance is achievable for organizations of any size.


If your organization is operating and functioning, you already have some sort of data governance going on. If only one team has access to their departments files in Google Drive or DropBox, that is a current form of data governance. Ask yourself: is your data available to those that need it? Is my data quality good? Do my technology systems integrate with one another?

Being aware of what your current data governance looks like and identifying the improvements that need to be made will make creating a plan and strategy much easier.


Potential areas of risk:

  • Do you have BDRs or AEs traveling with company equipment?
  • Do we have decent security at the front desk?
  • Does the door on the data center lock?
  • Do we have the right probability of risk identified?

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First Steps To Implement Data Governance

Implementing data governance begins with making crucial decisions or requirements for the people and policies governing your data. Data governance strategy requirements may vary according to your needs, but this is an excellent place to start.

  • Choose your data stewards or the administrators in charge of your program.
  • Define the processes and policies that work for your enterprise.
  • Choose your data governance solutions. Understand that no solution will work for your company straight out of the box it will involve careful deployment and customization. However, Tableau is designed to work with your native architecture and is flexible as your data environment and business needs to grow and evolve.
  • Identify your data governance team that will work with your data stewards.
  • Plan your training program to get everyone on board.

About George Firicanthe Course Teacher

Building a Data Governance Plan for Your Power BI Environment

George is a passionate advocate for the importance of data, a frequent conference speaker and a YouTuber, being ranked among Top 5 Global Thought Leaders and Influencers on Big Data, Digital Disruption and Top 15 on Innovation.

His innovative approach to addressing data challenges received international recognition through award-winning program and project implementations in data governance, data quality, business intelligence and data analytics.George advises customer organizations on how to treat data as an asset, and he shares his practical takeaways on social media and various industry sites and publications.

George has been a data professional for more than 10 years. One of George’s passions is to create informative, practical and engaging educational content to share with individuals such as yourself, and help organizations get more visibility on social media. George is the proud founder of and co-host of the Lights On Data Show.

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Identify And Build The Value Driver

The first step to building a business case is to understand the value of the data initiatives you have or plan to have. Its not worth investing in a massive data platform if you dont know the value of potential use cases.

In mature organizations, there are already various data initiatives in place. So, to understand the importance of data governance, you simply need to determine how a data governance program could help speed up or improve the efficiency of these initiatives. On the other hand, in a fledgling organization, you must determine the potential value of these initiatives first.

Mature organizations will usually have built a business case before implementing a significant web of data lakes and data warehouses. A mature organization will ask itself whether it has achieved the objectives it set out to achieve, and if not, why not.

In a mature organization, it can be difficult to build a definitive business case because there already exist many initiatives. The main objective is to create an inventory of these business cases and their objectives and record their successes and/or failures. The next step would be to focus on the problems youve identified. If any initiatives are inefficient you should focus on how to improve them. Often, data initiatives are interlinked, but many people within an organization are unaware of these connections.

Adopt An Overall Data Governance Policy

The first step in governing Big Data is to adopt overall policies about your data. In particular, there must be clear policies around:

  • data inventory
  • data lineage
  • data retention

Policy management helps you consult the right stakeholders, understand the impact of changes, and formulate and enforce policies that improve efficiency and reduce errors and risk. This improves control over previously hidden or siloed enterprise data and empowers everyone in the organization to go beyond just producing and consuming data to trusting and using the data to optimize value.

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Taking The Right Steps To Implement Data Governance And Data Stewardship

Data as an asset comes up a lot in conversations these days. Data Governance enters the picture because of the huge role Data Strategy plays in supporting the business strategy and the need for that to happen without compromising data security, according to Mary Levins, Data Governance Principal at Sierra Creek Consulting.

Among the foundational requirements for a successful Data Governance program are focusing on Data Quality, standards management, policies, procedures, and accountabilities in alignment with business goals. But theres more to it, too. We dont hear enough about culture, stated Cassie Elder, Co-founder, Principal, Data Strategist and Data Scientist at DataCraft Partners. Its the most important factor to consider when you are leading a Data Governance program.

Culture Campaign

Levins broached the topic of how to identify and organizations core culture type. The task can involve the observation of the corporate mission statement and conducting surveys of employees or reviewing past surveys. A people-oriented company that is focused on today probably has a collaborative culture, for example, while a competence culture may be found within a future-focused business. Most organizations dont fall very neatly in one area, she noted. So, think about strengths and pitfalls to understand where your organization mostly falls.

Take the Data Governance Test

The response to it so far has been great, according to Sandwell:

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