Get Governed Building World Class Data Governance Programs

Getting In Front On Data

This book lays out the roles everyone, up and down the organization chart, can and must play to ensure that data is up to the demands of its use, in day-in, day-out work, decision-making, planning, and analytics. As Tom Redman, the Data Doc, explains in Getting in Front on Data, the secret lies in getting the right people in the right roles to get in front of the management and social issues that lead to bad data in the first place. Everyone should see himself or herself in this book. We are all both data customers and data creatorsGetting in Front on Data proposes new roles for data professionals.

Data Governance Vendors And Tools

Data governance tools are available from various vendors. That includes major IT vendors, such as IBM, Informatica, Information Builders, Oracle, SAP and SAS Institute, as well as data management specialists like Adaptive, ASG Technologies, Ataccama, Collibra, Erwin, Infogix and Talend. In most cases, the governance tools are offered as part of larger suites that also incorporate metadata management features and data lineage functionality.

Data catalog software is included in many of the data governance and metadata management platforms, too. It’s also available as a stand-alone product from vendors such as Alation, Alteryx, Boomi, Cambridge Semantics and Data.world. Learn more about the features that data catalog software offers, including its governance-related capabilities.

Continue Reading About What is data governance and why does it matter?

Determine A Data Governance Model

The next step is to create a data governance model for your team to work off of. This model should describe the hierarchy for who can view and distribute different types of data. This ensures that sensitive data is placed in the hands of your most trusted employees and isn’t shared without authorization. You can view one example of a data governance model below.

Source: TDan

You should also describe your rules and regulations for data collection. Outline your standards for securing data as well as which channels you’ll use to obtain it. This will create consistency in your data collection which will lead to more reliable and accurate takeaways.

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Engage Your Stakeholders For Success

Naturally, it is important to engage with your colleagues throughout all levels of the organization to make your data governance program a success. Program leaders should communicate value metrics that resonate with strategic, operational, and tactical stakeholders so that they understand the value of your data governance program in helping all stakeholders achieve their own goals and objectives.

To learn more about how your organization can benefit from a business-first approach to data governance, watch our free on-demand webinar today, How to Build Data Governance Programs That Last.

Components Of A Data Governance Framework

A data governance framework consists of the policies, rules, processes, organizational structures and technologies that are put in place as part of a governance program. It also spells out things such as a mission statement for the program, its goals and how its success will be measured, as well as decision-making responsibilities and accountability for the various functions that will be part of the program. An organization’s governance framework should be documented and shared internally to show how the program will work, so that’s clear to everyone involved upfront.

On the technology side, data governance software can be used to automate aspects of managing a governance program. While data governance tools aren’t a mandatory framework component, they support program and workflow management, collaboration, development of governance policies, process documentation, the creation of data catalogs and other functions. They can also be used in conjunction with data quality, metadata management and master data management tools.

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The Data Governance Imperative

The Data Governance Imperative is written from a business persons view of data governance. This practical book covers both both strategies and tactics around managing a data governance initiative, and enables readers to understand their business at a deeper level and handle support issues more smoothly. Steve Sarsfield is a leading expert in data quality and data governance, focusing on the business perspectives that are important to data champions, front-office employees and executives. Understand how proper data governance can transform your business buy this book today and gain an edge over your competitors.

Who’s Responsible For Data Governance

In most organizations, various people are involved in the data governance process. That includes business executives, data management professionals and IT staffers, as well as end users who are familiar with relevant data domains in an organization’s systems. These are the key participants and their primary governance responsibilities.

Chief data officerThe chief data officer , if there is one, often is the senior executive who oversees a data governance program and has high-level responsibility for its success or failure. The CDO’s role includes securing approval, funding and staffing for the program, playing a lead role in setting it up, monitoring its progress and acting as an advocate for it internally. If an organization doesn’t have a CDO, another C-suite executive usually will serve as an executive sponsor and handle the same functions.

Data governance manager and teamIn some cases, the CDO or an equivalent executive — a director of enterprise data management, for example — may also be the hands-on data governance program manager. In others, organizations appoint a data governance manager or lead specifically to run the program. Either way, the program manager typically heads a data governance team that works on the program full time. Sometimes more formally known as the data governance office, it coordinates the process, leads meetings and training sessions, tracks metrics, manages internal communications and carries out other management tasks.

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Goals Of Data Governance

The goal is to establish the methods, set of responsibilities, and processes to standardize, integrate, protect, and store corporate data. According to BARC, an organizations key goals should be to:

• Minimize risks
• Improve internal and external communication
• Increase the value of data
• Facilitate the administration of the above
• Reduce costs
• Help to ensure the continued existence of the company through risk management and optimization

BARC notes that such programs always span the strategic, tactical, and operational levels in enterprises, and they must be treated as ongoing, iterative processes.

Big Data Governance: An Emerging Imperative

Written by a leading expert in the field, this guide focuses on the convergence of two major trends in information managementbig data and information governanceby taking a strategic approach oriented around business cases and industry imperatives. With the advent of new technologies, enterprises are expanding and handling very large volumes of data this book, nontechnical in nature and geared toward business audiences, encourages the practice of establishing appropriate governance over big data initiatives and addresses how to manage and govern big data, highlighting the relevant processes, procedures, and policies.

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Data Governance Goals And Benefits

A key goal of data governance is to break down data silos in an organization. Such silos commonly build up when individual business units deploy separate transaction processing systems without centralized coordination or an enterprise data architecture. Data governance aims to harmonize the data in those systems through a collaborative process, with stakeholders from the various business units participating.

Another data governance goal is to ensure that data is used properly, both to avoid introducing data errors into systems and to block potential misuse of personal data about customers and other sensitive information. That can be accomplished by creating uniform policies on the use of data, along with procedures to monitor usage and enforce the policies on an ongoing basis. In addition, data governance can help to strike a balance between data collection practices and privacy mandates.

Measure Your Goals With Metrics

Lastly and certainly not least, a crucial data governance best practice is measuring your data governance program. Your team needs to evaluate the data governance programs progress and its impact on the rest of the organization.

This data governance best practice tends to be the most challenging for organizations, but it is an essential element to powering continuous improvement.

The first step is to understand and define what success looks like. Success at your organization will not look like success at another organization. Success will depend on what your organizations overall objectives are. Ask yourself and your teammates

• What does a successful data governance program look like?
• What does it mean to achieve Data Intelligence?
• How will we know when we achieved Data Intelligence?

Once, you can answer the above questions, you can identify your goals and evaluation criteria. Your key performance indicators should relate directly to your organizations objectives and strategies. Some areas to track are

These are just some of the data governance best practices that Data Intelligent organizations follow. And depending on the industry, there are different approaches. To learn more about data governance practices and how they generate positive business outcomes, check out these success stories.

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Benefits Of Data Governance

Most companies already have some form of governance for individual applications, business units, or functions, even if the processes and responsibilities are informal. As a practice, it is about establishing systematic, formal control over these processes and responsibilities. Doing so can help companies remain responsive, especially as they grow to a size in which it is no longer efficient for individuals to perform cross-functional tasks. Several of the overall benefits of data management can only be realized after the enterprise has established systematic data governance. Some of these benefits include:

• Better, more comprehensive decision support stemming from consistent, uniform data across the organization
• Clear rules for changing processes and data that help the business and IT become more agile and scalable
• Reduced costs in other areas of data management through the provision of central control mechanisms
• Increased efficiency through the ability to reuse processes and data
• Improved confidence in data quality and documentation of data processes
• Improved compliance with data regulations

Data Governance Vs Data Management

Data governance is just one part of the overall discipline of data management, though an important one. Whereas data governance is about the roles, responsibilities, and processes for ensuring accountability for and ownership of data assets, DAMA defines data management as an overarching term that describes the processes used to plan, specify, enable, create, acquire, maintain, use, archive, retrieve, control, and purge data.

While data management has become a common term for the discipline, it is sometimes referred to as data resource management or enterprise information management . Gartner describes EIM as an integrative discipline for structuring, describing, and governing information assets across organizational and technical boundaries to improve efficiency, promote transparency, and enable business insight.

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Best Data Governance Books In 2022

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As data becomes more significant, it is perhaps the most valuable asset that businesses have. Data governance makes sure that this information is usable, accessible, and well-secured.

Data governance also leads to better data analytics, which leads to better decision-making and operational support.

Acknowledged industry leaders, experts, and technology professionals have written insightful books that even the most seasoned data worker will find useful.

This article explores a list of the best Data Governance books to read in 2022.

Templars book is well-organized and informative, with an approachable voice that covers all the bases without becoming bogged down in jargon.

This is our overall best book on Data Governance because it lays out a clear path to success while also keeping you awake and entertained with stories of how Data Governance has impacted the lives of consumers and workers.

The Small Business Corner section of each chapter, which pertains directly to businesses with specific and relevant ideas offered by Templar, was well-received by the majority of those who read the book.

Date Published: 2010

Date Published: 2016

Price: Affordable

Grow Up Kid: The Maturity Model

Measuring your organization up against a data governance maturity model can be a very useful element in making the roadmap and communicating the as-is and to-be part of the data governance initiative and the context for deploying a data governance framework.

One example of such a maturity model is the Enterprise Information Management maturity model from Gartner, the analyst firm:

Figure 2.

Most organizations will before embarking on a data governance program find themselves in the lower phases of such a model.

Phase 0 Unaware: This might be in the unaware phase, which often will mean that you may be more or less alone in your organization with your ideas about how data governance can enable better business outcomes. In that phase you might have a vision for what is required but need to focus on much humbler things as convincing the right people in the business and IT on smaller goals around awareness and small wins.

Phase 1 Aware: In the aware phase where lack of ownership and sponsorship is recognized and the need for policies and standards is acknowledged there is room for launching a tailored data governance framework addressing obvious pain points within your organization.

Phases 4 and 5 Managed & Effective: By reaching the managed and effective phases your data governance framework will be an integrated part of doing business.

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The Straightforward Guide To Data Governance

Data governance plays a major role in organizing and protecting your internal data. It acts as a form of insurance that every piece of information you collect is properly stored and distributed within your organization.

In this post, let’s discuss what data governance is and how you can implement a policy at your company.

Master Data Management And Data Governance 2/e

Master Data Management and Data Governance, Second Edition provides up-to-date coverage of the most current architecture and technology views and system development and management methods. Discover how to construct an MDM business case and roadmap, build accurate models, deploy data hubs, and implement layered security policies. Legacy system integration, cross-industry challenges, and regulatory compliance are also covered in this comprehensive volume.

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Get Governed By Morgan Templar

The book Get Governed: Building World Class Data Governance Programs by Morgan Templar is an excellent book for any information professional to read. In the world of information governance, data governance is only a small slice of the pie. Although there isnt huge overlap between records management and data governance there is still a lot that can be gleaned from this book for Certified Records Managers. Data governance is a more mature discipline than information governance and many of the principles in Get Governed can be applied to those working in information governance.

The similarities between data governance and information governance can be found in the definition of the disciplines. In the glossary Templar defines data governance as The activity of defining and organizing structure around information. As she talks more about the topic in the book she fleshes out this definition by stating that data governance ensures that the right information is available in the place to the right people at the right time. Information governance is this same principle, but at a higher strategic level and with an emphasis on the policy and not the activity.

After policies and reference documentation are in place Templar next recommends deciding how you will structure your governance program as this will have a big impact on the success of your undertaking.

Set Clear Goals For Data Governance

Once you’ve implemented the new governance system, setting goals for your program will ensure its long-term success. These goals can include protecting top-level data, reducing friction between teams, decreasing the costs of data management, and creating a faster data entry process. Whatever your goal is, it should be actionable and include a roadmap to success.

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How Data Drives Your Business

Data serves three critically important functions in most organizations. Reporting and compliance helps to shield the company from regulatory action and risk. Analytics and insights inform both strategic and tactical decisions and provide an accurate picture of how the organization is doing with respect to key performance indicators and process performance indicators . Finally, data drives operational excellence by enabling automation and eliminating friction from business processes.

The best data governance programs act as a support for all three of these functions. To be successful, data professionals must think about how data is going to be used to drive all of them simultaneously. In many organizations, these three functions often operate as disconnected silos, although they frequently work with the same data.

Imagine that customer service leaders in the organization want to increase online data availability for self-service inquiries without adversely impacting risk and compliance. That could result in happier customers and fewer routine calls handled by customer service personnel. The same customer data serves the product management team, as they seek to better understand the companys customers and their needs using advanced analytics.

What Is Data Governance

Data governance is the combination of individuals, processes, technologies, and systems that work together to ensure an organization’s data is accurate, secure, and easily discoverable for employees. Businesses use data governance to safeguard their data, control who has access and who is responsible for owning and managing it, and distribute it to employees for routine use.

Without data governance, data can become unreliable or invalid and pose a significant threat to your organization. Or, data may not be easily available, which will affect employees’ day-to-day workflows. In a survey by McKinsey, respondents said that 30 percent of their total enterprise time was spent on non-value-added tasks because of poor data quality and availability and this percentage varied by department or role.

Worse still, if the data becomes completely unusable, data collection will have to start from scratch.

Let’s take a closer look at the reasons businesses need a data governance strategy.

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