The Importance Of Data Governance

What Is Data Governance

Importance of Data Management and Data Governance in AI | Great Learning

Data governance is the process of managing the availability, usability, integrity, and security of the data in enterprise systems. It is governed through internal data standards and policies that control data usage, and effective governance ensures that data is trustworthy, consistent, and does not get misused.

Costs Of Data Governance

To implement a data governance plan that addresses potential data issues your company faces, youll need to dedicate resources and time. Depending on the size of your business and the data it collects, you may need staff dedicated entirely to implementing your governance plan.

While your organization may need to invest its time, money and resources into a data governance plan, a successful plan can help recoup this investment. When an effective plan is put in place, your company has high-quality data that is organized efficiently so it can be used to streamline business processes and identify consumer needs.

The Importance Of Understanding Why

Understanding why your organization is implementing data governance is crucial for several reasons, but most importantly you need to know the why in order to guide your data governance strategy and the change management adoption strategy within your organization.

Unfortunately, its not enough to just know that you should have data governance, its also important that everyone within your organization understands why you should have data governance. If not, everyone understands and can relate to the why then there is a risk that the whole initiative could come off the rails.

That might sound dramatic, however, there are countless examples of organizations that have designed excellent data governance frameworks that are well suited to their businesses that have eventually failed because they failed to address the culture change in the very beginning.

Simply, you need everyone, particularly those who will be involved in the implementation of the data governance initiative to buy into it for it to be a success. You cannot start to manage your data as an asset and realize the value of it if you don’t address culture change and adopt a change management strategy early in the process.

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Trust Smartfile To Help You

There are a lot of important factors that need to be included when you are putting together your strategy. If you want to get the most out of your data, you must adopt a strong data governance strategy. It can be difficult to do this on your own, which is why it is important to rely on a professional service that can help you. SmartFile can help you get the most out of your files, keeping them protected and making sure the right people can quickly and easily access them.

Through SmartFile, you will have access to a web interface and a traditional FTP connection, allowing you to customize your service to meet your needs. You can quickly and easily manage file permissions, ensuring that the right people have access to your files. You also have access to various helpful tools for administrators, allowing you to easily manage your compliance and regulatory issues. With more transparency, youâll have the information you need to make decisions quickly. SmartFile is trusted across multiple industries, and you will have a convenient dashboard that you can use to manage all of your information. Contact us today to learn more about how we can help you with data governance.

Starting A Data Governance Program

Working with relevant stakeholders to develop data governance standards and rules is the first step toward establishing a successful data governance practice. The next stage is to create plans for putting such procedures in place and enforcing them. These processes are just as vital as the underlying policies to ensure that projects are carried out properly and that guidelines are followed consistently.

Take these pointers into account:

From the start, including all stakeholders and data asset owners in the process.
Train and educate all necessary teams, people, and stakeholders on data governance on a routine basis.

Assist in creating and executing the data governance systems and procedures by maintaining open lines of communication. This assistance can take the form of emails, newsletters, official reports, updates, or conferences, but regular contact with all stakeholders is critical.
Make sure to work with goals that are clear, precise, and attainable.
Begin small and gradually build up once ready. It is tempting to take on all the goals at once, but it is better to start with a few minor goals and gradually build up from there.

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Quick Review: What Is Data Governance

Data Governance is the set of processes, and procedures organizations use to manage, utilize, and protect their data. In this context, data can refer to a subset of a companys digital or hard copy assets. Defining what data means to an organization is one of the core data governance best practices. Once you define what data means, you can formulate ways to use your data in ways that advance your business.

Think of data governance as the who, what, when, where, and why of your organizations data.

Another key aspect of data governance is protecting both company and customer private data. Data breaches are near-daily occurrences and governments are constantly enacting laws and regulatory frameworks like HIPAA, GDPR, and CCPA. A big part of data governance is protecting the private data of customers and citizens. A good data governance program builds controls to protect data and help organizations adhere to compliance regulations.

Align Data Governance To Specific Business Outcomes

It is crucial to align your business strategies and priorities with your data governance framework. More often than not, data governance efforts are not associated with business priorities. When data governance is not connected with business priorities, data leads are often not heard when it comes to decision-making.

Aligning data governance with specific business outcomes is attainable for organizations. It can be done by laying out attributable business metrics to stakeholders who work with data. Data governance decisions should reference both business and data metrics while relating those decisions to business goals.

Lets say a marketing team does not trust the data theyre working with they are not only unable to base their decisions on the data but are likely to take their data elsewhere. When data is siloed off, it is much harder to unify data within an organization, ultimately, leading to game-changing use cases never being turned into a reality.

Make Sure Everyone Follows The Rules

There should be consistent communication between your DGC and the rest of the business. Employees should be aware of new policies and understand the reasons behind them. For example, one new policy might be that employees can no longer use their personal devices for work-related tasks. This might cause an inconvenience, but communicating the why will help employees understand that no longer using work-related devices will keep company information .

Better Decision Making And Business Planning

The Growing Importance and Impact of Information Governance

We live in an age where data has become the critical driver of business decisions. A strong data governance allows authorized users to access the same data, erasing the danger of data silos within a company. IT, sales, and marketing teams work together, share data and sights, cross-pollinate knowledge, and save time and resources. Increased data centralization

Ensure A Data Governance Strategy Is Rooted In Accountability

Basing a data governance strategy on accountability will assure stakeholders that the right governance processes are in place. When users are accountable for their actions with data governance, users confidence in the quality of data will increase. This will lead to increased data productivity across the organization.

To achieve a data governance strategy rooted in accountability, it is best to start with evaluating the current accountability model your company follows for data governance. Compare that model with the way your data decisions are currently made in your organization, and then understand why you do so.

Once you figure out the difference between what is happening and what should be happening, you can identify the business impact and take action on your current accountability model. Here are some steps your organization can take to ensure data governance is rooted in accountability:

Create a centralized team or person responsible for data governance in your organization.

Work with internal stakeholders to agree on an approach to data governance.
Work with tools to deploy your data governance model that works for both systems and people.
Review and reassess your data governance strategy as often as possible.

You need someone internally to take responsibility for the initiative. Great analytics isnt plug and play but once you get it set up properly with Snowplow, it just works!!

Ty W, VP Operations, Anon

Data Governance In Healthcare

Healthcare may be at the top of the list of industries that require a comprehensive data governance policy. Consider the enormous amount of healthcare data available to any individual, the sensitive nature of that data, and the life-or-death situations that rely on accurate data. It is indeed understandable why data governance is critical in healthcare.

Patient records, blood test results, EKGs, MRIs, billing records, drug prescriptions, and other sensitive medical information are all examples of data in the healthcare profession. Medical professionals require healthcare data to make educated decisions about patient treatment. Data governance gives healthcare organizations a regulated and structured way to share medical data so that each patient receives the best possible treatment.

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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.

Besides more accurate analytics and stronger regulatory compliance, the benefits that data governance provides include improved data quality lower data management costs and increased access to needed data for data scientists, other analysts and business users. Ultimately, data governance can help improve business decision-making by giving executives better information. Ideally, that will lead to competitive advantages and increased revenue and profits.

Know Who Is In Charge Of What

Getting the right people involved is critical to a successful data governance plan.

A strong data governance strategy consists of multiple levels of leadership. On the executive level, you have senior leaders and managers. On the strategic level, you have the Data Governance Council , which consists of one to two people from each unit or department. At the tactical level, you have Data Domain Stewards and Data Steward Coordinators. At the operational level, you have Data Stewards, who are your employees who use data for daily tasks or projects. Lets take a look at the different roles to understand exactly what each position does.

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Aligning The Data Governance Roadmap With The Business Plan

A business plan is a formal document that defines the goals of a business in detail and its plans for attaining those goals. It lays out the businesss goals from financial, marketing, and operational perspectives.

These goals should be built into the Data Governance roadmap. The broad goal of increasing online sales may be a business goal that can be broken down into smaller goals, some of which are covered by Data Governance. For example, many businesses have discovered that cross-selling can increase their profits by creating relevant and useful consumer experiences. Cross-selling which includes the use of recommendation engines is a powerful tool supported by DG.

A good Data Governance program can be used to build trusted data sets, which are needed for effective cross-selling. Examples of this include Netflix, which uses a collaborative filtering process to examine the viewers likes and dislikes, and then offers a list of movies and shows it predicts the viewer will enjoy. Similarly, Amazon offers customers products they predict will be personally relevant.

So What Should My Company Do

When you are ready to get serious about data governance a few things must be in place: buy-in from multiple teams, and the right tools.

One of the most important factors with data governance is alignment with all teams and individuals that will be in charge of collecting, governing, and consuming the data. Ensure that everyone is on board and that there are clear goals, clearly defined processes, and clear permission levels to make everything run smoothly. The key to data governance is effective collaboration. The right data governance tool should go hand-in-hand with these principles. Make sure that whichever tool you are evaluating is easy to use for business and IT users alike, enables seamless collaboration across teams and is flexible enough to evolve with your changing business needs.

What Is Data Management

Datamanagement is the workflow managing the creation and realization of theelements required to handle an organizations data, including data retrieval,generation, and disposal. With these elements implemented, an organization cananalyze and utilize big volumes of data significantly more efficiently.

Nowadays,nearly all business processes are data-driven, so an organization should treatdata as a critical asset and manage that asset appropriately. To do that, ITteams should understand the elements of data management clearly and establishthe required workflows.

Data Management Elements

The listof data management subcategories includes the following:

Below weexpand the definition and underpin the critical meaning of data governance fora contemporary organization.

Looking For More Data Governance Support

CIA Triad in Data Governance, Information Security, and Privacy: Its Role and Importance

If you want to know more about data governance and how you can implement a strategy, we are here to help.

You can find all the support you need in IT Governance: A Pocket Guide. Written by IT Governance Founder and Executive Chairman Alan Calder, this guide outlines the key drivers for IT governance in the modern global economy.

It looks specifically at corporate governance requirements and the need for companies to protect their information assets.

Youll learn how the role of IT governance supports the management of strategic and operational risk. Youll also discover important considerations when setting up an IT governance framework.

The approach throughout is resolutely nongeek, avoiding technical jargon and with the emphasis on business opportunities and needs.

Data Governance Best Practices

There is general agreement among experts that the first five best practices for data governance are:

Think with the big picture in mind, but start small. All good advice. If youre starting from scratch , youre breaking new ground. Its always prudent to start small test out your ideas and understanding in a limited way to learn, develop skills, and validate the approach before committing to the whole effort. At the same time, keeping the big picture in mind is important. Its too easy to get wrapped up in the minutia and stray from the overall objective. So, document the high-level goals of your project , carve out a modest piece that can be your pilot test area, and validate your approach through this pilot test.

Appoint an executive sponsor. As with all cross-enterprise projects, it is important to secure an executive business sponsor to be the champion for the data strategy. They will actively advocate and communicate the strategy to the broader organization. The sponsor will also enforce accountability, model the desired data mindset, and help arbitrate data issues between business units.

A manageable handful of useful and meaningful measurements is much better than 50 or 100 that dont provide much insight into how systems are actually functioning and whether objectives are being met.

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24 April 2020

My team and I lead self-service analytics initiatives in the United Nations and our work has helped transform the Organizations approach to data. I believe that as the UN continues to make analytics platforms available to mostly non-technical business users, the value proposition for effective data governance is imperative.

In my view, data governance is associated with a set of tenets that can significantly improve data quality and data-driven insight within an organization. Once defined, these tenets would guide all our data work and would be adhered to even as the volume, variety and velocity of data continued to expand and change.

Governance is not incompatible with innovation

Technology is changing at a much faster rate than our processes. But data governance does not need to get in the way of technological innovation. If a data governance framework is built with the objective of providing a foundational layer that can help users operate data responsibly and securely, it will have better chances of being accepted and adapted in the innovation process.

Foundational governance elements can provide solid underlying guidance, regardless of our technologies or data volume. These elements include:

A clear definition of data principles

Data classification
Data quality criteria
Data lifecycle and

Classification of users .

*The views expressed herein are those of the author and do not necessarily reflect the views of the United Nations.

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Who Is Involved In Data Governance

A well-designed, high-quality data governance program usually includes a responsible governance team, a steering committee that serves as the governing body, and a group of data stewards. Data stewards refer to an oversight role in data governance within an organization.

They are tasked with ensuring the quality and fitness of the organizations data assets. Data stewards are considered a specialist role, and they also assist with the development and implementation of data assets and recommend improvements to the data governance process.

All the individuals mentioned here work together to create the standards and policies for governing data, as well as the implementation and enforcement procedures primarily carried out by the data stewards. Senior executives and representatives from an organizations management also take part in data governance along with the IT and data management teams.