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What Is Data Governance? What Is Its Importance?
Want to be a data-driven organization? Then get your data governance in place. In this article, you will learn what data governance is, the Importance of data governance, why data governance is not optional, best practices for data governance, 7 principles of data governance, and lastly, data governance challenges.
Data governance is a system for defining who has the authority, within an organization, to control data assets, and how they can be used. Data governance includes processes, people, and the technologies that are required to manage and protect the data assets.
Importance of data governance
When there is effective data governance, the chances of finding data inconsistencies across an organization isn’t a problem anymore. For example, account names might be written differently across systems. Something like this can create data integrity issues and affect the accuracy of Business Intelligence (BI) and analytics accuracy.
Find some of the benefits of data governance, below.
- Data will be consistent and uniform across the organization and decision making becomes easier
- There is increased efficiency because of reusing processes and data
- Since there are clear rules for changing processes and data, your business becomes more agile
- Reduces your costs for data management
- Easier to be compliant with data regulations
- The business will be able to get a 360-degree view of critical business entities
- You will be able to understand the location of all data related to key entities
Data governance tools
If your organization is looking for the right data governance approach, then it is imperative that you look for reliable and scalable tools. Make sure that you choose a cloud-based tool and that it has a plug-and-play system. The data governance tool that you select should be based on the business benefits that you want to get out of it.
The data governance tool you choose should help do the following:
- Control your data by actively reviewing and monitoring it
- Understand your data by profiling, discovery, benchmarking tools, etc.
- Validating, data cleansing, and enriching to improve the data quality
- Managing your data effectively so that it is easy to track and trace them
- Increase the searchability, linkability, accessibility, and compliance of the data
Why is data governance not optional?
Organizations these days have incredible amounts of data, not only of their customers, but also of their suppliers, employees, third-party vendors, partners, and so on. If they can make good of the data that is available to them, the business will be able to prosper. When there is data governance, the data within the organization also become trusted, secure, safe, documented, and confidential. It is the duty of the leadership to ensure that your organization is able to maximize data governance investments and minimize the chances of any data breach.
Best practices for data governance
While every organization is different, you do need to follow some of the best practices to ensure that your business has a smooth data governance journey.
- Do not go all in. Strive for small victories.
- Ensure that you have specific, measurable, achievable, and realistic goals.
- Define the ownership of the data governance responsibilities. If there is no one to handle the issues, then the data governance framework cannot succeed.
- The data governance framework should be adapted into how you conduct your business.
- Make sure that you map your infrastructure, architecture, and goals. Your company’s data governance framework should be a part of your IT landscape and enterprise architecture.
- Get the buy-in from key stakeholders.
- Speak about the data governance framework in simple business terms so that it is easy to understand what it entails
- Focus on the most critical data elements after identifying them.
- Identify use cases related to your cost savings, growth, etc.
- Focus on data quality KPIs and integrate it with your performance KPIs
Seven principles of data governance
In 2020, Gartner identified seven principles that you need to follow for data governance. Let us look at each one of them:
1. Value and outcomes
Your data governance should be aligned with your business outcomes. To measure the progress, you need a strong data analytics setup in place.
Is it possible for you to trust all your data sources? Is the data under your control throughout its lifetime? If you want a distributed data system, your data governance should be built on a model of trust. It is imperative that you know where the data comes from so that expectations can be managed.
3. Accountability and Decision rights
Ensure that your team is accepting of your data governance strategy. All the stakeholders should be made accountable for your data. You need to define who can make decisions about the data.
4. Transparency and ethics
The data analytics on your data governance should be transparent. There should be a well-established decision-making process so that even a 3rd-party audit should not find any faults.
5. Education and training
Train data owners and other stakeholders on the principles of data governance. Make sure that you have a well-defined training program to make sure data governance is in place.
6. Risk and security
Businesses engage in data governance to manage risk and security issues that might crop up because of data.
7. Collaboration and culture
How are different departments going to operate together so that they can keep the data safe?
By focusing on these seven areas, you will be able to accomplish your data governance goals and refine your data governance operational methodology.
Data governance challenges
When you put a data governance plan in place, you will come across a variety of challenges that you need to face head-on. Let us look at each of them.
1. Data silos
One of the biggest problems with data governance is that different departments do not share their data with each of them. This happens often because datasets are not available for each of them. The teams might not even know about the kind of data that other teams have. There is such a disconnect that it leads to inconsistencies across data sets and creates more problems.
2. Lack of trust
To get actionable insights from your analytics engine, the data quality should be superior. The data in your system should be reliable and consistent, which is what will build trust. When there is distrust of data, they will not trust the results from the analytics.
3. Lack of leadership
To execute new standards and policies, there should be immense support from the leadership. There are many organizations that do not have a Chief Data Officer (CDO) to manage their information. When a data governance structure is being developed, each and every implementation process should be reviewed thoroughly so that the structure, delivery, and policies are clear.
4. Lack of resources
More often than not, data governance is an afterthought for most companies. Finding the resources or necessary budget for it is usually more difficult than normal. Many organizations assume that data is the responsibility of the IT department. IT cannot manage all the data, and they certainly cannot be solely responsible for data governance.
5. Lack of control
One of the most common data governance challenges is the lack of control over data. When there is no control over data, it can result in non-compliance. The reason why laws such as HIPAA, GDPR, PCI-DSS, and CCPA have been put in place is to regulate how sensitive data is handled. Businesses that do not follow them strictly will be met with severe punishments.
All organizations out there should have a clear-cut strategy on how to handle their data, and it starts with having a data governance strategy in place. When data is consistently handled with care, it will give you solid business outcomes. Organizations that ensure security and compliance of their data, stand to extract value from all that is collected, and it will reflect in their business’ success too.
So, whether you are an SME or enterprise company, data tracking is the key to the success of your business. Schedule a 30-minute call and learn about Zuci’s Data Engineering Services to craft a single source of truth system for real-time data analytics, business reporting, optimization, and analysis.
If you want to make sense of your data while being compliant with all the data regulation laws, we would be more than happy to help your organization achieve that. Get on a call with the data governance experts at Zuci.
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