5 Reasons Why Data Governance is Important for Business Intelligence Success

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“Every business intelligence or analytics initiative needs to have the foundation of accurate, well-managed data that comes from a robust data governance program” – Anne Marie Smith, Ph.D.

Do you want to be at the forefront of business intelligence success? Then data governance is absolutely essential for your organization.

In fact, Report Linker projects that the BI market will see a market expansion and hit $33+ billion by 2025, and data governance is one of the key drivers for this, alongside dashboarding and cloud adoption.

When properly implemented, data governance can lead to better decision-making, improved performance, and reduced risk — all great outcomes for your organization!

In this blog post, we will discuss five reasons why data governance should be an integral part of your business intelligence strategy.

Get ready to unlock the potential of effective data governance and stay ahead of your competition!

Let’s get started!

What is Data Governance?

Before we can dive right into how data governance helps with business intelligence success for your business, you first need to understand what data governance is.

Data governance is the process of ensuring that data is accurate, reliable, and consistent, both in terms of content and format, across all systems and within an organization.

It involves creating policies and procedures to ensure the quality of data, as well as establishing roles and responsibilities for maintaining it.

Data governance also involves defining data collection, storage, retrieval, and usage standards.

By implementing effective data governance strategies, organizations can ensure that their decision-making is based on accurate and up-to-date information.

With effective data governance, organizations such as yours can unlock the potential for improved efficiency and better results.

What is the Difference Between Data Governance and Data Management?

Data governance involves creating policies and procedures around data, while data management is responsible for implementing those policies and procedures to gather and utilize the data for informed decision-making.

Essentially, data governance is one of the elements of data management. Other elements include:

• Data preparation
• Data pipelines
• Data extract, transform, load (ETL)
• Data catalogs
• Data warehouses
• Data governance
• Data architecture
• Data security

However, data governance focuses on how the data being managed is processed through the organization.

Some elements of data governance include: 

• Data Quality
• Data Security and Compliance
• Data Stewardship
• Data Transparency

In an analogy by Tableau, data governance is like designing and creating the blueprint for a new building, while data management is akin to constructing the building according to that blueprint. 

Although it’s possible to construct a building without a blueprint (data governance), it will likely be less efficient and effective, with an increased risk of data structure failure in the future.

Why is Data Governance Important for Business Intelligence Success?

1. Improved Quality of Data

The 6 Dimensions of Quality: Source

Data governance helps ensure that all data in an organization is accurate, reliable, and consistent.

This means that the data that you will use for decision-making is of a much higher quality, which in turn leads to better decisions by yourself.

For example, if inaccurate customer information was used for marketing campaigns, this could lead to ineffective campaigns and wasted resources.

With data governance in place, you can be assured that your customer information is up-to-date and accurate.

Data governance also helps create a system that makes it easier to detect and fix errors quickly when they arise.

By creating clear policies and procedures for data accuracy, organizations can detect errors at early stages and take corrective action before any significant damage has been done.

This will enable business intelligence analysts and business analysts to report accurate data that reflect the true health of your business.

As a business scales, it is important for you to have data governance infrastructure to be in place so that you can leverage the historical data collected for predictions and trends in your business moving forward.

What I mean by infrastructure is things like teams, processes, and systems; must all be aligned.

Spiceworks recommends that your Security, Compliance, Privacy, and Data Teams ensure data governance. These are done by ironing out and defining processes and putting systems in place to ensure data integrity.

Here is a team structure you can adopt:

• Security Team: The security team is familiar with the cloud environment and detect/prevent sensitive data from leaking.
• Data Team: The data team wrangles data sets and is responsible for data availability, quality, and discoverability, and maintains the data dictionary.
• The Privacy & Compliance Team: This team ensures users review and consent to the privacy policy and oversees the organization handles data subject requests (DSRs) well.

However, organizations often face cross-functional talk between teams.

The security team lacks the context of data stores, the data team lacks regulatory and security expertise, and the privacy & compliance team lacks context and access controls.

As data governance is cross-functional, the teams mentioned above need to be working in a cross-functional manner to work together to protect and govern data at scale.

According to Spiceworks, to achieve good cross-functional teams, they must build processes and systems that:

• Track both data at rest and data in use
• Consider data, user, and infrastructure context against applicable regulations, third-party DPAs, and other internal data governance guidelines
• Protect data after assessments on a continuous basis
• Reduce dependence on time-consuming and occasional audits
• Improve how data governance is performed in their organizations. 

2. Reduced Risk

Data governance helps to greatly reduce the risk associated with decisions made using inaccurate or unreliable data.

“Managing and mitigating data-related risk is critical for business growth and sustainability. The better you manage data integrity, the more efficiently you can run operations and maintain stakeholder trust.” – Chris Ajiri

For example, if your organization were to make a decision based on faulty customer information, this could have serious consequences such as legal action, fines, or brand damage.

With data governance in place, organizations can be sure that they are making decisions based on reliable and accurate data.

Data governance also helps reduce the potential for fraudulent activities related to data manipulation.

For business intelligence success, improving the accuracy and consistency of data across systems and networks, organizations can ensure that all users have access to reliable information in your organization or business.

3. Increased Data Handling Efficiency

With reliable data at your fingertips, organizations like yours can make faster and more informed decisions, increasing efficiency and reducing costs.

By monitoring and regulating the data stored in databases using a data governance tool, you can ensure its accuracy and reliability, thus ensuring more accurate analysis results.

In a Gartner report in 2022, they predicted that “By 2026, 20% of large enterprises will use a single data and analytics governance platform to unify and automate discrete governance programs.”

Benefits of Cloud-Based Data Analytics and Data Governance Platform

Data-savvy companies are adopting cloud-based data analytics platforms due to the many benefits it has compared to traditional tools.

Here are some benefits of using a cloud-based data management platform:

1. Cost savings

If you’re looking for a budget-friendly way to handle data analytics, cloud-based solutions may be the answer.

With no need to purchase expensive on-premise hardware or software upfront, you can save money from the get-go.

Plus, ongoing maintenance and support costs are reduced, leaving more room in your budget for other business needs.

2. Agility

With cloud-based data analytics, you can hit the ground running. They’re easy to deploy, so you can start using them in no time.

Plus, they’re more agile than on-premises solutions, which means you’ll be able to take advantage of new features and updates more frequently and faster – giving you a competitive edge in today’s fast-paced business environment.

3. Flexible Deployment

Cloud-based data analytics can be deployed in a variety of ways, including on-premises, in the cloud, or in a hybrid environment.

This provides the flexibility to choose the deployment option that best meets your needs.

4. Enhanced Collaboration

With cloud-based data analytics, accessing and sharing data becomes effortless for team members, allowing for more efficient collaboration.

5. Access to Data Worldwide

Users can access data from any location worldwide with cloud-based data analytics, enabling better decision-making regardless of their whereabouts.

6. Efficient Decision-Making

Cloud-based data analytics equip you with the necessary tools to make faster and better decisions. By accessing real-time data and robust analytics tools, you can confidently make informed decisions that propel your business forward.

7. Improved Data Consistency

Additionally, by ensuring data consistency across systems and networks in a unified automated cloud data governance platform in a modern data stack, you can streamline access to necessary data needed for decision-making.

This allows you to quickly pivot and position your business to enter a new market or capitalize on a new opportunity.

This is supported by the same narrative as Gartner, who says that relying on tools that support multi-cloud systems is important for future business intelligence and data success.

As a result, you will be able to make timely decisions based on accurate and reliable data, which will boost your competitive advantage and better meet customer expectations.

4. Enhanced Data Compliance

Data governance can lead to enhanced compliance and business intelligence success by helping organizations ensure that their data is accurate and secure at all times.

According to a report by Malijet, the majority of survey respondents (62.4%) indicated that their company is not fully compliant with the data regulations that apply to them, such as GDPR, CCPA, and CDPA.

Given that most companies don’t exactly adhere to data compliance rules, it is alarming that many companies are not aware of the repercussions of it.

Additionally, regular auditing of data usage allows organizations like yours to identify any potential issues before they become too large.

With clear policies and procedures in place for data governance, it will help enforce the need for appropriate access control within your organization.

This will help prevent unauthorized access and manipulation of personal or confidential information, thereby ensuring compliance at all times.

Data Science Central states that compliance is an essential factor for organizations of all sizes, regardless of industry, geographical location, or profitability. It must be taken into account from the beginning stages of any analytics project and is key to sustained success and ethical business practices.

As an example, Nexen, an oil company based in Alberta, Canada experienced a major incident when it spilled over 30,000 barrels of crude oil in July 2015.

In response to this breach of regulations, the Alberta Energy Regulator (AER) immediately revoked 15 pipeline licenses held by Nexen as there were a lack of maintenance data records. This happened as a result of lax regulations set by the provincial energy regulator.

Businesses should always exercise data compliance as a long-term sustainable data strategy, especially for business intelligence success.

5. Increased Data Insights

Source: BI Survey

With clean and consistent data across systems, organizations can gain valuable insights into customer behaviors, market trends, and other areas of interest that help drive business growth.

Data governance can lead to increased insights and business intelligence success by helping organizations take better advantage of the data they have.

This is done so by having centralized control over data, which can enable your organization to ensure uniformity of data across all systems, thus providing a more comprehensive view of their operations.

Additionally, by properly managing and curating the data available to them, organizations can identify correlations between different variables, which can lead to more accurate and insightful analysis.

Data Governance Case Study: Aldo’s Successful Story

“Start with a small initiative, prove the value with a “quick-win” type mentality, and build credibility for the desire to be more data-driven. As you build that credibility and win those quick wins, you are going to garner more support from your executive management to move forward and be more data-driven.” – David Dadoun, former Senior Director Business Intelligence and Data Governance at Aldo Group

Let’s now go through a success story by Aldo group in their implementation of data governance which led to business intelligence success and enhanced insights for their business.

During his time in Aldo, David focused his data governance strategy on changing the process and improving the data quality would result in reducing manual work for inspectors.

With more available people and resources, the team was able to expand the number of inspections at no additional cost.

From what started with the manual entry of data into Excel spreadsheets, the end product of this data governance strategy was an audit app that streamlined its quality control process with standardized data entry forms, quality control over the data, and full auditing control over the data generated throughout the process.

Once data is collected through the app, the data was integrated into a cloud-based analytics platform that did away with the need for manual manipulation of data and creating PDF and Excel reports. 

As a result, David and his team were able to detect defects instantaneously on the app without having to wait two whole days for the analysis results previously.

How does this tie into business intelligence success?

David mentions that the most important part of this initiative is the 1500% in ROI and governance over their data. By integrating their data entry forms into a cloud-based platform, their data warehouse was updated in real-time, which was governed by a data warehousing team.

Through the data warehouse, analysts were able to run predictive analytics, find patterns and trends, and visualize issues with trusted data coming from a governed data source, which results in insights for all business users.

“But if you try to boil the ocean, you won’t even warm it up.” – David Dadoun

What’s best about this initiative is that it was small and inexpensive and was begun in what David refers to as “stealth governance” where an initiative is so small and harmless but can be a gradual runway for people to get used to adopting data governance practices.

Final Thoughts

The importance of data governance in business intelligence success cannot be overstated!

When your organization has trustworthy and reliable data, it will be able to make informed decisions, thereby reducing risks associated with incorrect decisions, increasing efficiency, ensuring compliance with relevant regulations, and gaining valuable insights.

By implementing a robust data governance team and program for your organization, you can ensure that the data available to you is accurate and up-to-date.

This will help to ensure the success of your business intelligence efforts, thus allowing your organization to stay ahead of the competition and remain successful in today’s ever-changing market!