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What is data governance and why does it matter?

What is data governance?

Data governance is the process of managing the data’s usability, security, availability, and quality within an organization using internally set and enforced rules and policies.

Why does data governance matter?

Data governance is a must for any organization that seeks to use their data for analysis. Data governance creates an environment where data can thrive as a source of useful insight that enables the organization to prosper. Without it, data may fail to meet the quality standards necessary for usable insight extraction or be exposed to security threats that compromise its integrity thereby putting the organization at the risk of being sued.

Data governance provides consistency across all the organization’s businesses thereby making efficient data integration possible. For instance, a supplier’s name may be specified differently in the procurement’s office and the factory’s database. During the integration of data, this may pose a challenge for the analyst who has never interacted with the supplier. Data governance ensures that there is uniformity and that the analyst doesn’t need to consult the departments generating the data in order to gain an understanding of the data.

Data governance goes beyond insight extraction and security provision by governing who within the organization can access the data and how they can access it. It is therefore important to understand what data each individual member of staff needs before setting the rules of policies of accessing the data internally.

Data Governance Goals

  • The breakdown of data silos within the organization: Lack of a centralized system that defines the policies and rules to be followed can lead to departments within an organization deploying their own transactional systems. Data governance seeks to harmonize the data structure being generated within the organization.
  • Ensuring proper use of data: It ensures that all members of staff can easily access the data they require without unnecessary delays. By limiting the data available to only what is necessary, the employees are able to easily access and extract the information that they require. Data governance also ensures that customers’ data is protected and is not misused by unauthorized employees at the expense of the customer’s right to privacy.
  • Improve data quality: Data governance ensures that there is a controlled flow of data within the organization and thus protects the quality of the data. The process of data cleansing is also simplified when the data is well organized, and all the sources harmonized in the structure of data stored.
  • Ensuring compliance: Exhaustive privacy rules and policies ensure that the data being collected by the organization is well protected.

Benefits of Data Governance

  1. Provides consistency in compliance: Data protection regulations such as EU General Data Protection Regulation (GDPR), PCI DSS (Payment Card Industry Data Security Standards) and US HIPAA (Health Insurance Portability and Accountability Act) are very strict on how data should be managed. Failure to comply with these laws can lead to the organization incurring hefty fines and damaging their reputation. Data governance takes into consideration all the requirements of the applying laws early on thereby protecting the organizations’ data.
  2. Improved quality of data: strong data governance ensures that all points of data creation function with data quality as a priority. This leads to an overall improvement of data quality within the organization.
  3. Readily available and accurate data map: by defining where the data is and how it can be accessed, data governance works like an address book for all the data in the organization. This ensures there is no data that is isolated by errors of commission or omission from the overall organization’s rules and policies.
  4. Improves data management: the code of conduct and rules established by data governance ensures that data management is made easier. It makes possible for the management of the data’s security and legal compliance.

Data that has integrity issues can not be relied on by the management for profitable insight. Therefore, any organization that is seeking to extract value from their data must first come up with a data governance system that touches on all the data they wish to use and protect. Every organization has different needs for its data and thus the need to come up with rules and policies that are customized to an organization’s needs.

Data Governance Strategy Components

Before embarking on the specific details of a data governance policy, the team involved has to first come up with a mission statement, the objectives, the evaluation metrics, and identify the people responsible for various data governance aspects. This should be shared with all the people involved so as to have a unified understanding of how the organization will treat its data.

Good data governance should include the following:

  1. Policies
  2. Rules
  3. Procedures
  4. Structures

DQLabs, an enterprise data governance platform provides a comprehensive framework that is modern and will help an organization add value to all their data as well as remain compliant. This makes it easy for an organization to set up strong data governance fast with the comfort that they are compliant with the jurisdiction’s laws. DQLabs system will help in supporting the creation of a catalog, development of policies, workflow management, and process management.

Data Governance Implementation

Implementation of data governance within an organization requires a team from different areas of the organization that understands the importance of setting the right rules and policies. The diversity of the team ensures that the policy includes the needs of as many departments as possible and thus the possibility of some employees’ data needs being ignored is reduced significantly. The inclusion also makes it easier for all members of staff to understand the policy and adopt it with ease. After coming up with the policy, it is important to train all the users of data who will be impacted to make it easier for the organization to fully implement it.


Data governance sets the rules to be followed throughout the organization while interacting with the data. Strong data governance ensures that the data is secure in storage when it’s being accessed and high quality when being created. With strict data regulations being introduced in different jurisdictions, data governance ensures that the organization remains compliant with the laws in all the jurisdictions it operates it. Data governance matters to an organization that intends to use their data for analysis and remain compliant because it ensures consistency, integrity, and security of the data. By improving data quality and proper data use, it increases efficiency within the organization and saves a lot of time for the data users. To successfully implement it in an organization, the data users should be trained on the policies of data governance to ensure they understand what will be required of them. DQLabs’ data governance tool makes it easier for an organization to set up strong data governance by providing a framework that is comprehensive and is guaranteed to increase the organization’s data value as well as ensure compliance.

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Smart Cities MDM Initiatives - Case Study Brief


Smart Cities MDM Initiatives

The City is one of the top-ranked metropolitan areas in the United States. The City’s regional economy is versatile and spread across various verticals, with a robust emphasis on life sciences, agribusiness education and research, logistics, manufacturing, aerospace, and professional services.

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DQLabs webinar


Manage Data Smarter using AI/ML with DQLabs

The combination of scarce technical skills to address data volume, trust issues and an ever increasing diversity of data types and structures is accelerating the demand to automate as many data management tasks as possible. There is already a shift in focus from “how data is stored” to “how data is used and accessed.”  As organizations further shift towards “Cloud-first approach” with still data left across silos, on-premises and third-party applications, the need of using AI/ML to manage data is a must and critical.

Organizations today need to easily know what data they have, what it means, how it delivers value, and whether it can be trusted.  This needs bringing three categories of data management features – Data Catalog, Data Quality, Agile Governance together seamlessly in one unified platform to manage data smarter.

As part of this session, Raj Joseph, CEO of DQLabs shall present how uses AI/ML to manage data smarter immediately ..not months..not years.

Webinar Highlights

  • Learn how Artificial Intelligence and Machine Learning is used to manage data smarter?
  • Improve the data inventorying efforts of humans by significantly augmenting along with AI/ML powered Data Quality
  • How DQLabs provides a simple, but unified experience in bringing all three components together  – Data Quality, Data Catalog, and Agile Governance.

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