Vijay Sharma — Updated On June 7th, 2023
Beginner Data Science

This article was published as a part of the Data Science Blogathon.


What is DATA by Definition?

What is Data?


Data are details, facts, statistics, or pieces of information, typically numerical. Data are a set of values of qualitative or quantitative variables about one or more persons or objects.

While running a huge enterprise it is imperative that the data by any means necessary needs to be Protected with utmost care and security, in Today’s evolving world where each and everything you look at or store is in the form of data of some sort where a few examples could be social media, phone applications, cloud storage, customer databases everything in and around us right now is susceptible to any kind of data or security breach leaving the millions and billions worth data in wrong hands.

Thus, we all as individuals are strongly encouraged to bring in a few rightful practices or governance that could help avoid such massacre of data breaches that causes it to fall into the wrong hands. So let’s all practice hard to protect, secure, and abide by all the governance designed to protect against any kind of data infringement, breach, or exploitation of millions or billions of consumers who consume data in any form in life.

Impact of Data Breaches on lives

In 2021, organizations experienced a massive increase in cyber security breaches, even exceeding 2020’s startling numbers by 17 per cent.

The benefits of remote/hybrid work are undeniable, but IT leaders must mitigate the potential new security risks.

Over the past two years, we have seen an increase in data leakage, access control, and device theft. Organizations should follow a clinical cyber security framework for remote & hybrid working environments which should be updated and modernized.

Let’s look at some astonishing number of users getting affected due to these breaches

Data Governance


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Data Needs Governance? 

A data governance framework specifies who has the right to take what actions, by using what data and in what situations. Using data governance, an organization ensures that information is used effectively and efficiently to meet its objectives by following processes, roles, policies, standards, and metrics

Big data is the new gold, and companies are not going to take it away from them. Data must always be handled with care, right from storage to usage to security. In any other case, it can be misused by the wrong individuals.

Take on Data Governance

There are laws and rules that govern how data is handled. It should be handled with care and in an unbiased manner. One of the prime examples could be that of The Cambridge Analytica scandal that had already affected the Facebook universe and Zuckerberg. Nevertheless, there are rules and laws that govern it, just as there are for anything else of similar value. With these, you can ensure that your enterprise is protected against most threats while handling large amounts of data.

Each of these principles is vital to the success of any form of data governance and discipline because they guarantee that data at any stage of sharing and consumption is not breached or hacked unethically, preserving its integrity and authenticity of it. This must be observed and taken care of by big enterprises that have multiple levels of security and therefore adhere to the norms of good data governance at the global level

An Overview of Data Governance Principles

So? What are these rules? How are they implemented? There are seven of these principles that govern how the data is used. Some of these principles include the likes of Maintaining the integrity of the data, data Transparency, Accountability and Ownership of the data, Data Audit, Standardization of Data, Change Management, Stewardship.

To understand how each of these functions, let us review them individually.

Data Governance


Maintaining the Integrity of the Data

A principle of the highest importance is integrity. It depends on the entity using your data whether or not it is being used in the appropriate manner. Data integrity is maintained if their means and goals are ethical. In all decisions about the data, the participants must be honest and forthcoming. This can include decisions about actions, impacts, constraints, etc.


In every case where data is used, proper transparency must always be maintained. To use data, as well as whose data is being used, all parties must understand how it is being utilized. Whenever there is a decision about usage or control, it must be communicated effectively to all parties involved. This will prevent any potential conflict in the future.

Accountability and Ownership of the Data

The ownership of the data must be defined. Appropriate procedures should be followed for defining access rights. Data governance applies to any data that is used across functions. As a result, data governance defines all decisions, processes, and controls related to data, i.e., its accountability.

Data Audit

Audits are permitted on every piece of data used. Any decision, control, and process about data that relates to data governance can be audited. Therefore, they must contain documentation proving compliance.

Standardization of Data

A company’s data is used by many teams. In this case, the data in one format might not be compatible with another. It is imperative that specific guidelines and rules be defined in order to standardize data.

In addition to these, there are rules for data definition, accessibility, security, and privacy.

Change Management

There may be some discrepancies in the data that require a change. As a result, there is always a risk of tainting the data. Therefore, data governance ensures proper change management activities, whether proactive or reactive. The data will include reference values, metadata, master data, and its use and structure.


Next, we must adhere to the principle of stewardship. Accountability goes hand in hand with responsibility. It is essential to appoint a data steward in any organization. All rules and regulations must be followed by the data steward. This holds true for groups of stewards as well. It is their responsibility to ensure that the data is stored and used appropriately. It is their responsibility to always follow the best practices when managing data.

Frequently Asked Questions

Q1. What are basic principles of data governance?

A. The basic principles of data governance include:
1. Data Ownership: Clearly define roles and responsibilities for data ownership, ensuring accountability for data quality, security, and compliance.
2. Data Stewardship: Designate data stewards who are responsible for data management, including data quality, metadata management, and ensuring adherence to data governance policies.
3. Data Quality: Establish data quality standards, processes, and controls to ensure data accuracy, completeness, consistency, and validity.
4. Data Security and Privacy: Implement measures to protect data confidentiality, integrity, and availability, while complying with relevant regulations and privacy requirements.
5. Data Lifecycle Management: Define processes for data creation, acquisition, storage, usage, sharing, archival, and disposal, ensuring adherence to legal, regulatory, and business requirements.
6. Data Standards and Metadata: Establish data standards, naming conventions, and metadata management practices to enable effective data discovery, understanding, and integration.
7. Data Governance Framework: Develop a structured and documented framework that outlines the governance policies, procedures, and decision-making processes to guide data management activities.
8. Continuous Monitoring and Improvement: Regularly monitor data governance activities, measure adherence to policies, and continuously improve data governance practices based on feedback and evolving needs.
These principles form the foundation of effective data governance, promoting data quality, security, compliance, and maximizing the value and utility of organizational data.

Q2. Why are data governance principles important?

A. Data governance principles are crucial for several reasons:
1. Data Quality: They ensure data accuracy, consistency, and reliability, enabling informed decision-making.
2. Compliance: They help organizations meet legal, regulatory, and privacy requirements related to data handling.
3. Security: They protect sensitive data, mitigating the risk of data breaches or unauthorized access.
4. Trust: They establish trust in data, fostering confidence among stakeholders and promoting data-driven strategies and initiatives.


Management of data can be a tedious task. Lack of guidelines and standardization can be puzzling when it comes to handling and using data. To learn how to use data effectively, guiding principles in data governance can be useful. As a result, data are effectively used, and promising results are produced.

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