What is Data Governance?
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Making your company truly data-driven

Disclaimer: This article is not written using Chatgpt :)

I never imagined that my journey as a data engineer would eventually lead me to start a data observability company. But as I look back on my experiences, I see how gaining exposure to data has been a constant thread throughout my career, guiding me to where I am today. Serendipity is not just a fancy word but also a satisfying feeling!

As a data guy, at the beginning of my career, I focused solely on building systems to collect and process data. However, handling sensitive information was always tricky — a fact every person working in data can empathize with. I realized that simply having the technology to collect data, build ETL pipelines, and then use data for modeling & prediction was of no use when data governance principles were not enforced within an organization.

My team and I would spend long exhausting hours troubleshooting issues where the culprit would mostly be “bad data”.

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“Data is unreliable, data is missing, data is inaccurate’ was a common dialogue for us.”

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Ensuring that data is ethically and securely in accordance with industry regulations was and is of importance in every organization. Effective data governance ensures that data is consistent and trustworthy and doesn’t get misused. And being a dreamer, I always dreamt of a super simple platform that helps data engineers solve data quality issues at a lightning speed.

This is where my interest in data governance or observability grew multifold. I learned that data governance was more than just data security — it was about ensuring that data was used in a responsible and controlled manner throughout its lifecycle. In fact, I have seen the consequences of poor data governance, such as data breaches leading to business loss.

The overall concept of data governance may sound very basic but it’s often overlooked especially when companies are just starting out. Apart from failing to build a data infrastructure, they often overlook the data security aspect of their business as well.

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The importance of data governance has only increased with the rise of new technologies. As a strong advocate for healthy data governance practices, I envision a future where data is used responsibly and ethically, to the benefit of both businesses and their customers.

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Why you need Data Governance?

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If we go by the book’s meaning of it, data governance is a set of processes and policies that govern the collection, storage, use, and dissemination of an organization’s data.

Let’s go one by one on what data governance means:

• Data Quality Management: Data needs to be accurate, consistent, and free of errors. For example, an organization may implement data quality checks to validate that customer addresses are correctly formatted before they are stored in the company’s database.
• Data Security and Privacy: Implement measures to protect data from unauthorized access and breaches. Plus, ensure you’re complying with privacy regulations such as the General Data Protection Regulation (GDPR).
• Data Retention and Disposal: Establish policies for how long data should be kept and when it should be deleted or disposed of, in accordance with legal requirements and best practices. In short, it’s all about adding rules to the stored data.
• Data Access and Usage: Define who has access to data and how it can be used, in line with the organization’s data governance policies. For example, a company may restrict access to sensitive customer data to only those employees who have a valid business reason for using it.

The implementation of effective data governance policies and procedures helps organizations to avoid the costly consequences of poor data management, such as data breaches and loss of customer trust. It can also help to ensure regulatory compliance and promote the responsible and ethical use of data.

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But why do we need data governance?

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Companies have faced massive fines and damage to their reputation due to data breaches and the misuse of customer information.

Here are a few occurrences:
In 2018, a marketing and data aggregation company based in Florida called Exactis made a major mistake that had far-reaching consequences. They left a database with personal information on nearly 340 million people on a server that anyone could access. This information included people’s phone numbers, addresses, email addresses, interests, and details about their families, including the number, age, and gender of their children.

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Thankfully, a security expert discovered the breach and brought it to the public’s attention. We are talking about millions of adults’ and businesses’ data being exposed. This example highlights the importance of proper data governance and the serious consequences that can occur when personal information is not properly secured.

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By now you must have understood the importance of data governance. It’s undoubtedly relevant to all companies, regardless of size or industry. Every company collects and uses data in some way, and without proper governance, this data is at risk of being misused, lost, or stolen. In addition, new regulations like the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) require companies to be more transparent about how they use personal data. So if you are in a company or have a company, there’s no escape from enforcing good data practices. Either the hackers or the Government will be knocking on your door when it gets too late. And I personally wouldn’t wish that on anyone.

So how to implement data governance?

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Let us break down each step (we data folks like it that way):
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• Develop a Data Governance Policy: A comprehensive data governance policy outlines the guidelines, procedures, and standards for collecting, processing, storing, and using data within an organization. It should include data retention schedules, data security protocols, and privacy policies.
• Appoint a Data Governance Team: The team should include representatives from various departments within the organization, including IT, legal, and compliance. The team should be responsible for managing and enforcing the data governance policy.
• Establish Data Management Procedures: Procedures for data management should include data classification, data protection, and data backup and recovery. The procedures should be communicated to all employees and regularly reviewed and updated.
• Implement Data Security Measures: This includes measures to protect against data breaches, such as encryption, firewalls, and access controls. Data security should be a priority, and all employees should be trained on security best practices.
• Monitor and Evaluate Data Governance: Regular monitoring and evaluation of data governance policies and procedures are essential to ensure that they remain effective and up-to-date. This includes monitoring for potential data breaches, reviewing privacy policies, and conducting regular audits to assess the overall effectiveness of data governance.
• My favorite: Use simple, seamless, hassle-free data observability tools that help with improving the efficiency of data management by reducing data quality issues and boosting data reliability. There are so many good tools out there such as Monte Carlo, Databand, Acceldata. And if you’re looking for Unified platform for observability, catalog and governance tool, you can sign up for a 30-day free trial here.

Data governance and observability are essential for all organizations. Implementing effective data governance policies and procedures can help to protect against data breaches, ensure regulatory compliance, and maintain customer trust.

So, whether you’re a busy business leader or a cool data person, now is the time to start thinking about data governance. Don’t wait until it’s too late — protect your company, and your customers by taking control of your data today.

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How can data governance help improve data security?

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Data governance plays a critical role in improving data security. By implementing effective data governance practices, organizations can ensure that data is handled securely throughout its lifecycle, reducing the risk of security breaches and unauthorized access. Here are some ways in which data governance helps improve data security:

1. Data classification and categorization: Data governance establishes a framework for classifying and categorizing data based on its sensitivity and importance. This allows organizations to prioritize their security efforts and allocate appropriate resources to protect the most critical data.

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2. Access control and authorization: Data governance enables organizations to define and enforce access control policies, ensuring that only authorized individuals can access and modify sensitive data. By implementing robust authentication and authorization mechanisms, data governance helps prevent unauthorized access and data breaches.

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3. Data privacy and compliance: Data governance ensures that data is managed in accordance with relevant privacy regulations, such as GDPR or CCPA. By implementing data governance processes and controls, organizations can effectively address privacy requirements, maintain data integrity, and safeguard sensitive information.

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4. Data lifecycle management: Data governance provides a structured approach to managing data throughout its lifecycle, including data creation, storage, usage, and disposal. By defining clear guidelines and standards for data handling, organizations can minimize the risk of data leakage, accidental disclosure, or improper data handling.

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5. Data auditing and monitoring: Data governance establishes mechanisms for auditing and monitoring data activities, enabling organizations to track and detect any unauthorized access or suspicious activities. By implementing data monitoring tools and conducting regular audits, organizations canidentify and address potential security threats in a timely manner, minimizing the impact of security breaches.

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6. Data transparency and accountability: Data governance promotes transparency and accountability by establishing clear roles, responsibilities, and processes for data management. This ensures that data owners and users are aware of their responsibilities and adhere to data security protocols. By fostering a culture of accountability, organizations can reduce the risk of data misuse or mishandling.

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7. Data quality and integrity: Data governance helps ensure data quality and integrity by implementing data validation and verification processes. By establishing data quality standards and conducting regular data quality checks, organizations can identify and address any data inconsistencies or errors that may compromise data security.

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8. Incident response and recovery: Data governance provides a framework for incident response and recovery in the event of a security breach. By defining incident response procedures and conducting regular incident simulations, organizations can effectively respond to security incidents, minimize the impact, and recover data in a timely manner.

In conclusion, data governance is a crucial component of data security. By implementing effective data governance practices, organizations can ensure that data is handled securely throughout its lifecycle, reducing the risk of security breaches and unauthorized access. From data classification and access control to data privacy and incident response, data governance plays a key role in improving data security and protecting sensitive information.

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Conclusion:

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Effective data governance goes beyond data observability and cataloging tools. It also encompasses master data management, data asset ownership, and decision-making processes. Master data management ensures that the organization's core data, such as customer information or product data, is accurate, consistent, and reliable across systems. Data asset ownership involves assigning responsibility for data quality and ensuring that data is treated as a valuable asset. Additionally, data governance should include processes for making data-driven decisions, ensuring that stakeholders have access to reliable and trustworthy data to inform their choices. By incorporating these elements into your data governance strategy, you can ensure the integrity, reliability, and value of your data assets.

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In the era of data-driven decision-making, effective data governance is crucial to ensure data accuracy, security, and ethical use. By implementing policies and procedures, organizations can protect against data breaches and maintain customer trust while complying with regulations like the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) [1][2]. In countries like Australia, the United States, and South Korea, data governance is essential for businesses to prevent costly consequences and protect sensitive information [3][4][5]. Data observability tools, such as Monte Carlo, Databand, and Acceldata, can help improve data management efficiency and reliability [6][7][8]. Start thinking about data governance today to safeguard your company and customers. Decube is among the few platform to manage data observability, catalog and governance.

[1] https://gdpr.eu/[2] https://oag.ca.gov/privacy/ccpa[3] https://www.oaic.gov.au/privacy/australian-privacy-principles/[4] https://www.ftc.gov/tips-advice/business-center/privacy-and-security[5] https://www.pipc.go.kr/cmt/english/main/englishMain.do[6] https://www.montecarlodata.com/[7] https://databand.ai/[8] https://acceldata.io/

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