What is data governance (and do I need it)? (2023)

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Data governance is a requirement in today's fast-paced and highly competitive business environment. Now that organizations have the ability to capture vast amounts of diverse internal and external data, they need a discipline to maximize its value, manage risk, and reduce costs.

Was ist Data-Governance?

Data governance is a collection of processes, roles, policies, standards, and metrics that ensure the effective and efficient use of information to enable an organization to achieve its goals.Establishes the processes and responsibilities that ensure the quality and security of data used in a company or organization. Data governance defines who can take which actions with which data in which situations and with which methods.

A well-designed data governance strategy is essential for any organization working withbig data, and explain how your organization can benefit from unified and shared processes and responsibilities. Business drivers highlight what data needs to be carefully controlled in your data governance strategy and what benefits can be expected from those efforts. This strategy will be the basis for yoursData-Governance-Framework.

For example, if this is a business driver for your data governance strategyensure privacyWhen it comes to health-related data, patient data needs to be managed securely as it flows through your organization. Retention requirements (e.g. history of who changed what information and when) are defined to ensure compliance with relevant regulatory requirements such as:DSGVO.

Data governance ensures that data-related roles are clearly defined and that responsibilities and accountabilities are agreed across the organization. A well-planned data governance framework covers strategic, tactical, and operational roles and responsibilities.

What data governance is not

Data governance is often confused with other closely related terms and concepts, includingdata managementjmaster data management.

Data governance is not data management

Data management refers to managing the requirements of an organization's entire data lifecycle. Data governance is the core component of data management and brings together nine other disciplines such as data quality, reference and master data management, data security, database operations, metadata management, anddata storage.

Data governance is not master data management

Master Data Management (MDM) focuses on identifying the most important units of an organization and then improving the quality of that data. It ensures you have the most complete and accurate information on key entities such as customers, suppliers, medical providers, etc. Because these entities are shared across the organization, master data management is about merging fragmented views of these entities into a single view—a discipline that transcends data governance.

However, without proper governance, there is no successful MDM. For example, a data governance program defines the masterdata models(what is the definition of a customer, product, etc.), detailed data retention policies, and define roles and responsibilities for data creation, data retention, and access.

Data governance is not data management

Data governance ensures the right people are assigned the right data responsibilities.data managementrefers to the activities required to ensure that the data is accurate, under control and easy for the relevant parties to discover and process. Data governance is primarily about strategy, roles, organization and policies, while data stewardship is about execution and go-live.

Data stewards take care of data assets and ensure that the actual data conforms to the data governance plan, is linked to other data assets, and has control over data quality, compliance, or security.

Benefits of data governance

An effective data governance strategy offers many benefits to organizations, including:

  • A shared understanding of the data.— Data governance provides a consistent view and common terminology for data while individual business units retain appropriate flexibility.
  • improvement of data quality— Data governance creates a plan that ensures data accuracy, integrity and consistency.
  • Datenkarte— Data governance provides an advanced way to understand the location of all data related to important entities, what for . Like a GPS that can map a physical landscape and help people navigate unfamiliar landscapes, data governance makes data assets actionable and easier to connect to business outcomes.
  • A360 degree viewby each customer and other business entities— Data governance creates a framework for an organization to agree on a “single version of the truth” for critical business units and to provide an appropriate level of consistency between units and business activities.
  • consistent compliance— Data governance provides a platform to meet the requirements of government regulations such as the EU General Data Protection Regulation (GDPR), the US HIPAA (Health Insurance Portability and Accountability Act).
  • Improved data management— Data governance brings the human dimension to a highly automated, data-driven world. It establishes codes of conduct and best practices in data management, ensuring that concerns and needs that extend beyond the traditional domains of data and technology, including areas such as legal, security and compliance, are consistently addressed.

Cloud data governance

More and more companies and organizations are realizing the benefits of moving some or all of their data storage and processesCloud-IntegrationStrategies uiPaaS, the need for effective data governance is increasing at scale.

Migrating to the cloud is all about delegating certain tasks to a third party, such as B. infrastructure management, application development, security, etc. lives in a certain place or country. Additionally, cloud-first strategies typically encourage decentralization, allowing business units or workgroups to deploy their own system independently, which can result in an uncontrolled flood of data.

This is where governance finds its place. First, a strategic data governance plan is critical to migrating content to the cloud. Regardless of whether an organization is moving to a hybrid data model or fully to the cloud, thedata migrationThe process enjoys the same benefits as an overall data governance plan, and the migration itself becomes more efficient and secure.

Additionally, moving data processes to the cloud adds a layer of complexity around security and access. While a fully on-premises data solution still requires a robust data governance strategy, stakeholders appreciate the value of data governance especially when that data is moving through the cloud.


To find the right data governance approach for your business, searchOpen Source, scalable tools that can be quickly and inexpensively integrated into a company's existing environment.

Also acloud-based platformThis allows you to quickly connect to robust features that are inexpensive and easy to use. Cloud-based solutions also avoid the overhead required for on-premises servers.

As you begin to compare and select data governance tools, focus on selecting tools that will help you realize the business benefits outlined in your data governance strategy.

These tools should help you:

  • Collect and understand your datathrough discovery, profiling and benchmarking tools and capabilities. For example, the right tools can automatically detect personal information like a social security number in a new record and trigger an alert.
  • Improve the quality of your datawith validation, data cleansing and data enrichment.
  • Manage your datawith metadataETLjELTand data integration applications so that data pipelines can be tracked and tracked with end-to-end data lineage.
  • Control over your datawith tools that actively check and monitor.
  • Document your dataso that it can be enriched with metadata to increase its relevance, searchability, accessibility, linkability and compliance.
  • Empower the people who know the data bestcontribution todata managementTasks with self-service tools.

Talend understands data governance and offers useful cloud-based tools that can help organizations of all sizes move from uncontrolled data to active data governance. by Talenddata quality, data and metadata management anddata management toolsThey are robust and easy to use, so you can quickly and effectively meet your data governance needs.

Data governance is not optional

Companies today have incredible amounts of data about customers, suppliers, patients, employees and more. When this information is properly used to better understand the market and its target audience, a business will be more successful. The same data governance also ensures that this data is trusted, well-documented, easy to find and accessible within your organization, and that it is kept secure, compliant, and confidential.

Ensure your organization is able to maximize investments in data governance and minimize the risk of data breaches. Check out oursData Governance Solutionswhen you're ready to go

Ready to get started with Talend?

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What is data governance (and do I need it)? (1)What is data governance (and do I need it)? (2)

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What is data governance and why do you need it? ›

Data governance (DG) is the process of managing the availability, usability, integrity and security of the data in enterprise systems, based on internal data standards and policies that also control data usage. Effective data governance ensures that data is consistent and trustworthy and doesn't get misused.

Do we need data governance? ›

Data governance is important because it brings meaning to an organization's data. It adds trust and understanding to an organization's data through stewardship and a robust business glossary, thus accelerating digital transformation across the enterprise.

What is meant by data governance? ›

Data governance means setting internal standards—data policies—that apply to how data is gathered, stored, processed, and disposed of. It governs who can access what kinds of data and what kinds of data are under governance.

What happens if you don't have data governance? ›

A lack of clear data governance results in poor quality data, which inhibits the adoption of new technologies that procurement professionals require to evolve their organisations so it's fit for the future.

What are examples of data governance? ›

An example of data governance is when an organization adopts a data governance initiative in order to: define data models, distribute roles and responsibilities regarding the use of data, retention of old and new data — particularly sensitive data — create data standards, implement protection and establish security in ...

What are the five areas of data governance? ›

The 5 Principles of Data Governance
  • Accountability. Accountability is of the utmost importance in any successful data governance process. ...
  • Standardized Rules and Regulations. ...
  • Data Stewardship. ...
  • Data Quality Standards. ...
  • Transparency.
Jan 2, 2018

Is everyone responsible for data governance? ›

Everyone in your enterprise has a responsibility in data governance processes. Data governance includes securing your data, organizing it, defining the access permissions, and determining the way your organization uses data.

How do you ensure data governance? ›

Let's take a look at the seven key steps for implementing data governance:
  1. Identify and Prioritize Existing Data. ...
  2. Choose a Metadata Storage Option. ...
  3. Prepare and Transform the Metadata. ...
  4. Build a Governance Model. ...
  5. Establish a Process for Distribution. ...
  6. Identify Potential Risks. ...
  7. Constantly Adapt Your Data Governance Framework.
Dec 15, 2021

What are data governance tools? ›

A data governance tool is defined as a tool that aids in the process of creating and maintaining a structured set of policies, procedures, and protocols that control how an organization's data is stored, used, and managed.

What are the basic data governance principles? ›

Data must be recognized as a valued & strategic enterprise asset. Data must have clearly defined accountability. Data must be managed to follow internal & external rules. Data quality must be defined & managed consistently across the data life cycle.

Why is data governance so hard? ›

Challenges to Data Governance

Conflicting data flows and a lack of data ownership can lead to a lack of trust in information, he said, and an inconsistent understanding of that information. According to Dye, challenges come from a variety of sources: Limited funding and resources, or competition for them.

What is an example of poor data governance? ›

The Securitas breach is a classic example of bad data governance and one of many high-profile cases of publicly exposed S3 buckets. But it's important to remember that permission issues aren't just restricted to Amazon S3. They can put data at risk in virtually any type of storage repository.

What is the core of data governance? ›

Data governance is a collection of processes, roles, policies, standards, and metrics that ensure the effective and efficient use of information in enabling an organization to achieve its goals.

What is data governance vs data management? ›

In the simplest terms, data governance establishes policies and procedures around data, while data management enacts those policies and procedures to compile and use that data for decision-making.

What are the goals of data governance? ›

Data Governance Goals:

Foster an organized system to manage data effectively and ensure clean, consistent data. Ensure use of standard, repeatable processes for data entry and reporting. Support a culture of informed decision making based on clean, consistent and understandable data.

What is good data governance framework? ›

A data governance framework helps ensure that your policies, rules and definitions apply to all the data in your organization. It helps you deliver trusted data to individuals in many roles, from business leaders to data stewards and developers. A framework also allows you to introduce self-service tools.

Who owns the data in data governance? ›

One of the tenets of Data Governance is that enterprise data doesn't “belong” to individuals. It is an asset that belongs to the enterprise. Still, it needs to be managed. Some organizations assign “owners” to data, while others shy away from the concept of data ownership.

Who is the drivers for data governance? ›

Data-driven decision making

The need for data governance in this case is largely driven by the amount of data generated by businesses in the past decade and how data is being used to drive key agendas for organisations.

What is the first step in data governance? ›

Determining the strategy for having an effective data governance team in an organization is the first step in developing a data governance structure. This strategy can be started by writing a data governance charter with the assistance of stakeholders and those involved in the project who work at the company.

Is data governance a software? ›

Companies use data governance software to ensure regulatory standards are met, in effect improving security and organization.

What's the biggest data governance mistake to avoid? ›

  • Creating a “Data Governance Project Team” ...
  • Having inconsistent data. ...
  • Unclear objectives. ...
  • Insufficient tools or skills. ...
  • Too much focus on tools.

What are two 2 benefits of data governance to organization? ›

The most notable benefits of data governance include providing improved data quality, lower data management costs, increased access to needed data across the organization, lower risks of errors being introduced, and ensuring that clear rules regarding access to data are both set, enforced, and adhered to.

How do you implement data governance? ›

Let's take a look at the seven key steps for implementing data governance:
  1. Identify and Prioritize Existing Data. ...
  2. Choose a Metadata Storage Option. ...
  3. Prepare and Transform the Metadata. ...
  4. Build a Governance Model. ...
  5. Establish a Process for Distribution. ...
  6. Identify Potential Risks. ...
  7. Constantly Adapt Your Data Governance Framework.
Dec 15, 2021

What are key data governance principles? ›

Typical universal goals of a Data Governance Program:

Train management and staff to adopt common approaches to data issues. Build standard, repeatable processes. Reduce costs and increase effectiveness through coordination of efforts. Ensure transparency of processes.

How data governance improve data quality? ›

Data Quality is the degree to which data is accurate, complete, timely, and consistent with your business's requirements; whereas Data Governance is the process of organizing, securing, managing, and presenting data using methods and technologies that ensure it remains correct, consistent, and accessible to verified ...

What is the most important benefit of a governance? ›

Governance helps you to always act in the best interests of the business. More specifically, it can improve the performance of your business, help it become more stable and productive, and unlock new opportunities. It can reduce risks, and enable faster and safer growth. It can also improve reputation and foster trust.


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