Guide: Data Governance

Data Governance Tools

Data is one of an organization’s most significant elements. When a company has a good system for capturing and processing data, that company is already leaps and bounds ahead of businesses with inferior data collection and utilization practices.

How well data gets managed in terms of consistency, management, and ownership will determine its overall performance. Effective data governance involves management and responsibility across the company. One way of handling these data is using data governance tools.

This article will discuss the following:

This chapter is part of our Essential Data Governance Guide

What are Data Governance Tools?

In the face of so many interdependencies, many organizations struggle to adopt an effective data governance strategy. More firms use solutions to assist, manage, retrieve, and safeguard data daily to make this asset process easier. These technologies, also known as data governance solutions, aid in the automation of workflow and the organization of enormous amounts of data.

 

Data governance tools include a framework of rules, procedures, operations, and metrics to assist businesses in avoiding risks and liabilities, as well as a series of tools for extracting the most value from data. It also has control over how data is used, archived, and managed. It enables everyone in a company to use information responsibly, productively, and efficiently.

Why Do You Need Data Governance Tools?

Data governance tools provide mechanisms to manage, preserve, and update data while assuring quality and compliance within an enterprise-specific framework as the availability and access to real-time data grows. These procedures ensure accessibility, consistency, integrity of information, data security, and transparency, allowing information to be used swiftly across the business.

 

Listed below are just some of the benefits of having data governance tools.

 

  • Make more competent corporate decisions: easily accessible and well-managed data quickly provide reliable insights for major organizational choices.
  • Improved data quality: Although data cleansing may be necessary to ensure quality, data governance adhering to internal data uniformity ensures accuracy and utility in informed decision-making.
  • Enhanced master data management: Every industry has its own rules, and non-compliance frequently results in large fines. Data governance ensures compliance with legislation while also safeguarding security and privacy.
  • Interoperability of data is improved: From inventory levels to customer satisfaction, data provides vital information on all aspects of a firm. In terms of production rate, quality of products, and resource utilization, leveraging and utilizing insights derived from this data can increase operational efficiency.
  • Superior data lineage: Data governance gives a holistic perspective of where it is stored and utilized. Plus, it controls the rights that govern how and when data is accessible.

 

Although an effective data governance program is founded on meticulous planning and deep insights from business operations personnel, data governance tools are just as crucial as any other element. Finding a way to organize and manage data from various sources of entry guarantees that the company benefits from consistent, high-quality data.

Choosing the Most Appropriate Data Governance Tool

While many data governance tools serve typical management duties, specific tools for governance programs, policy management, and data quality have evolved.

 

The first step for each organization looking for the best solution is determining the use case and describing general business priorities. Understanding the data governance needs and business KPIs can make the best possible decision. Moreover, one should consider the following questions below.

 

  • Is the company more likely to use on-premise or cloud-based operating systems?
  • Is it critical for the workflow to have a self-service admin dashboard?
  • How many interconnections does the company currently have in place? Will they require a tool that can connect to each app? If so, to what extent?
  • Does the company require a tool that will allow them to work with big amounts of data from various sources?

 

Determine which features are required to acquire a better understanding of which tool will best fulfill company needs. The following is a list of features:

 

  • Keep an eye on the company’s strategies.
  • You can track metrics and effectiveness.
  • Manage important assets like data structures and glossaries.
  • Data management tasks such as change history and lineage information get tracked and managed.
  • Create a workflow and keep track of user permissions.
  • Keep track of the work’s progress.
  • Metadata creation and management.
  • Deliver classification and lifecycle management for documents.
  • Assigning responsibilities and standards to governance.

 

Examining and matching each business need to a targeted product feature will help identify the most effective tool in accomplishing the objectives and plans.

Data Governance Tools in the Market

Once the aims of data governance policies are determined, you should begin exploring data governance technologies that suit company frameworks and operations. The following are some of the most important data governance technologies and how they can aid a company.

Talend

Talend’s data governance product gets described as a single cloud platform for trusted data. This data governance platform has a lot to offer, from metadata management to enhanced data lineage. Not only that, but this data governance solution makes cloud data integration a breeze. One can also use the open-source version of this program to introduce and accustom the data operations team to it.

Collibra

Collibra is a cross-functional data governance platform that automates data operations and keeps cross-functional teams on the same page. While no single solution can fit the demands of all businesses, Collibra has been developed to provide the needs of frameworks with a wide range of data governance standards.

IBM

Data cataloging is another wonderful feature of IBM’s technology. Machine learning algorithms fuel these data catalogs, resulting in speedier metadata gathering and data asset growth. You can be confident in the security of data and the users’ privacy since IBM’s cutting-edge technology backs its security infrastructure.

Informatica Axon

Informatica Axon Data Governance is an automated data governance solution that allows users to access curated data quickly. The platform ensures that teams can identify, access, and comprehend the required data through a curated marketplace. Axon also allows for creating data dictionaries, which provide a consistent source of business context across numerous tools.

Egnyte

Egnyte provides a content protection, regulation, and collaboration solution that manages an organization’s files no matter where they are stored. Through a unified solution, the technology provides a variety of access control capabilities, lifecycle management, data protection, compliance, business process management, and API connection. Locating valuable and sensitive data, compliance automation, and more are part of the information governance capability.

Claravine

Customers can use Claravine’s Data Standards Cloud to drive internal standardization across data sets, classifications, and sources. By using referenceable fields and descriptions, the solution allows for the formulation of specific criteria. Users may audit, monitor, and standardize data and automatically validate tag placement and setting across landing pages to maintain standards.

 

Claravine boasts the ability to assign the appropriate responsibilities and permissions to users or groups using standard and custom settings and evaluate, audit, and visualize platform activities using dashboards.

Atlan

Data cataloging and discovery, data quality and profiling, data lineage and governance, and data exploration and integration are all capabilities of Atlan’s data workspace platform. For developing a shared understanding of data, the software includes a Google-like Search tool, automatic data analysis, and an accessible business lexicon. Users can manage data usage and adoption throughout an ecosystem using granular governance and access restrictions no matter where the data flows.

Ataccama One

Ataccama ONE is a full-featured data management and governance platform with master data management and data quality features. The solution includes a user interface centered on machine learning and a data processing engine that handles data processing, business rule evaluation, and matching and combining rules. The platform supports many data integrations, domains, and a variety of integrations.

Oracle

Oracle Enterprise Metadata Management is a metadata management platform that can gather and catalog data from various sources. The solution provides data lineage, evaluation, semantic definition, and semantic usage analysis for any metadata asset inside the catalog and interactive searching and browsing of the information. Advanced algorithms in Oracle Enterprise Metadata Management weave together metadata assets from each of the suppliers.

Satori

Satori, the DataSecOps platform, is helping organizations with their quest for an agile data governance operation. This is done by capabilities such as data access controls that are simple to apply by data owners without writing any code. In addition, Satori enables organizations to apply fine-grained access control in a simple way universally across all data stores.


To learn more about Satori, visit our product page, or schedule a demo.

Conclusion

The need for practical and actionable data is ever-evolving. Therefore, as the demand for and availability of big data grows, so does the need for data governance, protection, and regulation.

 

As you can see, security for your data is just as important as the data itself.

 

From meta-data collecting to the level of data security users demand, and from data storage procedures to data visualization approaches, each aspect influences the technology we choose.

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