Comparing Data Governance Tools & Software

Data Governance Software Definition: What are Governance Tools?

The term "data governance" describes procedures for ensuring the security, correctness, availability, and usability of data. Data protection is a central discipline here. Practical data governance includes the measures that employees must take in this context, the standards they must follow, and the technologies that support them during this process.

The Data Governance Institute (one of the oldest institutions for data governance best practices and guidelines) defines data governance as follows:

"Data governance is a system of decision-making rights and responsibilities for data-related processes, carried out according to agreed models, which in turn describe who can execute which actions with which information when, under what circumstances, and with what means." In simplified terms, it is about creating the appropriate foundations to use data based on clear rules in a beneficial and lawful way.

Data governance software is a tool to ensure corresponding qualities. In the business context, it helps companies to manage their data stocks effectively. Furthermore, it provides support in developing strategies, with which to considerably reduce the risks associated with poor data quality and inappropriate data handling. Such software provides transparency, control or efficient governance collaboration, and various automations that ensure appropriate data usage in the long term.

It can apply both internally and externally - that is, in internal company systems and also with partners, such as suppliers or customers. Ideally, specific governance conditions should apply everywhere where the company's data is used.

Data Governance Software vs. Data Management Software The above definition certainly sounds like data management in many places: and of course, data governance is fundamentally a form of data organization. Therefore, the corresponding terminologies are often used synonymously.

However, data governance and data management are not the same! Data management deals with the administration of the entire data lifecycle within an organization. Data governance, on the other hand, focuses more specifically on strategies and related control mechanisms that ensure data quality, correct handling of information, and their ideal availability.

It is a central component of data management. However, data governance is just one part of it, alongside other components, such as data stewardship and data warehousing. Admittedly, the boundaries are often fluid, as many of the processes are closely intertwined.

Why should companies use a tool for data governance?

Data are today a necessary resource that virtually any company can benefit from. If they are used perfectly, exceedingly targeted decisions can be made based on their data, which can enormously boost the short and long-term sales of a brand and can massively influence its competitiveness. However, making full use of data's potential is anything but simple. Among the biggest challenges are technical deficiencies, limited manpower, and a lack of data competence.

When data are considered for business purposes, only a few designated data specialists often take care of the quality, availability, and legal correctness of the relevant information. The majority of employees are left out of such considerations. This is disadvantageous and can also become dangerous, as data normally come into play at many points in the company and are therefore used by numerous people in some way. In general, it is not enough to simply store the information important for the individual departments in different folders and formulate certain usage guidelines to it. A comprehensive beneficial and risk-free use of data can hardly be guaranteed in this way.

This is precisely where the system of data governance comes into play: It centrally determines who can do what when and with which data. The control of these guidelines also falls within the remit of data governance. This is particularly important for most companies insofar as the GDPR sets tight limits when using personal data, which are, of course, almost everywhere business-critical. But also the respective company values or the branding, the production processes, the customer requirements, and other business-related facts or processes, which are generally associated with data, can assume certain standards that must be observed.

Whoever does not ensure optimal data handling here, may violate laws, possibly puts his company's reputation at risk, possibly produces inefficiently and can lose many customers. A strategically clever and well-organized data governance largely rules out such risks in connection with data.

For a suitable handling, especially in large corporations, but also in SMEs, usually a great number of to-dos need to be coordinated and completed. In the end, you must reliably pay attention to compliance with relevant guidelines. Without technical help, it is almost impossible to create such conditions. Suitable data governance solution offers comprehensive support. With it, it can be ensured that all potential benefits of a wide data usage can be claimed, without having to accept the typical quality and security risks associated with it.

How does data governance software work?

Data governance software offers various tools that enable companies to make their data usage more purposeful and secure based on certain guidelines. The solutions provide insights into data across departments, teams, and external partners. They enable the establishment and enforcement of specific rules, the monitoring of access rights and facilitate joint decision-making.

How this works specifically, or which processes the software supports, naturally depends primarily on the features it includes. Here are some typical tools.

• Data Cataloging: Data governance software allows companies to create an inventory of their data. They can thus identify which data sources are available and how they are interrelated. It also allows companies to track changes to their data over time.

• Implementation of Rules: Applied data governance is largely based on standardized rules and regulations. Everyone must adhere to these to make optimal data usage possible. Some data governance software can help establish corresponding criteria. Furthermore, these are to be implemented in individual processes of such solutions to ensure their correct execution.

• Metadata Management: Data governance software allows users to write relevant information about the structure and characteristics of their data. This specification ensures that the correct data sets can always be accessed effortlessly with the right context to guarantee appropriate usage.

• Quality Assurance: Data governance software offers tools with which companies can establish, monitor and enforce quality standards for all their data sources. This ensures that only high-quality or contextually appropriate data sets are used for business processes.

• Risk Assessment: Data governance software often includes risk analysis functionality. With their help, companies can evaluate potential dangers in connection with their data sets and, if necessary, take measures to reduce risk. This can help protect the reputation, sales, and of course also the legal security of the business.

• Privacy Monitoring: Data governance software often provides tools for monitoring compliance with privacy regulations, especially with regard to the GDPR. It thus ensures, above all, that personal data is used in compliance with the law. If this is not ensured, enormous penalties threaten.

• Access Controls: Access controls for different data types can be created with data governance software. All users, each group, or each connected application thus receive the access rights necessary for their respective tasks.

What are the advantages and disadvantages of data governance solutions?

The biggest advantage of data governance software, of course, is that it allows you to take full advantage of corresponding benefits against the backdrop of an ever-growing flood of data in a practical and safe way. What benefits arise in detail is summarized in the following.

• Increased Efficiency: Data governance software allows companies to manage and maintain correct data simply, sometimes even automated. This approach negates the enormous effort required for manual organization. Efficiency is significantly increased. Those responsible can thus spend more time analyzing data and planning specific follow-up measures.

• Improved Accuracy: With data governance software, companies can track data changes over time and ensure that always the latest versions of individual data sets are used. This ensures that there are no discrepancies in the information and that all participants access the same version of the respective set.

• Automated Compliance with Regulations: Data governance software facilitates compliance with legal or company-internal regulations through automated compliance checks. This greatly reduces the risk of non-compliance.

• Increased Security: By tracking who has access to what kind of information, data governance software contributes to protecting critical data from unauthorized access. It provides extended security features such as user authentication and encryption.

• Lower Costs: With a data governance program and correspondingly efficient processes, companies can save a lot of money that would otherwise have to be spent on manual maintenance of data sets. Also, costly duplicate processing due to a lack of synchronization between several systems is no longer an issue. Fewer errors mean less budget for corrections. Plus, potential penalties, for example in the case of incorrect use of personal data, are at best completely excluded.

However, like any software, a data governance tool unfortunately does not have only advantages. However, the typical disadvantages concern rather the use of the solutions. The following problem occur more frequently.

• Lack of personnel resources: Data governance solutions certainly take many to-dos off the hands of data managers. Nevertheless, data governance processes are still very labor-intensive even with the support of such a tool. Among other things, strategies have to be developed, new legal guidelines carefully considered, the technology maintained, and (ideally) fresh impulses given regularly. After all, everything comes together in the governance software. These and other typical tasks can hardly be done purposefully alone by IT and/or a data manager. If the necessary personnel resources are lacking, even the best program for securing data quality and correct data usage can never fully exploit its potential.

• Unsuitable data integration: It happens quite often that a data governance program is used, within which however not the complete spectrum of data is taken into account. Although the solutions sometimes give tips on data relevance and management, the responsible parties still make the decisions. Moreover, not all applications are designed for every data governance area. If not all important data are correctly integrated and processed, various difficulties may arise. Deficits in data quality and use are still the least problem here.

How do you select the right software for data quality and data guidelines?

Data governance software comes in an enormous variety of versions or with different ranges of functions, and sometimes also for specific business areas. Finding a suitable application here is anything but easy.

Taking into account the following tips, responsible persons can significantly facilitate their search. They also get more precisely to the perfect solution for optimal data quality and data guidelines.

Identification of the main users Some data governance tools are designed for general business users, others for IT staff, and still others for data science experts. So, the responsible persons should first define which group will use the tool most in their company.

The technical abilities of the respective teams are, of course, an important factor to consider here. Complex data transformations often require analysts to have profound SQL knowledge or programming experience, for example in Python. If the future users do not have a solid technical background, it is better to look at no-code programs that perhaps additionally bring extensive assistance and additional services.

Clarification of the need After it has been determined who will ultimately use the application, it should be worked out what these employees should achieve with it. When people say that they need a data governance solution, they are sometimes actually looking for a data quality program or a data integration solution. It is important to determine exactly what functions are expected from a data governance tool and for what purposes.

In fact, there are only relatively few data governance software vendors who provide solutions that are exclusively focused on data governance. Most of them also include other related functions. Those responsible here are well advised to shop carefully to ensure that they get exactly what they need. Otherwise, a lot of money might be wasted on functions that are not useful.

To get an optimal basis for research, those responsible should first consider which problems they want to solve with the data governance solution. Is it to create an option to monitor and control data changes in real time? Should management processes around data quality be automated? Do GDPR requirements need to be considered in even more detail?

Without clearly defined problems that are to be solved programmatically in the end, data governance software is just a bunch of expensive tools that can hardly be used in a targeted way.

Compatibility with existing systems Data governance tools are usually not useful as standalone solutions. They are often bundled with other applications. Therefore, an inventory of existing relevant programs or functions should be made before deciding on a software. Otherwise, there is a great risk that features will eventually be available and paid for twice.

Furthermore, of course, it needs to be clarified if the more closely considered data governance programs can cooperate optimally with the applications already established in the company. The chosen tool is ideally widely integrable and generally flexible to adapt. This can pay off in the long run as well - when the company's governance requirements change.

What do data governance tools cost?

The costs for a data governance program can vary significantly depending on the selected type of software and the integrated functions as well as the size of the company that uses the solution.

In general, data governance software ranges from small, simple tools that cost less than €100 per month, to complex analytics suites that demand more than €50,000 per year. For smaller companies or organizations with manageable requirements, minimal solutions often suffice. Large corporations, which often have to manage huge amounts of data, however, rarely get by without individual governance models, automations, and a wide scalability.

Generally, cloud programs as software-as-a-service are particularly affordable. On-premise software not only commonly requires a larger investment in the acquisition, but also specific administrative and maintenance personnel.