Data is already regarded as one of the most important commodities in the world. With the ever-increasing use of connected personal devices and broadening internet penetration, virtually everyone produces and there are many parties interested in getting it.
Digital data goes beyond information about individuals, objects, projects, or organizations. It is a highly valuable asset that does not only represent something at a point in time but can be used to make forecasts, generate new information, facilitate inventions and innovations, and serve various other purposes. Conversely, data can be used by threat actors for felonious goals or to find weaknesses in an organization.
That's why there is a need for data to be governed properly and intelligently. With the deluge of data in the modern era, it is crucial to have a systematic way of storing, enabling access to, maintaining, and, most importantly, securing data.
The need for data governance
The process of data management-with emphasis on its availability, integrity, usability, and security-is called data governance. It is aimed at ensuring the effective and secure management of digital information. Regardless of size or type, organizations that use data need proper data governance to address the risks that come with modern data handling. A good data governance framework ensures the optimum utilization of data, resulting in seamless collaboration and accountability among stakeholders.
Data governance has several aspects, but they can be summed up in three key points: integrity, availability, and security. Integrity means that there should be processes to ensure data completeness, consistency, accuracy, timeliness, and relevance. Availability is about having a robust system for data lifecycle management, access and usage controls, data stewardship, and general governance strategies to make sure that data is complete and available when needed. Lastly, data security entails the implementation of appropriate measures for privacy, confidentiality, and security. An organization's data handling should comply with all applicable regulations and there has to be sensible monitoring and auditing procedures.
These pertain to standard data governance, though. They do not have specific methods to address new challenges in the modern setting, especially with the rise of cloud computing, hybrid IT setups, and other sophistications that come with the use of new IT technologies. To keep up with the new data management paradigm, it helps to have data governance applications to target specific concerns.
Applications for efficient data governance
The data governance applications listed and described below represent specific functions that help achieve good data governance. They do not necessarily point to specific solutions or apps. Two or more of these functions can be incorporated into one data management solution.
Quality monitoring - One challenge in data management that will always be present no matter how advanced technologies become is quality, especially in terms of relevance, accuracy, and completeness. Good data governance requires the assurance that the data an organization uses is of high quality, so it is crucial to have the means to examine and monitor data quality through validation checks, rules, and alerts.
Classification, tagging, and cataloging - After ascertaining accuracy and completeness, data also needs to be properly categorized, labeled, and cataloged. These procedures are important to make sense of the massive amounts of raw data collected. Data is only usable if it is identifiable and easily accessible. It would be virtually impossible to use data if users have to repeatedly scour through available data to find the specific details they need for a specific purpose.
Metadata management - Concerning data tagging and cataloging, there are apps designed to make it easy to add or modify metadata for specific data or datasets. Metadata provides context for the collection of data an organization has. It may include details such as the origin of the data, its structure, relationships, and intended purpose, among others.
Data lineage monitoring - There are data management applications created to focus on the history of data. They can show the movement of data from its source to its various destinations and the procedures the data went through. These apps are useful in identifying the transformations data has undergone as well as its dependencies.
Access control and security - Data governance requires rigorous access control and security to protect the integrity of information. This entails a carefully planned definition of rules, permissions, and the deployment of effective security controls to protect data. Only those that have the right permissions should be allowed to access data usually under a role-based arrangement.
Compliance management and data policy enforcement - Data nowadays is subjected to various regulations such as HIPAA and GDPR. There are many rules designed to make sure that data is safe from hacking, privacy violations, and other cyber attacks. Also, organizations have their respective data policies. As such, it is important to have a way to monitor regulatory compliance to avoid legal entanglements. At the same time, it helps to have an app that can monitor the enforcement of in-house data policies.
Data stewardship - Data governance does not have to be the job of just a single or a few people. The task can be collaboratively undertaken with the help of data stewards. These can be data owners and stakeholders who assume the responsibility of overseeing data quality, usage, and security.
Data retention and disposal - Most data users are unaware of the need for proper data retention and disposal policies. These two are crucial points in data governance, as it is important to have clear policies on which data to retain and which ones to dump. It helps to have a tool that makes it easy to implement sensible data renewal and secure disposal. Data storage devices have capacity limitations. It is impossible to keep all data so there is a need to erase some of them after identifying the right data to retain. On the other hand, careless data disposal can result in data loss or the exposure of sensitive data to threat actors.
Change management - Another crucial data governance application focuses on the changes data goes through. Data change management apps simplify the tracking of data modifications, transformations, and other changes to verify accuracy and minimize the impact of changes.
Communication and collaboration - The use of data, especially by large organizations that operate in different geographic locations, is not as simple as transmitting data to the intended recipients. The transmission or sharing has to be a secure and timely process, which can be quite difficult if there are numerous participants and platforms involved. A robust communication and collaboration app can address this challenge.
Data governance reporting - It is advisable to have a reporting system or a dashboard regarding data governance to have a comprehensive view of data governance in an organization. This dashboard or report can show compliance metrics, data quality evaluations, and other information relevant to data governance.
New data governance challenges
Data governance is expected to become more difficult mainly because of the explosion of data volume growth, the complexity that comes with the utilization of various data forms and multiple computing platforms, the imposition of more regulations, and the evolution of cyber threats. For organizations to achieve good data governance, it is crucial to have the right tools or functions to ascertain data integrity, availability, and security.
The security aspect is particularly important given the unpredictability of threats and the increased sophistication of cybercriminals. Security is a crucial concern since data attacks can result in data loss or corruption that affects the integrity and make data unavailable, especially in cases of ransomware and virus infections.
Data will continue to be a vital commodity if not the most important commodity in the modern interconnected digital world. Hence, proper data governance is a must. Organizations need to gain data governance proficiency and take advantage of all suitable tools to manage data as efficiently as possible.
