Data Governance, and the tools supporting it, reflect the growing importance of “automated services” when dealing with the laws and regulations that have been developed to protect privacy and societal norms. Data Governance has become a necessity for organizations using the internet. It is a collection of rules, policies, and standards designed to improve Data Quality, protect the rights of individuals, and comply with the appropriate laws.
Data Governance tools help to organize and use data, and should be coordinated to support the organization’s objectives. For example, if a hospital has the goal of maintaining patient privacy, data must be managed securely while it moves through the hospital’s network, and should not be accessible to the general public. This requires an understanding of the goal (patient privacy) by hospital staff, with appropriate Data Governance software supporting the process.
For many organizations, Data Governance began as the manual documentation of information by using tools like spreadsheets. IT departments were often focused on risk mitigation in terms of regulatory compliance, or tracking data lineage to manage it and gain insights.
Concerns about regulatory compliance grew significantly after the passage of several regulations, such as:
- The California Consumer Privacy Act (CCPA)
- The Basel Committee on Banking Supervision’s standard number 239 (BCBS 239)
- Comprehensive Capital Analysis and Review (CCAR)
- The General Data Protection Regulation (GDPR)
- The General Law for the Protection of Personal Data (LGPD)
- Solvency II
- Markets in Financial Instruments Regulation II (MiFID II)
Increasing the Enforcement of Data Privacy Regulations
Businesses around the world face two conflicting pressures. They want to collect and distribute ever increasing amounts of data to increase competitiveness and profits and, at the same time, they are being legally required to implement stronger privacy and security policies.
With the passage of Europe’s General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA), it has become critical for businesses to develop and implement Data Governance systems that comply with these new laws and regulations (preferably with the help of automation).
Outdated manual approaches for Data Governance simply cannot provide the speed and accuracy needed to comply with modern privacy laws. In their 2019 Emerging Risk Monitor Report, Gartner named “Accelerating Privacy Regulations” as the primary risk that concerned executives. It has been predicted that areas with existing data privacy laws will increase their enforcement through 2021 and 2022.
Organizations using the defense of confusion or ignorance will no longer be tolerated by investigating regulators. Violations that have been ignored or punished with a slap on the wrist, will be taken more seriously, and punished more severely with more expensive fines. (Small companies will not be immune.) “True” Data Governance tools can help tremendously in complying with these laws and regulations.
The Current State of Data Governance Tools
Having to comply with various laws, regulations, and standards, the “necessity” of having a Data Governance program has resulted in a large number of vendors describing their platforms as containing Data Governance tools. In many situations, these “tools” were originally features of a larger platform (often a Data Management platform) and are focused primarily on Data Quality.
In the majority of cases, these platforms “do not include apps that help in complying with laws and regulations.” It is, however, possible to have apps created specifically for an organization’s purposes, and there are a few platforms that are designed specifically for Data Governance.
Data Governance Platforms Supporting Automated Regulatory Compliance
In response to the increase of fines for ignoring privacy laws and regulations, many organizations are seeking Data Governance platforms that include automated regulatory compliance features. By using cloud-based software to automatically protect privacy and comply with an area’s laws and regulations, companies can defend themselves from large fines.
Listed below are a few Data Governance platforms supporting automated regulatory compliance features:
- Odaseva is a platform built specifically to support Salesforce customers. This platform has provided its users with the ability to automate data compliance and privacy regulations for the General Data Protection Regulation. The Odaseva platform has allowed businesses to reduce regulatory and financial risks by automating their regulatory compliance processes. Its compliance automation features cover several industries and regions, including California Consumer Privacy Act and the Health Insurance Portability and Accountability Act.
- PeerNova’s Cuneiform Platform offers an active Data Governance platform that deals with the challenges businesses face regarding regulatory compliance. Organizations can use automated tools to meet regulatory compliance. Protecting personal data and supporting transparency are one of the platform’s themes. Dashboards can be created to monitor the flow of data through the organization, and can be used in complying with the GDPR and CCPA. PeerNova’s tools can also be used to manage metadata catalogs.
- Immuta offers a Data Governance platform that has been integrated with Databricks. “Immuta for Databricks” automates fine-grained access controls and privacy protection as part of Databricks and Delta Lake. This platform simplifies regulatory compliance privacy and security controls with automation. It enhances the ability of data compliance and governance teams to automate the processes needed for complying with the CCPA, GDPR, HIPAA, COPPA, and other regulations.
- SAS reduces risk by using automated compliance management. It provides the governance tools needed for compliance and includes validation and integrity controls. SAS Data Governance provides a common business glossary and offers a business rule repository governing data across all databases and applications.
- Compliance.AI delivers a flexible and automated approach for regulatory requirements, allowing them to be understood and addressed quickly. This flexible, automated response helps compliance teams increase accuracy, while minimizing compliance gaps.
RegTech
The term “RegTech” describes a Data Governance platform using cloud-based software to help businesses comply with financial regulations efficiently, while saving money. RegTech is also known as regulatory technology and is used primarily by financial institutions and regulators to handle complicated compliance processes through automation.
RegTech is gaining popularity, and many banks have shifted to, or are shifting to, the use of RegTech. This is, in part, a response to the increase in cyber hacks, money laundering, data breaches, and other fraudulent activities.
RegTech helps reduces the risk of noncompliance by sharing data regarding online money laundering — information a traditional compliance team would not normally be able to access. Banks are increasingly relying on RegTech technology for automating fraud checks and sending data to regulators.
Ensuring Data Quality with Artificial Intelligence
Today, businesses are competing to gain the most successful business solutions by using AI/machine learning to improve Data Quality. Artificial intelligence is being used to extract maximum value from massive amounts of data, and to enhance productivity. It is also being used to improve the reliability, accuracy, and quality of data.
The unique ability of artificial intelligence to learn from past experiences, and to adapt accordingly, can be very useful when applied to Data Governance strategies. AI can increase the reliability of data sources, smooth data integrations, and meet various government regulations.
Organizations using AI and machine learning as Data Governance tools are generally quite pleased. AI and machine learning can help in finding hidden data and can make limited predictions.
Additionally, machine learning platforms can automate tasks, such as compliance audits and data organization. Machine learning is an ideal tool for responding to regulatory compliance issues and enforcing Data Governance.
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