Stay ahead of 2024’s data trends! Explore the evolving landscape of Data Governance and Security, and learn how to safeguard your digital assets efficiently.
Table of Contents
Introduction
1. Data Monitoring and Data Lineage
2. Data Democratization
3. Adoption of AI and ML
4. Cloud-based Data Governance
Conclusion
Introduction
In this digital world, data governance is a critical tool for operating any data-driven organization. As data continues to be favored in business operations, data governance measures are required to keep all data secure, accurate, and updated.
Therefore, to remain on top of the data governance game, the data engineering teams must understand the multiple options that will aid them in developing data governance strategies that perfectly suit their respective businesses.
So to stay ahead of the technological curve, we will look at some of the top data governance trends and forecasts for 2024, which will help you understand some of the valuable insights and aid in navigating the evolving data governance landscape.
1. Data Monitoring and Data Lineage
Data monitoring and data lineage are interconnected with data governance. Data lineage aids in tracking the flow of data through various systems and modifications that ensure data quality. On the other hand, data monitoring assists in enhancing the data quality by demonstrating how data is converted and detecting errors or inconsistencies. This clear understanding of where the data originated will help the data teams to make decisions about the data pipeline and also make sure that the data flow is tracked and all the policies are adhered to. With the help of data lineage tools, data professionals can efficiently create a transparent data governance strategy.
2. Data Democratization
As organizations are becoming more data-driven, data democratization is becoming increasingly popular. By implementing data democratization, data is accessible and functional for everyone, even non-technical users. While more employees have the power to access data efficiently, enforcing data governance in this situation is equally important; the data teams must make sure that strict access management protocols are adhered to by every employee.
The next wave will see data democratization, intersecting with AI and ML; AI will depend on data to train algorithms further to drive automation and expand access to data. ML, NLP, and vision analytics will provide insight and recommendations in real-time without any manual analysis.
3. Adoption of AI and ML
In 2024, artificial intelligence (AI) and machine learning (ML) are two such prevalent technologies that will help you implement data governance in your organization. Both of these technologies have the potential to detect anomalies and inconsistencies in the datasets and further make the data more reliable for the users. AI and ML are also useful in data mapping and pattern recognition as they automate the data discovery process to detect and stop data breaches. With AutoML platforms, data professionals could easily automate the data cleansing process allowing them to spend more time solving other business problems.
4. Cloud-based Data Governance
To access and use data without the help of data engineering teams, organizations are implementing data warehouses, data lakes, and data lakehouses. Since these cloud-based data storages can be accessed from anywhere, it requires an equal approach to the data governance framework, which makes sure security measures guard this data and access controls are properly implemented. Therefore, opting for cloud-based data governance platforms such as SAP Master Data Governance, IBM Cloud Pak for Data, Alation Data Governance App, or Erwin Data Intelligence offers capabilities such as scalability, flexibility, and cost-effectiveness, eventually aiding employees in promoting faster decision-making and innovation.
Conclusion
With more research in the area of AI, ML, and other technologies, the thought leaders predict a huge shift in data monitoring and data lineage platforms in the first quarter of 2025, which will reduce manual intervention and improve data accuracy. However, looking at the current situation and the increasing complexity of data architecture, data governance comes as a savior for organizations that are looking for a solution to protect their data. By understanding the above trends, the data teams can create strong data governance strategies that aid in improving the chances of discovering and applying data to pinpoint unlimited possibilities.
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