Introduction
As we head into 2023, it’s clear that enterprise data management (EDM) is more important than ever. With businesses producing and storing vast amounts of data, it’s crucial that they have effective systems in place to manage and analyze this information. In this blog post, we’ll explore some of the key trends that we expect to see in the enterprise data management space over the next year.
Data Governance Will Be a Top Priority
One of the biggest trends in enterprise data management for 2023 will be a renewed focus on data governance. With the proliferation of data and the increasing importance of compliance and security, companies are realizing that they need to take a more proactive approach and employ a data management strategy to manage their data. This means establishing clear policies and data quality management procedures for how data is collected, stored, and used, as well as assigning responsibility for overseeing these processes.
At the same time, organizations will be looking for ways to automate many of these governance tasks to reduce the burden on IT and other staff. Tools like data catalogs, which can automatically scan and classify data, will become increasingly important in this context.
Data quality management and Data Integration Will Become More Complex
As more data sources are brought online, the task of integrating this information will become more complex. Companies will need to employ a data management strategy and be able to seamlessly bring together data from different sources, including structured and unstructured data, and data from both internal and external sources.
To achieve this, we expect to see an increase in the use of enterprise data management and data integration platforms, which provide a centralized hub for managing data integration tasks. These data quality management platforms will be designed to work with a wide range of data sources and will offer advanced features like data mapping, data profiling, and data transformation.
Cloud-Based EDM Will Become More Prevalent
Cloud-based enterprise data management has been on the rise for several years now, and we expect to see this trend continue in 2023. With the increasing availability of cloud-based enterprise data management and computing resources, more companies will be looking to move their data management systems to the cloud.
Cloud-based enterprise data management offers a number of advantages, including increased flexibility and scalability, reduced hardware and maintenance costs, and the ability to more easily share data across multiple locations and devices.
AI and Machine Learning Will Play a Bigger Role
AI and machine learning technologies have already made significant inroads in the enterprise data management space, and we expect to see this trend accelerate in 2023. These data quality management technologies offer powerful tools for analyzing and managing large amounts of data, including advanced analytics, predictive modeling, and natural language processing.
One key area where we expect to see AI and machine learning have a big impact is in data quality management. By analyzing large amounts of data, these enterprise data management technologies can identify patterns and anomalies that might be missed by human analysts, helping to improve data accuracy and reliability.
Data Privacy and Security Will Be a Key Concern
Data privacy and security will continue to be a top concern for businesses in 2023. With high-profile data breaches and cyber-attacks becoming more common, companies employing data management strategies will need to take a proactive approach to protect their data.
This will involve implementing a range of security measures for the enterprise data management system, including encryption, access controls, and monitoring tools, as well as ensuring compliance with data privacy regulations like GDPR and CCPA.
The Rise of the Data Democratization Movement
Finally, we expect to see a growing movement toward data democratization in 2023. This involves giving more people within an organization access to data, with the aim of enabling more informed decision-making and driving innovation, and data management strategy.
To achieve this, companies will need to develop data quality management systems that can provide secure and controlled access to data, while also ensuring that data is accurate and reliable. This will require a careful balance between openness and control and will require close collaboration between IT, enterprise data management experts, and business teams.
Conclusion
Sophisticated enterprise data management tools and technologies, advanced models, and effective data governance practices may empower the next generation of data-management capabilities, simplifying the administrative burdens that companies currently encounter.
It is, therefore, essential to strike the right balance in utilizing these resources, as it is crucial to identify relevant opportunities, driving visibility, build reliability, and achieve scalability within an organization. Chief Data and Analytics Officers play a critical role in managing the vast amount of data available and must skillfully balance the organizational needs and strategies to ensure effective management.
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