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Data Management: A necessity for those who wants to succeed with AI
Author: Rami Ballout
Feb 23, 2023
The world is in the midst of a technological revolution, with AI technologies becoming increasingly prominent across industries. Organizations are embracing AI as a tool to unlock valuable insights and make better, data-driven decisions. However, the success of any AI initiative hinges on the quality of data that fuels it. This is where proper data management practices come in.
Data Management is the underlying energy that powers and unlocks AI potentials
One must understand the importance of data management in enabling large-scale AI for enterprises. One of the challenges organizations face when it comes to data management is the sheer volume of data they generate. With so much data coming in from various sources, it can be difficult to ensure that it is accurate, consistent, and up-to-date. This is where data strategy, data governance and data architecture comes in.
Like anything else we do, a conscious and determined direction is crucial for ensuring expected targets are met. Data is not exempted from that rule, meaning a Data Strategy is required. A data strategy defines the long-term vision for the data management program and initiative. It pin-points the business case, business requirement and data vision. It also sets the target state and outlines the roadmap to transform the organization to becoming AI enabled and data-driven.
Data Governance is the process of managing the availability, usability, integrity, and security of the data used in an organization. Proper data governance practices can help organizations ensure that their data is of high quality, making it more valuable for AI initiatives. This includes practices such as establishing data standards, implementing data quality checks, and defining data ownership and accountability.
The last important pillar aspect of data management is Data Architecture. Data architecture is the design of the data structures used in an organization through business processes, which today is mostly distributed in hybrid environments. Proper data architecture practices can help organizations ensure that their data is stored in a way that is accessible and usable for advanced analytics and AI.
Use a well-defined framework that can support your Data Management Program
Numerous frameworks are available in the market, making it difficult to navigate through them. Each provider claims that their model is the superior one. When implementing a framework in your organization, it is critical to ensure that it is all-encompassing and caters to all of your requirements. Additionally, it is essential to select a framework that is built on industry best practices and incorporates the collective knowledge of top firms worldwide.
At Dyve, we are an independent agency that aims to expand our advisory services by incorporating a wide range of frameworks and applications. As part of that vision we are proud to announce that we are now DCAM certified and can support a variety of data-related initiatives and projects, including conducting a data maturity model assessment. DCAM, or the Data Management Capability Assessment Model, is a framework developed by the EDM Council to help organizations assess their data management capabilities. By undergoing a DCAM assessment, organizations can identify gaps in their data management practices and take steps to address them.
The EDM Council recently released their industry benchmark report for 2023, highlighting the importance of gauging internal capabilities against peers. The report shows that organizations that invest in proper data management practices are more likely to see success with AI initiatives.
We believe that proper data management practices are critical for organizations looking to leverage AI technologies for success. By ensuring that data is of high quality, accessible, and usable, organizations can unlock valuable insights and make better, data-driven decisions.
If you are looking to improve your organization's data management practices, including support for AI initiatives, we can help. Contact us to learn more about how we can support your organization!
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Management Consultant | Data Strategist
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