The term data management arose in the 1980’s when the Data Management Association (DAMA) was conceived to enhance data-related disciplines. Back then, data management was simple. Organizations would track data using punch cards and input values into a computer system. If you were really progressive, your system would be able to visually compare the input data with the information on the punch card.
However, technology has advanced significantly since the eighties. Firmly entrenched in the 21st-century, we enjoy smartphones, applications, tablets and other devices connected to the Internet of Things (IoT) that produce massive amounts of data. Data is the lifeblood of business, and all the information streaming into an organization on a daily basis makes managing data much more complicated and time-consuming. Data management today represents far more than just data storage; it represents a critical business function that is an essential piece of an effective corporate strategy.
Data management in the age of big data is about integrating data to support all areas of the business to streamline the exchange of information, and to ensure data remains trustworthy and accurate as it moves across the enterprise. While this all sounds great, developing a data management strategy isn’t enough in this data-intensive environment. We need the policies and processes in place that will ensure that data is properly leveraged for maximum competitive advantage.
The new concept of data management describes plans, policies, programs, etc. put into place to deliver and improve the value of data. With so much complex data at stake, it has become more critical than ever for organizations to develop deep knowledge of their data from a business context and to understand and quantify the value of that data to support business strategies and goals. To set guidelines for data management, data deployment and decision-making based on high-quality data, organizations need data governance.
Leveraging data today requires business users to access and apply data to swiftly perform analytics to solve business problems. A reliable data governance framework cannot just ensure that business users don’t use incorrect or low-quality data, it must also encourage accountability and assign data ownership so users have a resource to answer important questions.
Ensuring that business users have the right data available requires a modern approach to data governance. One that delivers a business-friendly perspective to provide business users complete transparency into their enterprise’s data landscape without solely relying on IT.
Data governance is about increasing the understanding of organizational data to serve the needs of both IT and diverse lines of business across the entire enterprise. Organizations need to bridge the business and IT divide by embracing a data governance approach that fosters a collaborative culture and serves the needs of both IT and diverging paths of business.
Successful governance requires collaboration among data owners and data consumers to remove any confusion as business users rely on data to perform critical business tasks and guide strategic decision-making. By engaging all parties and defining roles and responsibilities among data owners, stewards and users, this provides all stakeholders with a clear understanding of data assets.
The right approach, combined with the right solution suite to promote collaboration, enables business users to easily define, track and manage all aspects of their data assets. When business users have a complete understanding of their data, including its quality, lineage and associated terms, they can produce greater insights across the entire organization. With complete confidence in their data, business users can make strategic business decisions and extract maximum value.
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