Data governance is a set of processes that ensures that important data assets are formally managed throughout the enterprise. Data governance ensures that data can be trusted and that people can be made accountable for any adverse event that happens because of low data quality. It is about putting people in charge of fixing and preventing issues with data so that the enterprise can become more efficient.
Data governance also describes an evolutionary process for a company, altering the company’s way of thinking and setting up the processes to handle information so that it may be utilized by the entire organization. It’s about using technology when necessary in many forms to help aid the process. When companies desire, or are required, to gain control of their data, they empower their people, set up processes and get help from technology to do it
In general, most organizations have proliferated Excel use. When looking at business intelligence, many people use Excel to manage information and to analyze data. The issue arises when people use Excel as the key entry point of information access, meaning that individuals control, edit, and make changes to data used to plan and identify business performance and/or opportunities.
Because of the lack of validation within Excel, the ability to develop analyses based on incorrect assumptions and data manipulation are quite large. Consequently, organizations require the ability to use Excel and to interact with data, while still being able to validate the data being used to ensure proper data governance and overall compliance.
Excel Dashboard allows users to drill through to the original information without having to access a database or have an understanding of where the data resides. The overall ability to access and validate original data provides an asset to business users by allowing them to understand the context of information and how it interrelates with overall business information. When looking at compliance specifically, the ability to meet regulations and to maintain data integrity can have legal implications. Therefore, organizations require ways they can correlate Excel based analyses with original operational data to confirm that information has not been changed or compromised.