It is hard to keep track of trends in financial performance and performance metrics in the midst of a flood of information in your company. This could lead to costly delays and missed opportunities while you try to sort through the plethora of information.
Data management is a nebulous process that faces many challenges. These include managing relationships, identifying the data owners and managers as well as ensuring data integrity throughout its entire life. These issues are exacerbated by threats to integrity of data and trust loss which inhibits the use of data to make decisions.
Data management is a nitty gritty process that involves the integration and consolidation of information from different databases, applications, and systems. Large companies typically have numerous enterprise-level software with data stored in different places. Many of these applications employ various formats and have their own data schemas which can be difficult to navigate. This is particularly true if data engineers need to develop new SQL queries to get data.
Another issue is establishing clear roles and rights, which ensures that only authorized employees have access to data relevant to their job. This ensures data integrity and reduces the risk of unauthorized entry, and boosts efficiency of operations. It is also essential to regularly monitor, optimize, and maintain your database. This increases performance and helps avoid data silos, redundancy and the amount of manual work that IT teams must do.