Companies use and generate troves of data every year. More data is flowing in and out of a business than most realize. While every bit is important, some datasets hold greater importance than others.
With a data usage analytics platform, organizations can get a clear picture of the data environment and understand how their teams use data. Here are a few reasons to analyze your company's data usage.
Identifying Opportunities to Improve
One of the best reasons to analyze data usage in your organization is to discover new ways to improve. Maximizing productivity is always a top priority, but few companies fully consider how data plays a role in efficiency.
Understanding how the company uses data will enable you to fine-tune operations. Discover which operations are the most effective and use them as a framework to make improvements across the board. Conversely, analyzing data usage enables you to see what operations underperform. That information lets you know what needs work, giving you the tools to make changes that count.
Protect Your Most Vital Assets
Another benefit of using a data usage analytics platform is learning more about your company's most important data assets. Why does that matter? It empowers you to take steps to protect it.
Data quality and resiliency are critical. But it's even more important for the data assets your company relies on most for its success and efficiency. Use what you learn to allocate resources for monitoring and testing. You can spend more time on the data that requires your company's attention.
Save Resources
Data debt and compute costs can lead to inflated budgets and uncontrollable spending. Analyzing data usage is a fantastic way to identify areas where you can save. Discover slow queries that need optimization, perfect latency dependencies for smoother accessibility and more.
Knowing more about how your company uses data enables you to reduce costs as much as possible. You can direct your attention to bloated datasets, clean house and cut back on unnecessary resources used to manage them. It's about optimization throughout your data environment.
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