Data Observability: What Is It and Why Is It Important?

Data has become one of the most valuable assets in modern times. As more companies rely on insights from data to drive critical business decisions, this data must be accurate, reliable, and of high quality. A study by Gartner predicts that only 20% of analytic insights will deliver business outcomes, with this other study citing poor data quality as the number one reason why the anticipated value of all business initiatives is never achieved read more

What is Metadata Scanning?

Metadata is data that describes other data or gives context to data. You can use metadata for several tasks in business, including tagging data entries in a large volume of information for easier archival and retrieval. Metadata is also used in data visualization software applications like Microsoft’s Power BI.

Power BI is a data visualization tool that uses metadata scanning within its anomaly detection data platform. An anomaly detection data platform is software that looks for strange data behaviors that fall outside normal patterns. These anomalous behaviors may indicate suspicious activity is taking place and further investigation is warranted.

How Does Metadata Scanning Work?

Metadata scanning works by first analyzing a document or file to identify its elements. Metadata helps with this since a document’s metadata identifies what data is and what categories it belongs to. Metadata involving processes like file access can also be scanned to determine what type of access someone had to a file at a given time.

Next, metadata is extracted and sent to the cloud for further parsing. One of the reasons for sending this data to a cloud-based solution is that cloud computing can help process very large volumes of data faster.

If you were to analyze a single document with only a few pages of data, your organization would likely have no problem running parsing applications locally. For data involving many thousands of documents or more, a cloud-based solution will likely be much faster.

How Do Metadata Scanning and Anomaly Detection Work Together?

In terms of the relationship between anomaly detection and metadata scanning, the two work hand-in-hand. Metadata scanning can identify anomalies using anomaly detection solutions, and cloud-based applications can parse the results of a scan to interpret the results.

Once again, these solutions are often most beneficial to large organizations that have huge volumes or libraries of files to scan. An enterprise-level organization that has archived millions of customer records over the course of decades would have a very hard time manually scanning and comparing metadata by hand. Software like Power BI can speed these processes up and also provide an analysis of anomalies to help companies make stronger data security decisions.

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Why You Should Be Analyzing Your Company's Data Usage

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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