FinOps Relies on Data Observability to Provide Accurate, Reliable Data

Financial operations teams, or "FinOps," need insights into data in order to make informed decisions about the financial health and performance of a company or organization. Data can provide a detailed picture of a company's revenue, expenses, cash flow, and other financial metrics, all of which are important for assessing financial performance and making decisions about future investments, budgets, and other financial matters.

As per the FinOps Foundation:

FinOps is an evolving cloud financial management discipline and cultural practice that enables organizations to get maximum business value by helping engineering, finance, technology and business teams to collaborate on data-driven spending decisions.

Having insights into data can also help FinOps teams identify trends, patterns, and potential issues that may not be immediately apparent from looking at the data in isolation. This can help them anticipate problems and take steps to address them before they become major issues. Additionally, data can also be used to measure the effectiveness of financial strategies and to identify areas for improvement.

By providing a comprehensive and accurate picture of a company's financial performance, data can help financial operations teams make more informed decisions that can ultimately have a positive impact on the bottom line.

How do FinOps teams effectively manage all their data?

Managing large amounts of data from various tools can be challenging for financial operations teams, but there are several strategies that can help them make the data more actionable and usable for better decision-making.

One strategy is to implement a data governance framework that establishes clear guidelines and policies for how data is collected, stored, and used within the organization. This can help ensure that data is consistent, accurate, and of high quality, which can in turn improve its usability and effectiveness for decision-making.

Another strategy is to leverage data warehousing technologies like Snowflake, cluster management tools like Databricks, distributed data processing tools like Hadoop, and other data tools to make data more accessible to everyone within the organization. Data warehousing can also help with data integration, data quality and data governance.

It’s also critical to have a data literacy culture in the organization, where team members are trained to understand the data, clean it, join and aggregate it from different sources and build meaningful insights from it.

However, one of the most important approaches taken by modern data teams is to use data observability. With a data observability platform, data teams can identify operational data bottlenecks that reduce scaling and performance issues, reduce cost and resource overruns through better operational data visibility, and monitor data reliability across the data supply chain. This makes it easier for FinOps teams to access, analyze, and visualize data from different sources, make the data more actionable and usable, and improve their overall data ROI.

By implementing these strategies, financial operations teams can better manage large amounts of data and make it more actionable and usable for better decision-making.

How does data observability improve FinOps efforts?

Data observability helps FinOps teams by working with greater data accuracy and data reliability by providing them with more complete, up-to-date, and actionable information about the data that is critical to their operations.

Data observability provides insights and continuous monitoring into the state, behavior, and performance of systems, applications, and data infrastructure, by providing a holistic view of data, from collection to processing to storage, across an entire distributed environment.

From a spend intelligence and cost optimization perspective, it improves resource efficiency and aligns cost to value for Snowflake environments. This is especially important for FinOps organizations since they can forecast their data spend with greater accuracy and analyze spend and chargebacks.

With data observability, financial operations teams can:

• Monitor the accuracy and completeness of data in real-time, which can help them identify and correct errors and inconsistencies before they lead to inaccuracies in financial reporting or other decision-making.
• Track and trace data as it flows through data pipelines, which can help them understand how the data is being used and identify any potential issues with data quality or integrity.
• Analyze and troubleshoot data at a granular level, which can help them quickly identify and resolve performance issues or other problems that may be impacting the accuracy or reliability of the data.
• Visually represent and make sense of large data sets, helping in understanding the data in an intuitive way.

By providing a more comprehensive and detailed view of the data, data observability can help financial operations teams better manage data with greater accuracy and reliability, which in turn can lead to more informed and effective decision-making.

To learn more about how FinOps can use data observability to improve data reliability and quality, check out the Acceldata Data Observability Platform.

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Photo by Chris Liverani on Unsplash

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