Unleashing Your Data's Potential: How ETL is Reshaping Finance and Accounting
- Sep 11, 2023
- Extracting raw data from diverse sources;
- Transforming it into a usable format based on a set of rules; and
- Loading the refined data to a designated destination for review or other analysis.
- Power Query: While Excel reigns as king of accessible spreadsheet editing for professionals, Power Query is Microsoft’s data transformation and preparation tool that allows for ETL process creation via a low-code editor and a formula bar, either within Excel or Microsoft’s data visualization software, Power BI. With a very familiar interface, it’s easy to pick up the basics as an Excel user.
- Alteryx: A comprehensive data analytics platform. It's popular for its ability to create robust workflows that can combine machine learning with other transform operations through a simple drag-and-drop, node-based interface.
- IBM DataStage: A modernized data integration solution to cleanse and deliver data on and across cloud-based environments.
- Wdata: Like Power Query and Power BI, Wdata is part of the Workiva platform and focuses on data preparation within that ecosystem. It allows users to clean, transform and combine data before ingestion into the cloud-based tool for financial reporting and compliance.
- Programming languages like Python and/or SQL may also be used within a workflow as needed.
When to Workflow
Sample Use Cases
- Convert Messy General Ledgers: Process many general ledger text files from a legacy system for detailed account-level review. Users can put unprocessed text files in one folder, refresh the tool and output the cleaned data.
- Combine Financial Statements: Review customized metrics and results for multiple offices or locations on a standalone or consolidated basis.
- Connect Previously Disconnected Data: Calculate profit and margin by item, using sales and cost information from disparate sources.
- Sort and Filter Transactions: Extract specific transaction detail by name or memo line to help calculate monthly journal entries.
- Join Related Tables: Join customer demographic information to sales data to extract sales by state for state tax analysis.
- Stack Related Tables: Append multiple accounts receivable or accounts payable aging reports to better view customer and vendor trends over time.
- Perform Dynamic Time-Series Analysis: Review sales and purchase orders that occurred in the last 30, 60 or 90 days based on today’s date.
- Quickly Summarize Information: Refresh the workflow to summarize and organize transaction detail from various banks for cash reconciliations.
- Parse Data: Split information using simple or complex delimiter rules.
- Enforce Data Type Consistency: Ensure data types are proper, so calculations and other analyses perform as intended.
- Pivot and Unpivot Data: Flip information that isn’t normally presented in the format needed for analysis.
- Allow Seamless Review and Iteration: Enable future editing in case there is a need to debug or further enhance the process.
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Alex Cannellos is a Manager with over 5 years of public and private accounting experience.
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