The Basics of Excel Transform Data
“Excel transform data” signifies the transformation of disorderly Excel data into carefully structured data spreadsheets rid of errors and incomplete information. This process, commonly referred to as data preparation, is an essential precursor to any data analytics or reporting project. In Excel, there are various techniques and add-ons used for the Excel transform data process. For example, one of the most common Excel functions, VLOOKUP, often plays a critical role in the Excel transform data process by surfacing data that needs to be standardized, corrected or enriched with further information. Excel Data Tables is another helpful Excel transform data tool that supports data entry and structuring. No doubt these Excel transform data tools and techniques have been essential to Excel’s millions of power users.
When the Excel Transform Data Process Breaks Down
As data grows messier and more complex, the Excel transform process is hitting its limits in certain use cases. Though a reliable tool for financial reporting or otherwise simplistic spreadsheet work, Excel was not built to handle large volumes of data, nor complex data. It slows considerably when dealing with large datasets, lagging anywhere between 10 to 30 minutes. This can be a considerable blow to a process that is already considered the most time-consuming part of any data analytics project. On top of that, while Excel is largely considered a user-friendly tool, its endless columns and rows don’t visually surface errors or outliers. Users must rely on Excel functions or their own knowledge of the data, which can let errors slip through.
In place of the Excel transform data process, many Excel users are now turning to modern data preparation platforms such as Alteryx for all or some of their data preparation use cases. This was the case for PepsiCo, a current Alteryx customer. Under the Excel transform data process, PepsiCo’s CPFR team was struggling to quickly turn around sales forecasting reports that would determine how much and what quantities of product was needed for their largest retailers. Their huge volumes of inventory data were breaking under the Excel transform data process, not to mention the dollars wasted in the time they lost or the occasional error that slipped through. After using Designer Cloud, the PepsiCo CPFR team saw tremendous results—reporting time has been reduced by 70% and build time has been reduced as much as 90%. To learn more about why PepsiCo’s use case was a better fit for Trifacta than the Excel transform data process, click here.
Trifacta: A Modern Replacement for the Excel Transform Data Process
Though analysts have relied on the Excel transform data process for decades, as the size, variety, and pace of data accelerates, certain use cases have begun to outgrow the Excel transform data process. Data preparation platforms such as Designer Cloud offer new approaches to preparing data that alleviate Excel transform data bottlenecks. The Designer Cloud data preparation platform presents representations of data in the most compelling visual profile, and simply selecting certain elements of the profile immediately prompts intelligent transformation suggestions. We’d love to chat with you about your use case to see if Designer Cloud is a better fit than the Excel transform data process.