Data analysts and business professionals globally rely on Microsoft Excel spreadsheets to capture, organize, and analyze information. As the industry standard for managing key business performance metrics reports, Excel has historically served as the platform where assessments and business decisions begin to form. With the emergence of new modern, mobile-first, web-based analytics platforms, Excel will no longer be the mainstay primary resource, and instead, may likely become a secondary tool for insights. Going forward, larger volumes of structured data will be analyzed and then exported to Excel for more flexible ad-hoc uses. While Excel’s interface permits an individual of almost any skill level to work with data, it is not the ideal tool for storing and analyzing granular data such commerce transactions which can number in the millions daily for supermarkets and other fast moving consumer goods retailers.
What is Causing the Shift from Excel?
Easily Interpret Large or Blended Data
Modern analytics platforms operate at impressive speed for analysts and retailers to save considerable time. Visualizations, like heat maps in our Dayparts application, showcase easy-to-understand trends and filters provide the ability to simplify reports, displaying massive, detailed data sets in an easy-to-interpret visual for decision makers of varying technical skillsets. This allows analysts to tell a story quickly, versus investing hundreds of hours on aggregating high-level performance results. Furthermore, these stories get exponentially harder to produce when multiple data sources are involved, especially in multi-channel retail companies, to identify optimal promotions or behavioral patterns across in-store, web, mobile, social and other consumer touchpoints.
Shifting the Standard Doesn’t Sacrifice Control
While some organizations or professionals may be reluctant to rely less on Excel, especially given its affordability and ubiquity, it remains valuable for filtering, organizing, and recording historical data for custom needs. Web-based big data solutions can automate much of the cleansing, blending and updating reports formerly performed in Excel so more time can be focused on activating decisions from the data. The power of web-based Hadoop and Spark-based solutions lies not only in the ability to mine large data or apply machine learning but also automating inefficient, costly manual tasks that take humans many hours to produce. The organizations that adopt this agility to react faster and gain leverage to analyze more data, faster, and with fewer people, will undoubtedly excel.