Can Microsoft Excel Handle Big Data? What works of Big Data we can do with MS Excel and how? MS Excel is a general purpose tool. MS Excel is not really designed to handle Big Data works. However, we can use MS Excel for data collection or as a conduit and convert to our desired format. MS Excel is a tool for data analysis, and pretty much everybody uses it for everything. It is just really accessible for those who are focusing on the data and analysis, rather than coding. MS Excel can only hold as much data as its of rows and columns. 64 bit MS Excel is limited to 1,048,576 rows, which is typically not viewed as a large amount of data in a big data context. MS Excel can be extremely inefficient when even managing tens of thousands of rows. However, if we are using a statistical environment such as R, the code template will allow us much greater flexibility in manipulating the data through data frames, vectors and so on. R is better equipped to handle large amounts of data. One of the major cons of using MS Excel is its inability to handle big data in data analytics.
MS Excel is great for ad-hoc general analysis. For sure, for a major big data statistical project, R is better. But that does not mean that R is better for everything. Pivot tables are an Excel feature that allows quickly and easily aggregating data in a crosstab fashion. With MS Query, ADO, and other traditional querying tools, your query can tell the database to aggregate and otherwise reduce the volume of data returned. Data sources designed for big data, such as HDFS may require specialized tools. MS Excel has Power Query, which is built into Excel 2016 (and available separately as a download). Power Query has several modern sets of connectors for Excel. Power Query provides the ability to create an auditable set of data transformation steps. A sweet spot for MS Excel in the big data is exploratory analysis. Some of the business analysts may want to use their favorite analysis tool against new data stores to get the richness of insight.