Microsoft Excel is Still Relevant in the Age of Data Analysis

In the age of data analysis, Microsoft Excel is still necessary

In recent years, leading companies and organizations are focusing more on content. Businesses are trying to deliver products, services, and content according to the preferences of the customers. But even though the focus is on the final product, the key to achieving that- is the data. Data analysis of the vast amounts of information received daily provides businesses the insights required to understand the market demands and serve the customers accordingly.

Data analysis uses advanced analytics tools like Hadoop, Apache Storm, and DataCleaner. The analytics technology is closely connected to the applications, which manage, analyze, and store the data. One such program, which often goes unnoticed when it comes to the analysis of data, is Microsoft Excel.

Microsoft excel is still relevant in the age of data analysis and advanced technologies. Data scientists who use Excel to store the information are well aware that it is indispensable and is an effective tool.

So, what is the function of Excel in data analysis?

Larger organizations indeed have moved away from Excel, but it remains a part of a larger data ecosystem. Primarily, people use Excel because they are familiar with it. The program is easy to figure out, but Excel can cause a lot of trouble when it comes to handling large datasets.

Excel holds data points in each cell, starting from raw data exports, date of sales, SKU, or the number of units sold; all this information is stored in Excel for easier access and viewing. Moreover, using Excel spreadsheets promotes teamwork. A team of professionals often creates and handles a spreadsheet. The team analyzes data to seek new business opportunities. An Excel spreadsheet would organize data into a readable format, which will make it easier for analysts and data scientists to draw insights from them.

Top data professionals have to consider several factors while using Excel, like if the framework is replicable, or whether the data is readable, and most importantly, whether they can manipulate the information. Data professionals need to be able to manipulate the information but they do not consider Excel as the tool that can be used to manipulate the data stored in it, even though the company has added several additional features to it in recent years.

Implementing Excel in data analysis requires advanced skills. Even though it is a part of a larger data ecosystem, the operator handling the data in Excel must be adept in handling Microsoft Excel and should possess advanced knowledge about the shortcuts and the extensions in the program.

Data analysis and augmentation are a part of the larger toolset that can be used to draw information from large datasets. Microsoft has added several features to ensure efficiency in analytics and help professionals extend the internal data depth. Better analysis leads to better data products. Excel might be an efficient tool but it is not a solution provider. Data analysts have to examine various other programs for better insights.