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Top 3 Reasons to Choose MS Excel for Data Analytics

MS Excel for Data Analytics

Microsoft Excel is one of the most commonly used data analytics tools used today. It is also known as the de facto standard for spreadsheets for anyone serious about data science. Excel is the most popular tool for data analytics because it is very user friendly, versatile, and available on Windows, Mac, and Chromebook.

Having said all that, it is extremely important to remember that Excel is still relevant to some companies for a variety of reasons. Let’s explore the reasons to understand how it is still useful to companies around the around for data analytics.

Familiar UI

First and foremost, Excel is very easy to use. It is quick to learn and get started with. Excel is also very versatile. Because it has been used for years and years, there is a lot of information out there about how to do certain things. This makes it very easy for even an entry-level data scientist to get up and running quickly. This is a great way to kick off the data science process for you!

There is a generation of the workforce to whom, using Microsoft’s productivity software is like second nature. Microsoft Office comes installed in every computer sold at a fraction of the cost of any other tool for data analytics. That implies that every person can easily be trained for analytics projects on Microsoft Office Excel. Seriously, many of us have been learning and using MS Excel since our childhood.

Scripting

Most people don’t realise that they can script and automate a lot of MS Office tasks, just like other scripting languages/tools. VBA for Microsoft Office is a sought after skill because it allows for the user to be creative with the kind of applications they want to create for automation of such tasks. Using this aspect of MS excel, end users can become very creative by working with data sets by connecting to databases like MS SQL Server. No other allows for this level of automation capabilities.

Cost

One major factor in deciding which tools are to be used for any project in any industry is the amount of the initial investment. And of course, this is a valid question. Even on this count, MS Excel along with VBA costs significantly lesser than any other tool available in the market. It is certainly worth having this tool around as the last line of defence with respect to the cost involved.

Data Analytics can cost a lot depending on the nature of the projects. There are many factors that will determine your spending. One of the most important things to consider is the size of your data. There are many factors that go into your costs such as the number of servers, the amount of processing power needed to handle your data, and of course the cost of hardware and the associated maintenance. If you already have a good budget in place, you can try to save some money by using free MS Excel to create reports. It may not be as sophisticated as a professional tool, but it will get you good results that are within your budget.

Versatile

Second, Excel is versatile. It is often used for a wide range of applications. This means you can get started quickly, but also that it is an ideal tool for the more complex tasks you may face in data analysis.

Some of the different fields in which Excel can be used include:

  • Business analytics
  • Data visualization
  • Regression analysis
  • Descriptive data analysis
  • Quantitative data analysis
  • Statistical analysis
  • Data mining
  • Hadoop-specific analysis

It has even been used for the creation of custom databases in Oracle. This is also one of the few pieces of software that have a very big ecosystem of add-ins and extensions. In the long run, this versatility will be a very big advantage to you.

Availability

Excel is very widely available. It is available in most computing environments. Therefore, you can access your work in Windows, Mac, and Chromebook. This means you will be able to use your work in whatever environment suits you best.

Easy to Use

Data Analytics requires some expertise to create the necessary reports. You need to understand the various mathematical functions and formulas to make sense of your data. Most data analyst tools have tutorials that help you to learn all the functions you need. However, it’s easier to learn all these functions using MS Excel. You can try to use existing examples of how they are created and simply use them to create your own report. You won’t be able to create elegant and sophisticated reports as you can with professional tools, but your data is already formatted to suit the type of reports you need. All you need is a bit of practice to learn how to combine all your data to create the complex reports you need.

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