More and more companies are asking for people with knowledge of Data Analysis. This discipline is based on data processing, screening, transformation and modelling to obtain useful information. We are going to explain the four programs that you must master, no matter what, to get a job in the field of Data Analysis.
Data analysis has gained strength in recent years because it is very important in the fields of business, science, engineering and social sciences.
It helps companies to make better decisions about future projects, saving costs. In addition, it allows the identification of different patterns and trends. It also serves to improve processes, detecting possible deficiencies and saving costs.
Although there are many different programs to carry out these research processes, we are going to leave you with the four most commonly used currently.
Microsoft Excel
The truth is that there is not much to say about one of the most widely used and versatile software out there. Microsoft Excel allows us to analyze data, perform all kinds of calculations and create different graphics.
It is not only used in data analysis tasks, it is used in a multitude of fields. There are even people who use it to paint pictures with truly spectacular results. There is also a world Excel competition, where you have to solve different problems using this tool.
You should be aware that this software has certain technical limitations. The more data it has to handle, the slower it becomes. For very large values, inaccuracies can occur. Nevertheless, it is a great application for analyzing data.
Excel is part of the Microsoft 365 suite. We can have access to this program (and all the other programs in the Office suite, as well as 1 TB of space on OneDrive) by paying the Microsoft fee.
Microsoft Power BI
Now we move on to a much newer tool that is fully focused on data analysis. Power BI started out as an Excel add-in, but Microsoft separated it in the 2010s to create a business data analysis tool.
It has the ability to generate highly visual reports and different control panels. Its great advantage is that the learning curve is minimal. In addition, it has the strength of being able to connect to data in Excel, obtain data from text files, SQL databases and other sources such as Google Analytics or Facebook Analytics.
It’s not all pretty, as it has a very large user interface, rather rigid formulas, and a proprietary language that is complex to use. The good thing is that it has a free or trial version so that we can familiarize ourselves with it.
PowerBi is also a Microsoft software. However, since it is a professional analytics software, it is only found within Microsoft 365 plans for businesses (such as E2). These are somewhat more expensive, and offer different benefits that are much more focused on professional use.
Tableau
This software is more focused on data visualization and generating interactive dashboards without any coding knowledge. It is currently considered as the best tool for Business Data Analysis.
Its great strength is that it can handle huge amounts of data and its fairly simple usability. It has a visual drag-and-drop interface.
It does have several limitations, though. The first is that it doesn’t have a scripting layer, so it has capacity limits. Also, the data manipulation functions aren’t very good. Also, if we want to run scripting functions with Python or R, we need to import the data first.
Jupyter Notebook
Let’s move on to an open source web application that has the ability to develop interactive documents. Jupyter Notebook has the ability to combine live code, equations, visualizations, and narrative text.
This tool is a much more interactive Microsoft Word document focused on data analysis. Rather than processing data, it is a tool for presenting it in an elegant way. It does not require installation, as it is accessed from a browser and is compatible with more than 40 languages, such as Python or R.
As usual, not everything is positive. The first shortcoming is that it has very poor version control and the change tracking system is quite complicated. It is not a good tool for collaborative work either.
