In the present world, where data is the king, the demand for data analysts has been soaring ceaselessly. This is evident from one of the World Economic Forum (WEF) reports in the year 2018, which stated that by the end of 2022, nearly 85% of the organizations are likely to adopt big data and analytics technologies. As a result of this, the job role of a data analyst was predicted to be one of the most in-demand job roles by the end of 2022. Data analysts play a pivotal role in an organization by deriving meaningful insights from a dataset and helping the organization to make strategic decisions based on these insights. To perform their roles and responsibilities, data analysts use a broad spectrum of tools. And when there are so many tools available, it becomes challenging to choose the right tools. The market is full of open-source tools that deliver good results at no cost than paid ones, such as R programming and Python. And in case you're looking for a great career in Rajasthan as a data analyst, you can look for a data analyst course in Jaipur that is comprehensive and meets your learning goals adequately. Here we bring to you some of the top and basic tools that every data analyst needs to perform his role adequately.
Excel
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Excel is the most basic and extensively used analytical tool having applications in almost every industry. It does not matter if you have expertise in other data analytical tools mentioned in this article as you must know Excel in any case. It primarily helps in analyzing complex tasks and summarizing data with the help of a pivot table that further helps filter data as per the client's need. Also, Excel possesses the advanced business analytics option that allows modeling capabilities having pre-built options like the creation of DAX measures, automatic relationship detection, and time grouping.
R Programming
R is one of the leading data analytics tools in the market and is used widely by data analysts for statistics and data modeling. The tool is capable of manipulating data and presenting it in multiple ways. It's considered much better than SAS in terms of data capacity, overall performance, and outcomes. R can efficiently compile and run on various platforms like Windows, Unix, and macOS. R has a total of 11,556 packages that will let you choose packages by category. Furthermore, R offers tools for automatically installing packages as per the user's requirement that can be further assembled with big data.
Python
Python is a free, object-oriented open-source tool and is easy to read, write and maintain. Python supports both functional and structured programming techniques and is quite similar to JavaScript, PH, and Ruby, making learning Python easy. Furthermore, Python has excellent machine learning libraries such as Tensorflow, ScikitLearn, Theano, and Keras. One more good feature of Python is that it can be assembled on multiple platforms such as a MongoDB database, SQL server or JSON. Also, Python can adequately handle text data as well.
Tableau Public
Tableau Public is a free software used to connect multiple data sources, be it Microsoft Excel, Data Warehouse, or Web-based data. It further helps develop data visualizations, dashboards, maps, etc., and real-time updates on the web. These can be shared easily with the client and on social media and can be downloaded in different formats. The wide range of qualities of Tableau makes it one of the most important data visualization tools using which one can analyze and visualize data better.
Sas
It's primarily a programming environment and language used for data manipulation and is presently the market leader in analytics. It can be accessed easily, is quite manageable and can analyze data from multiple sources. It has been used extensively over social media platforms, web and marketing analytics for profiling of customers and getting an idea of the future prospects. Furthermore, it's capable of predicting behaviors of customers, managing and streamlining communications.
While there are so many tools available on data analytics, we have brought to you some of the basic data analytics tools that are important in every step of managing data and deriving useful insights. If you're considering to have a career as a data analyst, you must seek knowledge of these basic tools for performing your roles well.