With the scope of creating 11 million jobs by 2026, the field of data analysis is growing at a breakneck speed. To stay relevant, it becomes necessary to change and adapt to the new trends and technologies that emerge. The field of data analytics is no exception to this trend. With the ever-evolving technology, there are improvements and additions to the list of data analytics tools that are used by professionals.
The article will give you a compiled list of the best data analytics tools that are now relevant for any professional to grow in the field of data analytics. But before diving into the list, it is crucial to understand the basic concept of data analysis.
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What is Data Analytics?
The basic idea behind data analytics is to draw meaningful conclusions from the vast array of available data. To extract meaningful information from the available data, a set of complex calculations and algorithms have to be performed on this data set to make statements and present them in a form that is understandable to the reader.
Data analysis has many applications ranging from educational research to business projections and data analytics tools are making the process easier. A few of the essential features of data analysis are:
- Optimises the performance
- Identifies specific errors and problems
- Gives better projections, in turn, provides better solutions
5 Best Tools For Data Analysis Every Beginner Must Know About
1. Excel
Microsoft Excel is the most basic yet powerful tool to perform operations and analyse data, and this can be considered a data analytics tools for beginners. Packed with a bunch of excellent tools and features, this application can perform fundamental analysis tasks such as sorting and filtering. Along with this, the tool can perform advanced operations like pivot table and statistics calculations like regression and correlation analysis.
Pros: Easy To Use, Dynamic Tools
Cons: Time-Consuming, Not Error-Free
2. Python
Python is much more than just a programming language. In the field of data analysis, the utility of tools provided by the software is increasing. The packages provided in the language make the process of scientific computing easier. The manipulation and operations of data series are also made convenient using Python. A lot of data analytics tools in Python like Pandas, Matplotlib, and others can be used to perform various functions on the raw data.
Pros: Vast Data Sources
Cons: High Processing Time
3. Tableau
A data visualisation tool founded in 2003, Tableau is a good addition to the list of data analytics tools that professionals can use to grow in the field of data analysis. The tool can be used to modify data and perform various complex mathematical calculations to generate significant results.
Pros: Can handle large amounts of data
Cons: Requires expertise in SQL
4. Power BI
Power BI is one of the best data analytics tools by Microsoft to be put to use at present. It is a cloud-based analysis service that can accurately extract and visualise data. Many professionals use this to prepare business reports and dashboards to make the data more appealing and put together. Power BI makes importing and exporting data faster and easier, along with providing a good range of tools making analysis more comprehensive by integrating the data with other Microsoft tools.
Pros: Good Data Sources
Cons: Rigid User Interface
5. R
R is another popular programming language used to perform advanced calculations and computations on the data set. The utility of R is especially recognised in the field of data visualisation and presentation. This data visualisation process makes it easier for the common man to comprehend the data and draw significant conclusions. This tool is a necessary addition to the list of data analytics tools as it provides a good deal of tools and methods to present the data in an understandable manner.
Pros: Great Quality Visualisation
Cons: Difficult to Learn
Also Read: Boost The Company Management Using These Four Analytics
Will These Tools Take Away Jobs Or Make The Process Easier?
There is skepticism in the domain of data analysis as better and more efficient tools are being introduced in this area. As brutal as it may sound, the advent of new and improved technologies and data analytics tools will automate tasks and reduce the involvement of humans in the process of calculations and computations. This does not mean that there will be a dearth of jobs in the field of data analysis. The data by the Bureau of Labor Statistics (BLS) states that from 2019 to 2029, the jobs in information research will grow by 11%, which includes the job role of data analysts as well.
This statistic is enough to prove that the field of data analysis is booming and will continue to grow even if new data analytics tools are launched in the coming years as the relevance and significance of data is growing.
The article throws light on the critical aspects relating to the field of data analysis. It lists data analytics tools that can help make data computation and visualisation more accessible. In this era of rapidly transforming global data scenarios, the need for data analytics is not only growing at a rapid rate, but the field is also growing exponentially.
So will you make use of data analysis for your everyday functions as well?
