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March 28, 2024

Top 5 Tools Required To Become Data Analyst in 2020

Top 5 Tools Required To Become Data Analyst in 2020

As multiverse is the new term that is wrapping the industrial sector, multi-skilling or multiple skill-sets are the new defining rules for the job aspirant in any field.

If you are a fresher or untapped working professional and looking for new prospects in the Data Analytics field, then you need to have specific fundamental knowledge about the tools required for this business.

Data analysis deals with the logic behind any business organization, which means the quantitative or qualitative scrutinization that is helpful to gain productivity in business. There are specific patterns, techniques, and processes involved in analyzing the data for gaining the upper hand in the industry.

So let’s move on to the analysis tools, code tools, or programming tools that will be useful if you want to be a Data Analyst.

1. Excel

If you are starting from the basic level of Data Analysis, then learning Excel is a prerequisite. Learning this spreadsheet application by Microsoft will come handy in a wide range of functions like sorting and manipulating data, performing arithmetic operations. To name some of the critical functions included in the everyday work of a Data Analyst are SUMIF function, Charts, Text Formulas, Conditional Formatting, IF formulas, etc.

2. Python

It is one of the simpler programming tools that are available in the market. With its fewer codes, even a novice can excel in dealing with Python, which is why it suits the need of a data analyst. Its standard library with a lot of tools makes it ideal for mathematical and data analysis functions. Its libraries like NumPy, Pandas, SciPy, IPython, etc. are perfect for data modeling and analysis, providing a broad scope for scalability.

3. R

Another vital programming tool for data engineers/analysts is R. It provides a software environment required for statistical computing, data analysis, graphical representation of data, which favors this language an important place in Data Analyst’s skill-sets. One of the facts remains that, originally, R was designed for processes like data cleaning, analysis, etc.

One of the advanced approaches of data analysis and predictive technology with the help of R is the Google Flu Trends project initiated to estimate flu activity based on Google search results.

4. SQL – Structured Query Language

Introduced in the industry since 1970, SQL is the most commonly used method for accessing data that enables one to read, control, or even change the data in databases. The core area of focus of a Data Analyst is data related management, and SQL is all that they need to interpret data for improving the business. If you are dealing with smaller data-related tasks, SQL is of great help to you, but it may lose its effectiveness while working with some bigger data projects like petabytes.

5. SAS

It is an essential tool for data analysis and writing reports based on this analysis. Developed by the SAS Institute, it helps you to store or retrieve data, modify or compute statistical analyses, and also create a report. With the assistance of SAS, you can work with any statistical modeling and big amount of data with no obstruction in the process.

These are some of the basics that will brush up your skills if you are choosing to become a Data Analyst in the future.

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