Data Analysis is a demanding skill in today's era. A career in data analysis is directly linked with the creation of data in today's world. With the increasing demand for tech and data, data analysts are needed for making conclusions and predictions from the data. Data analyst and business analyst uses the same somewhat same sort of software but the data analyst is more board and requires more in-depth knowledge while the business analyst is more business oriented. You can start your journey as a data analyst by learning this thing. But you need to make sure that data analysis is not only about computer science, statistics, and programming language but is more about solving real-life problems with your creative mind.

1. Statistics

Before starting out with any other software, you must have a basic knowledge of statistics, which is a complied mathematics you need for data analysis. Generally, people directly start with software and programming language, but having a proper knowledge of statistics for data science helps to make good commands on this software. Some important topics like measures of central tendency, variance, and standard deviation, box plots, and hypothesis testing are the basic but important parts of statistics. If you're a newbie, you can start learning statistics for data analysis from any youtube channel and learning platform like Coursera, Udemy, etc... Resources to learn statistics.

1. Introduction to Satistics[Datcamp]

2. Statistics for Data Science using python[Coursera]

3. Statistics in Data Science[Krish Naik]

2. Excel

Advanced-level Excel is used by data analysts, it is the most basic software that any data analyst should know. Microsoft Excel is used for storing, organizing, cleaning, and making basic visualizations. Many formulas and functions like vlookup and used for analyzing the data. Statistical modeling, forecasting, and predictions can be done by using excel.

1. MS Excel[Tutorial point]

2. Data Analysis in Excel[Datacamp]

3. IBM Data Analytics with Excel and R[Coursera]

3. SQL

SQL is one of the most famous query languages used by data analysts or business analysts for organizing and cleaning data. It stands for the structured query language. SQL is able able to handle more than millions of rows of data, which is not possible in Excel, this using SQL in case you have a lot of data is a better option. SQL queries are also more powerful and used in cleaning, analyzing, and manipulating data. Thus, learning SQL is one of the most important tasks in the journey of data analysis.

1. Data Analyst in SQL[Datacamp]

2. The Ultimate MySQL Bootcamp[Udemy]

3. Learn SQL Basics for Data Science[Coursera]

4. Power Bi

Power Bi is one of the most used business intelligence tools. According to Gartner's latest Magic Quadrant, Power Bi is one of the leading business intelligence, data analysis, and reporting tool. It is a cloud-based service by Microsoft, which enables you to effectively extract and reports insights from the data. You can easily create reports and dashboards in Power bi by creating different visualization. You can also edit data in Power Query Editor. Power Bi desktop is a desktop version used for data analysis or report creation which is 100% free while Power Bi service is a cloud-based version used for light-report editing and sharing of reports.

1. Data Analyst in Power Bi Track[Datacamp]

2. Power Bi Essentials 2023: Power Bi Training and Exam Prep[Udemy]

3. Microsoft Certified: Power Bi Data Analyst Associate

5. R programming language

R-programming language is used for statistical computing and graphical presential of data which is further used for analyzing and visualizing data. R-programming language with python is one of the most used programming languages for data analysis which is making it the hottest language to learn in today's era. You can learn R from many resources, but here are some of the best resources to start with.

1. Data Analyst with R [Datacamp]

2. Data Analysis with R programming[Coursera]

3. Data Science: R Basics[edx]