Introduction
To be successful as data analysts you need to learn fundamental data analysis techniques, and data-oriented programming languages, and have a strong background in math.
Here are the most common job titles for a Data Analyst career:
- Data Analyst
- Business Analyst
- Financial Analyst
- Operations Analyst
- Risk Analyst
- Research Analyst
- Data Journalist
- Business Intelligence Analyst
- Marketing Analyst
Some of these titles, such as Data Analyst, Business Analyst, and Operations Analyst, are pretty standard. Others, like Financial Analysts, Data journalists, and Marketing Analysts, are specific to a particular industry.
Tasks performed by Data Analysts include the following:
- Gathering and extracting numerical data.
- Finding trends, and patterns within the data.
- Interpreting the numbers
- Analyzing market research
- Applying these decisions back to the business.
The term hard skills refer to technical knowledge and teachable skills. Hard skills are likely to be tested during an interview. The most important hard skills in the industry are:
Structured Query Language (SQL)
This programming language allows data analysts to read, write, organize, and analyze data within a relational database. It’s a fundamental skill required by any experienced data analyst. The majority of data-related companies will have at least one specialist in SQL. Popular database systems that use SQL include MySQL, PostgreSQL, and Oracle.
To get started with learning SQL, learning the basic concepts, and practicing it online you can use the following resources:-
Microsoft Excel
MS Excel skills doesn’t just mean basic spreadsheet knowledge. You need to have an advanced understanding of MS Excel methods like macros and VBA lookups. These will help you deal with small data sets and quick analysis. MS Excel is particularly popular among small companies and startups.
Programming Languages
R and Python are the most commonly used statistical languages. They allow you to analyze large data sets quickly and easily. They’re also used in predictive and advanced analytics. You need to master at least one of these programming languages to be considered a strong contender for a data analyst position. Several certification courses can help you master these languages. Certifications also improve your resume and demonstrate your commitment to prospective employers.
To get started with Python learning the basic concepts and practicing it online you can use the following resources:-
Data Analysis and Visualization
Not everybody in the company can understand complicated data patterns and information. A data analyst needs to transform complex data into a form that’s easy to understand. The job of a data analyst is to draw conclusions from data and present them using visually compelling charts, tables, and graphs.
To understand, analyze and visualize patterns in data; you may learn from the following resources:-
https://tech-mags.com/interesting-story-for-understanding-the-art-of-data-analysis/
https://tech-mags.com/learning-exploratory-data-analysis-using-redwine-dataset/
https://tech-mags.com/exploratory-data-analysis-and-visualization-using-seaborn-library/
Data Cleansing
Data cleansing is a significant part of a data analyst’s job. It involves retrieving data from different sources and preparing it for analysis. Data may be in various different formats or contain errors, missing fields, and inaccuracies. Before any useful analysis can take place, the data must be corrected.
Statistical Knowledge
Statistics is extremely important for analyzing and interpreting data. A background in statistics or knowledge of important mathematical principles will help you stand out from the crowd. You should be familiar with clustering, MapReduce technology, unstructured data concepts, and association rules.