How to Become a Data Analyst in 2023
What Does a Data Analyst Do?
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Case Western Reserve University
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Typical Data Analyst Job Description
Data Analyst Qualifications
Skills Required for Data Analysts
- Programming languages (R/SAS): Data analysts should be proficient in one language and have working knowledge of a few more. Data analysts use programming languages such as R and SAS for data gathering, data cleaning, statistical analysis and data visualization.
- Creative and analytical thinking: Data analysts should demonstrate curiosity and creativity, as they are considered key attributes of a good data analyst. It’s important to have a strong grounding in statistical methods, but even more critical to think through problems with a creative and analytical lens. This will help the analyst to generate interesting research questions that can enhance a company’s understanding of various issues.
- Strong and effective communication: Data analysts must clearly convey their findings—whether it’s to an audience of readers or a small team of executives making business decisions. Strong communication is the key to success.
- Data visualization: Data analysts understand what types of graphs to use, how to scale visualizations and know which charts to use depending on their audience. Effective data visualization takes trial and error.
- Data warehousing: Data analysts may work on the back-end. They connect databases from multiple sources to create a data warehouse and use querying languages to find and manage data.
- SQL databases: Data analysts are well versed in using SQL databases, which are relational databases with structured data. Data is stored in tables and a data analyst pulls information from different tables to perform analysis.
- Database querying languages: Data analysts rely on database querying languages to carry out a host of tasks. The most common querying language data analysts use is SQL and many variations of this language exist, including PostreSQL, T-SQL, PL/SQL (Procedural Language/SQL).
- Data mining, cleaning and munging: Data analysts must use other tools to gather unstructured data when it isn’t neatly stored in a database. Once they have enough data, they clean and process through programming.
- Advanced Microsoft Excel: Data analysts should have a good handle on Excel, and understand advanced modeling and analytics techniques.
- Machine learning: Data analysts with machine learning skills are incredibly valuable, although certain data analyst roles might not require proficiency in machine learning.
Data Analyst Responsibilities
A Day in the Life of a Data Analyst
What Tools Do Data Analysts Use?
- Google Analytics (GA): GA helps analysts gain an understanding of customer data, including trends and areas of customer experience that need improvement on landing pages or calls to action (CTAs).
- Tableau: Analysts use Tableau to aggregate and analyze data. They can create and share dashboards with different team members and create visualizations.
- Jupyter Notebook: Jupyter Notebook makes it simple for data analysts to test code. Non-technical folks prefer the simple design of Jupyter Notebook because of its markdown feature.
- GitHub: GitHub is a platform for sharing and building technical projects, and a must for data analysts who use object-oriented programming.
- AWS S3: AWS S3 is a cloud storage system. Data analysts can use it to store and retrieve large datasets.
Data Analyst Job Outlook
Data Analyst Salary
University of Texas at Austin
The Data Analysis & Visualization Boot Camp at Texas McCombs
The Data Analysis and Visualization Boot Camp at Texas McCombs puts the student experience first, teaching the knowledge and skills to conduct data analysis on a wide array of real-world problems. Students dive into a comprehensive curriculum, learning how to collect, analyze, and visualize big data.
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Data Analyst FAQ
There are a variety of tools data analysts use day to day. Some data analysts use business intelligence software. Others may use programming languages and tools that have various statistical and visualization libraries such as Python, R, Excel and Tableau. Other skills include creative and analytical thinking, communication, database querying, data mining and data cleaning.
Some data analysts are proficient in programming languages, while others may use analytics software or Excel to analyze data and provide insights. Whether or not coding is required for a data analyst typically depends on the job or the employer. Employers may or may not list programming as a required skill for data analysts in job listings. It is important to look at the job description and consider your background before applying.
If you’re weighing your options between becoming a data analyst or data scientist, both occupations can come with benefits. Business intelligence analysts have a positive job outlook according to O*NET OnLine. From 2021 to 2031, employment of these professionals is expected to grow 11% or higher. Employment of data scientists is also projected to grow 11% or higher during the same time period.
Data analysts’ salaries typically depend on where they work and their industry.