Most jobs in data analytics involve gathering and cleaning data to uncover trends and business insights. The day-to-day data analyst job varies depending on the industry or company or the type of data analytics you consider your specialty. Data analysts may be responsible for creating dashboards, designing, and maintaining relationship databases and systems for different departments throughout their organization using business intelligence software, Tableau, and programming.
Most data analysts work with IT teams, management, and/or data scientists to determine organizational goals. Let us take a look at the qualifications/skills a Data Analyst must-have.
Skills Required for Data Analysts
- Programming Languages (R/SAS): data analysts should be proficient in one language and have a 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: Curiosity and creativity are 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 will enhance a company’s understanding of the matter at hand.
- 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: Effective data visualization takes trial and error. A successful data analyst understands what types of graphs to use, how to scale visualizations, and knows which charts to use depending on their audience.
- Data Warehousing: Some data analysts 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: SQL databases 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: The most common querying language data analysts use is SQL and many variations of this language exist, including PostgreSQL, T-SQL, PL/SQL (Procedural Language/SQL).
- Data Mining, Cleaning, and Munging: When data isn’t neatly stored in a database, data analysts must use other tools to gather unstructured data. 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 machine learning is not the expected skill of typical data analyst jobs.
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Data Analyst Responsibilities
The day-to-day for a data analyst depends on where they work and what tools they work with. Some data analysts don’t use programming languages and prefer statistical software and Excel. Depending on the problems they are trying to solve, some analysts perform regression analysis or create data visualizations. Experienced data analysts are sometimes considered “junior data scientists” or “data scientists in training.” In some cases, a data analyst/scientist could be writing queries or addressing standard requests in the morning and building custom solutions or experimenting with relational databases, Hadoop, and NoSQL in the afternoon.
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