Data Analyst-Python/ETL/SSIS/SSRS/SSAS/Microsoft SQL/PowerBI

Data is everywhere. Everything you do online and in your daily life generates data—and it’s a valuable business resource. In fact, 94% of companies say data and analytics are essential to their growth. As we move toward greater digitization, there is an ever-increasing demand for professionals who can turn information into actionable insights.

A data analyst is a person whose job is to gather and interpret data in order to solve a specific problem. The role includes plenty of time spent with data but entails communicating findings too.

Here’s what many data analysts do on a day-to-day basis:

• Gather data: Analysts often collect data themselves. This could include conducting surveys, tracking visitor characteristics on a company website, or buying datasets from data collection specialists.

• Clean data: Raw data might contain duplicates, errors, or outliers. Cleaning the data means maintaining the quality of data in a spreadsheet or through a programming language so that your interpretations won’t be wrong or skewed.

• Model data: This entails creating and designing the structures of a database. You might choose what types of data to store and collect, establish how data categories are related to each other, and work through how the data actually appears.

• Interpret data: Interpreting data will involve finding patterns or trends in data that could answer the question at hand.

• Present: Communicating the results of your findings will be a key part of your job. You do this by putting together visualizations like charts and graphs, writing reports, and presenting information to interested parties

During the process of data analysis, analysts often use a wide variety of tools to make their work more accurate and efficient. Some of the most common tools in the data analytics industry include:

• Microsoft Excel

• Google Sheets

• SQL

• Tableau

• R or Python

• SSAS

• SSRS

• SSIS

• ETL

• Microsoft Power BI

• Jupyter Notebooks