Answer.

A business analyst uses various methods and tools for data analysis to identify insights, evaluate the effectiveness of processes, and make decisions.

Data analysis tools:

• MS Excel, Google Sheets: for working with spreadsheets, analyzing and visualizing data.
• BI systems (Power BI, Tableau, Qlik): creating dashboards, automated reports, and visualizing large datasets.
• SQL: processing, joining, and querying data from corporate repositories.
• Python/R: automating analytics, complex processing, and modeling.

The use of tools is necessary for:

• Quick identification of deviations and trends.
• Demonstrating results to clients in a visual form.
• Ensuring transparency and reliability of decisions made.

Key features:

• Proficiency in both basic (Excel) and advanced (BI, SQL) tools.
• Ability to visualize large volumes of information.
• Application of Data Discovery and Dashboarding methods for operational analysis.

Trick questions.

Is it enough for an analyst to only know how to work in Excel?

No, modern projects require proficiency in both BI tools and basic SQL knowledge at the level of querying.

Can an analyst conduct analysis without checking the quality of the original data?

No, analysis is always based on correct, relevant data — otherwise, the conclusions will be erroneous.

Can all business problems be solved with BI platforms?

No, BI platforms are great for reporting and visualization, but not for detailed analysis of cause-and-effect relationships and complex modeling (Python or R is needed here).

Common mistakes and anti-patterns

• Analyzing only "manually", without automation.
• Using one tool for all tasks.
• Ignoring data quality, lack of preliminary cleaning.

Real-life example

A company implemented only Tableau and started building dashboards, ignoring the quality of the original data. The reports turned out to be visually appealing, but management relied on incorrect indicators, leading to financial errors.