Business Analyst
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09_Business Scenario
- A dashboard adoption is low even though data is correct. How do you improve adoption?
- A dashboard exposes negative performance. How do you manage stakeholder reactions?
- A dashboard is technically correct but visually confusing. How would you improve it?
- A dashboard is used for decisions it was not designed for. How do you address this?
- A dashboard looks correct but users say it is not useful. How would you investigate?
- A dashboard works well for managers but not for operational users. How do you address this?
- A KPI improves visually but business performance is actually declining. How do you investigate?
- A KPI shows sudden spike. How do you validate whether it is real or a data issue?
- A manager wants real-time data, but the source system refreshes only once a day. What do you do?
- A metric definition changes mid-project. What steps should you follow?
- A new stakeholder joins late and demands changes. How do you respond?
- A report is slow and users complain. How do you diagnose the problem?
- A report refresh fails on the day of a review meeting. What is your immediate action?
- A requirement is technically feasible but business impact is low. How do you advise?
- A stakeholder asks for a dashboard but cannot clearly explain what decision they want to take. How would you handle this?
- A stakeholder questions the credibility of the dashboard. How do you rebuild trust?
- A visual is misleading but requested by leadership. How do you handle this ethically?
- Business asks for automation but lacks process clarity. How do you handle this?
- Business users report that dashboard numbers do not match their Excel reports. How do you approach this issue?
- Business users want to compare data across years, but historical data structure has changed. What do you do?
- Business wants AI-driven insights without clean data. How do you handle expectations?
- Business wants forecasts, but historical data is unstable. How do you approach this?
- Different departments use different source systems for the same metric. How do you align them?
- Different teams interpret the same metric differently. How do you resolve this conflict?
- Leadership wants a single number, but the business logic is complex. How do you simplify it?
- Stakeholders ask for row-level details in an executive dashboard. How do you respond?
- Stakeholders want absolute accuracy but accept no delay. How do you balance this?
- Stakeholders want frequent changes after sign-off. How do you manage this?
- The business wants a KPI, but the data needed to calculate it is not available. What is your approach?
- The business wants to track too many KPIs on one dashboard. How do you push back?
- Two stakeholders want different KPIs on the same dashboard. How do you resolve this?
- Users misuse filters and draw wrong conclusions. How do you prevent this?
- Users rely on dashboard numbers without understanding limitations. How do you handle this risk?
- Users request daily refresh but infrastructure cannot support it. How do you negotiate?
- Users want to export dashboard data and manipulate it externally. What risks do you consider?
- You are asked to add advanced analytics features without clarity on usage. How do you proceed?
- You are asked to build a dashboard urgently with incomplete requirements. What steps do you take?
- You are asked to explain a complex insight to a non-technical executive. How do you approach it?
- You are asked to justify the business value of a dashboard you built. How do you do it?
- You are asked to replicate a dashboard without understanding original assumptions. What do you do?
- You are asked to show sensitive data to multiple teams. How do you handle access control?
- You are asked why two visuals showing the same metric give different numbers. How do you explain it?
- You detect data anomalies regularly but business ignores them. What do you do?
- You discover missing data in the source after the dashboard is already live. How do you handle it?
- You find duplicate records affecting key metrics. How do you handle this scenario?
- You notice different data granularity across sources. How do you align them?
- You notice KPI gaming by teams. How do you respond as a BA?
- You suspect confirmation bias in stakeholder interpretation. How do you counter it?
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01_Fundamentals
- How does a Business Analyst differ from a Data Analyst?
- What are structured, semi-structured, and unstructured data?
- What are the core responsibilities of a Business Analyst in a data-driven organization?
- What does row-level data mean?
- What does row-level data mean?
- What is a baseline in project delivery?
- What is a business glossary?
- What is a business problem statement?
- What is a business requirement document (BRD)?
- What is a business rule in analytics?
- What is a constraint in business analysis?
- What is a dashboard and how is it different from a report?
- What is a data mart?
- What is a data refresh cycle?
- What is a data source system?
- What is a data warehouse and why is it used?
- What is a dimension in analytics terminology?
- What is a fact in analytics terminology?
- What is a functional requirement versus a non-functional requirement?
- What is a KPI and how is it different from a metric?
- What is a measure and what is a dimension conceptually?
- What is a single source of truth?
- What is a success metric for a BI solution?
- What is a surrogate key?
- What is a use case in BI projects?
- What is an assumption in business analysis?
- What is an SLA in reporting systems?
- What is Business Intelligence and why do organizations invest in BI systems?
- What is change management in analytics projects?
- What is data accuracy?
- What is data completeness?
- What is data consistency?
- What is data democratization?
- What is data governance?
- What is data granularity?
- What is data lineage?
- What is data literacy?
- What is data reconciliation?
- What is data redundancy?
- What is data security from a BA perspective?
- What is data timeliness?
- What is data validation?
- What is denormalization at a conceptual level?
- What is descriptive analytics and how is it used by business teams?
- What is diagnostic analytics and when is it applied?
- What is domain knowledge and why is it important for a BA?
- What is drill-down and drill-through?
- What is exploratory data analysis conceptually?
- What is historical data and why is it valuable?
- What is hypothesis-driven analysis?
- What is master data?
- What is metadata?
- What is normalization at a conceptual level?
- What is predictive analytics at a high level?
- What is prescriptive analytics at a high level?
- What is real-time data vs batch data?
- What is ROI in analytics initiatives?
- What is role-based access in BI systems?
- What is scope creep?
- What is self-service BI?
- What is shadow IT in analytics?
- What is sign-off and why is it important?
- What is slicing and dicing data?
- What is stakeholder analysis and why is it important?
- What is the BI lifecycle from data source to decision making?
- What is the difference between data, information, and insight in a business context?
- What is the difference between OLTP and OLAP systems?
- What is the difference between operational reporting and analytical reporting?
- What is transactional data?
- What is value realization in BI projects?
- What types of business questions are best answered using data analytics?
- Why is data quality critical for business decision-making?
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02_Data Extraction
- How do NULL values behave in comparison operations?
- How does poor extraction affect downstream dashboards?
- What are advantages of Import mode?
- What are aggregate functions in SQL?
- What are limitations of DirectQuery?
- What does data extraction mean in the BI lifecycle?
- What happens when JOIN keys do not match?
- What happens when query folding breaks?
- What happens when you compare different data types?
- What is a Cartesian join and why is it dangerous?
- What is a correlated subquery?
- What is a data refresh schedule?
- What is a database table and how is it different from a view?
- What is a database view and why is it used for reporting?
- What is a date filter and why is it common in reports?
- What is a flat file source?
- What is a foreign key and how does it help in querying data?
- What is a FULL OUTER JOIN?
- What is a JOIN and why is it required during data extraction?
- What is a LEFT JOIN and when is it used?
- What is a primary key and why is it important for data extraction?
- What is a RIGHT JOIN and when is it used?
- What is a schema in a database?
- What is a SELECT statement used for in SQL?
- What is a subquery and when would you use it?
- What is a UNION and how is it different from UNION ALL?
- What is access control impact on extraction?
- What is an alias in SQL and why is it used?
- What is an INNER JOIN?
- What is API-based data extraction conceptually?
- What is authentication vs authorization in data sources?
- What is backward compatibility of data sources?
- What is backward compatibility of data sources?
- What is BETWEEN used for?
- What is casting in SQL?
- What is column pruning and why is it important?
- What is COUNT(*) vs COUNT(column)?
- What is CSV, Excel, and text file extraction?
- What is data duplication during extraction?
- What is data freshness and how is it validated?
- What is data masking during extraction?
- What is data refresh failure and common reasons?
- What is data source credentials management in Power BI?
- What is data type compatibility in SQL queries?
- What is DirectQuery mode in Power BI?
- What is DISTINCT used for in SQL queries?
- What is duplicate detection during extraction?
- What is error handling during extraction?
- What is filtering data and why is it required during extraction?
- What is full data extraction?
- What is gateway in Power BI?
- What is HAVING clause and how is it different from WHERE?
- What is implicit vs explicit type conversion?
- What is Import mode in Power BI?
- What is IN operator used for?
- What is incremental data extraction?
- What is indexing at a high level?
- What is IS NULL and IS NOT NULL?
- What is LIKE operator and when is it used?
- What is Live Connection in Power BI?
- What is logging and monitoring in extraction pipelines?
- What is MIN and MAX used for?
- What is NULL and how does it affect query results?
- What is on-premises vs cloud data source?
- What is pagination in data extraction?
- What is pattern matching in SQL?
- What is PII awareness during data extraction?
- What is Power BI data source connectivity?
- What is Power Query and its role in extraction?
- What is preview data vs loaded data in Power BI?
- What is preview data vs loaded data in Power BI?
- What is pushing filters to source systems?
- What is query execution order conceptually?
- What is query execution order conceptually?
- What is query folding in Power BI?
- What is query performance from a BA perspective?
- What is reconciliation after extraction?
- What is row-level filtering at source vs report level?
- What is schema drift and how does it impact extraction?
- What is set-based thinking in SQL?
- What is snapshot data?
- What is sorting data and how is it done in SQL?
- What is source system latency?
- What is SUM and AVG used for?
- What is the difference between SELECT * and selecting specific columns?
- What is the GROUP BY clause?
- What is the LIMIT or TOP clause and when is it used?
- What is the ORDER BY clause?
- What is the purpose of the WHERE clause in SQL?
- What is throttling in API-based extraction?
- What is timeout during data extraction?
- What is transactional data extraction?
- What is validation of extracted data?
- What is versioning of extraction logic?
- What questions should a BA ask before extracting data?
- What risks exist if extraction logic is incorrect?
- Why is query folding important for extraction performance?
- Why must aggregate functions be used with GROUP BY?
- Why should BAs understand basic indexing concepts?
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03_Data Transformation
- How does poor transformation affect reporting accuracy?
- What are common data quality issues addressed during transformation?
- What are common string transformation operations?
- What does data transformation mean in analytics projects?
- What is append queries during transformation?
- What is Applied Steps in Power Query?
- What is business rule implementation during transformation?
- What is calculated column conceptually?
- What is case standardization in text fields?
- What is CASE WHEN logic in SQL used for?
- What is COALESCE and NULL handling logic?
- What is column profiling in Power Query?
- What is conditional transformation logic?
- What is custom column in Power Query?
- What is data cleaning conceptually?
- What is data enrichment?
- What is data normalization from a transformation perspective?
- What is data shaping vs data modeling?
- What is data standardization?
- What is data type conversion and casting?
- What is data type detection in Power Query?
- What is data validation during transformation?
- What is date and time transformation?
- What is date formatting vs date conversion?
- What is date manipulation in SQL?
- What is de-duplication logic using SQL?
- What is derived column creation?
- What is duplicate removal and why is it important?
- What is dynamic transformation logic?
- What is error handling during transformation?
- What is extracting year, month, day from a date?
- What is filtering during transformation vs extraction?
- What is grouping and aggregation during transformation?
- What is handling large datasets during transformation?
- What is handling missing values during transformation?
- What is handling outliers conceptually?
- What is incremental refresh transformation logic?
- What is M language at a conceptual level?
- What is mathematical transformation in SQL?
- What is merge queries during transformation?
- What is numeric data transformation?
- What is parameterization in Power Query?
- What is performance impact of poor transformation design?
- What is pivot and unpivot transformation?
- What is Power Query and its role in transformation?
- What is query folding during transformation?
- What is reconciliation between source and transformed data?
- What is Replace Errors in Power Query?
- What is replacing values during transformation?
- What is rounding and scaling numeric values?
- What is row-level transformation vs column-level transformation?
- What is sorting during transformation?
- What is splitting and merging columns?
- What is string manipulation in SQL?
- What is text data cleaning?
- What is time zone handling in data?
- What is transformation documentation and why is it important?
- What is transformation reusability?
- What is transformation using SQL SELECT expressions?
- What is transformation vs modeling responsibility?
- What is trimming and why is it required?
- What is validation after transformation?
- What is window function usage in transformation?
- What issues arise due to wrong data types?
- What questions should a BA ask before defining transformations?
- What risks exist if transformation logic is incorrect?
- Which transformations break query folding?
- Why is data transformation required after extraction?
- Why step order matters in Power Query transformations?
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04_Data Modeling
- How does poor modeling affect DAX complexity?
- How does relationship affect filter context?
- How does RLS interact with relationships?
- What are advantages and disadvantages of star vs snowflake schema?
- What happens if you don’t use a proper date table?
- What is a calculated column in Power BI conceptually?
- What is a date dimension and why is it mandatory?
- What is a dimension table conceptually?
- What is a fact table conceptually?
- What is a measure in Power BI conceptually?
- What is a natural key?
- What is a primary key in a dimension table?
- What is a snowflake schema?
- What is a star schema and why is it preferred in BI?
- What is a surrogate key and why is it used?
- What is aggregation behavior in data models?
- What is bridge table and when is it required?
- What is CALCULATE function used for conceptually?
- What is cardinality in relationships?
- What is circular dependency in data models?
- What is composite model in Power BI?
- What is conformed dimension?
- What is context transition in DAX?
- What is data model scalability?
- What is data modeling in analytics projects?
- What is data type impact on model size?
- What is default aggregation and why does it matter?
- What is degenerate dimension?
- What is denormalization from a modeling perspective?
- What is DirectQuery model vs Import model?
- What is evaluation context in DAX?
- What is fact-to-fact relationship and why is it risky?
- What is handling blank values in models?
- What is hybrid model?
- What is implicit measure vs explicit measure?
- What is inactive relationship in Power BI?
- What is junk dimension?
- What is many-to-many relationship?
- What is model extensibility?
- What is model granularity mismatch?
- What is model size optimization?
- What is normalization from a modeling perspective?
- What is referential integrity?
- What is relationship ambiguity?
- What is relationship direction in Power BI?
- What is role-playing dimension?
- What is row context?
- What is row-level security (RLS) conceptually?
- What is security table in data modeling?
- What is semantic layer in Power BI?
- What is single direction vs both direction filtering?
- What is slowly changing dimension conceptually?
- What is summarization setting in Power BI?
- What is the difference between data transformation and data modeling?
- What is the difference between measure and calculated column?
- What is type 1 vs type 2 SCD at a high level?
- What issues arise when referential integrity is broken?
- What issues arise with many-to-many relationships?
- What modeling checks should a BA perform before publishing?
- What modeling mistakes commonly impact performance?
- When should bidirectional filtering be avoided?
- Why is CALCULATE central to DAX modeling?
- Why is data modeling critical before visualization?
- Why must fact table grain be clearly defined?
- Why should implicit measures be avoided?
- Why would you create an inactive relationship?
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05_Data Visualization
- How do you choose the right chart for a business question?
- How does poor visualization affect business decisions?
- What are common visualization mistakes in Power BI?
- What checks should a BA perform before finalizing visuals?
- What is a card visual used for?
- What is a KPI visual and when should it be used?
- What is accessibility in data visualization?
- What is annotation and commentary in visuals?
- What is axis scaling and why does it matter?
- What is chart clutter and how does it affect readability?
- What is color theory in dashboards?
- What is conditional formatting and why is it important?
- What is consistency across reports and dashboards?
- What is contextual filtering in visuals?
- What is cross-filtering in Power BI visuals?
- What is cross-highlighting?
- What is data ink ratio conceptually?
- What is data storytelling through visuals?
- What is data visualization in a BI context?
- What is decomposition tree and its analytical value?
- What is drill-down in visuals?
- What is drill-through from a visual?
- What is dynamic titles in Power BI visuals?
- What is exporting visuals and its risks?
- What is heatmap and its use cases?
- What is key influencer visual conceptually?
- What is measure-driven visualization?
- What is misleading visualization?
- What is mobile-friendly visualization?
- What is outlier visualization?
- What is over-visualization?
- What is report-level filter?
- What is responsiveness in visuals?
- What is role of data granularity in visualization?
- What is scatter plot and its business usage?
- What is slicer and how is it used?
- What is small multiples and when should they be used?
- What is sorting and ranking in visuals?
- What is the correct use case for a table vs a matrix?
- What is the difference between comparison and distribution visuals?
- What is the difference between data visualization and reporting?
- What is the purpose of a chart in analytics?
- What is the role of titles and labels in visuals?
- What is threshold-based visualization?
- What is tooltip and how does it add value?
- What is trend visualization?
- What is under-visualization?
- What is use of icons and shapes in dashboards?
- What is visual interaction control in Power BI?
- What is visual perception and why should a BA care about it?
- What is visual performance impact?
- What is visual-level filter vs page-level filter?
- What is waterfall chart and when should it be used?
- What questions should a BA ask stakeholders before designing visuals?
- When should a bar chart be used?
- When should a line chart be used?
- When should a pie or donut chart be avoided?
- Why is data visualization critical for business decision-making?
- Why should colors be used consistently across visuals?
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06_Dashboard Building
- How do dashboards fail even with correct data?
- How do dashboards support decision-making workflows?
- How do you identify the target audience for a dashboard?
- How does data model design affect dashboard performance?
- How is a dashboard different from a report in BI systems?
- How many slicers are ideal on a dashboard and why?
- How should deprecated dashboards be handled?
- What are common dashboard anti-patterns?
- What are data refresh considerations for dashboards?
- What are risks of exporting dashboard data?
- What business questions should a dashboard answer?
- What checks should a BA perform before dashboard sign-off?
- What does performance optimization mean in analytics solutions?
- What feedback should be collected after dashboard delivery?
- What is a dashboard in a business intelligence context?
- What is a strategic or executive dashboard?
- What is a tactical dashboard?
- What is above-the-fold concept in dashboards?
- What is an operational dashboard?
- What is cognitive load in dashboards?
- What is consistency in dashboard design?
- What is dashboard governance?
- What is dashboard maintenance responsibility?
- What is dashboard performance optimization at a high level?
- What is dashboard storytelling?
- What is dashboard usability testing?
- What is dashboard versioning and why is it important?
- What is documentation required for dashboards?
- What is drill-down vs drill-through in dashboards?
- What is export and sharing strategy for dashboards?
- What is global filter vs local filter in dashboards?
- What is guided analytics in dashboard design?
- What is information hierarchy in dashboard design?
- What is iteration cycle in dashboard building?
- What is KPI overload and why should it be avoided?
- What is layout planning in dashboard building?
- What is mobile dashboard design consideration?
- What is page navigation in Power BI dashboards?
- What is personalization in dashboards?
- What is real-time vs near real-time dashboard?
- What is responsive layout in Power BI?
- What is role-based dashboard access?
- What is the primary objective of a business dashboard?
- What is the role of filters and slicers in dashboards?
- What is tooltip-based navigation?
- What is user-driven exploration in dashboards?
- What is visual load and how does it impact users?
- What KPIs should be placed on the top of a dashboard and why?
- What metrics indicate dashboard adoption success?
- What questions should a BA ask before final dashboard delivery?
- What types of dashboards are commonly used in organizations?
- When should drill-through be used in a dashboard?
- Why should dashboards avoid excessive scrolling?
- Why should font, color, and spacing be consistent across dashboards?
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07_Performance Optimization
- How can broken query folding impact refresh time?
- How do many-to-many joins affect performance?
- How do unnecessary columns affect performance?
- How do you validate performance after deployment?
- How does concurrent user access affect performance?
- How does data model size affect Power BI performance?
- How does data volume impact query performance?
- How does number of visuals affect report performance?
- How does poor modeling increase DAX complexity and slow performance?
- How does poor performance affect business adoption of dashboards?
- How does relationship direction affect performance?
- What are common causes of slow Power BI reports?
- What are common performance anti-patterns in BI projects?
- What are common performance bottlenecks in SQL queries?
- What is aggregation at source and when should it be used?
- What is ambiguity in relationships and performance risk?
- What is caching behavior in Power BI?
- What is CALCULATE performance impact conceptually?
- What is cardinality and its impact on model performance?
- What is column encoding and compression conceptually?
- What is composite model performance consideration?
- What is data type optimization in models?
- What is DAX performance optimization conceptually?
- What is DirectQuery performance behavior?
- What is filtering at source vs filtering at report level?
- What is gateway performance impact in Power BI?
- What is Import mode performance behavior?
- What is incremental refresh and how does it improve performance?
- What is indexing and how does it improve query performance?
- What is join order impact on SQL performance?
- What is measure optimization best practice?
- What is model simplification strategy?
- What is overuse of slicers impact on performance?
- What is performance analyzer in Power BI?
- What is Power BI performance optimization conceptually?
- What is predicate pushdown and why is it important?
- What is predicate pushdown and why is it important?
- What is query execution plan at a high level?
- What is query folding and why is it critical for performance?
- What is refresh failure vs slow refresh?
- What is refresh frequency vs performance trade-off?
- What is row context vs filter context impact on performance?
- What is star schema advantage for performance?
- What is the cost of iterators in DAX?
- What is the difference between clustered and non-clustered indexes conceptually?
- What is using variables in DAX and why does it help performance?
- What is visual-level performance optimization?
- What performance checks should be done before publishing reports?
- What performance issues arise with snowflake schema?
- What questions should a BA ask when performance issues arise?
- What should a BA check using Performance Analyzer?
- What SLAs are relevant for BI performance?
- What transformations commonly break query folding?
- Why are complex DAX measures slow?
- Why is performance optimization critical for BI systems?
- Why should BAs understand basic indexing concepts?
- Why should calculated columns be used carefully?
- Why should high-cardinality columns be handled carefully?
- Why should SELECT * be avoided in production queries?
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08_Advanced Analytics
- How do you identify seasonality in business data?
- How does advanced analytics influence strategic decisions?
- How should insights be communicated to non-technical stakeholders?
- What are common forecasting use cases in business?
- What assumptions must be validated in advanced analytics?
- What checks should a BA perform before presenting advanced insights?
- What data quality risks impact advanced analytics results?
- What does advanced analytics mean in a BI and BA context?
- What ethical considerations exist in advanced analytics?
- What is A/B testing conceptually?
- What is ABC analysis conceptually?
- What is anomaly detection conceptually?
- What is baseline comparison in analytics?
- What is benchmarking analysis?
- What is break-even analysis conceptually?
- What is churn analysis at a high level?
- What is cohort analysis conceptually?
- What is confidence interval conceptually?
- What is contribution analysis?
- What is conversion rate analysis?
- What is correlation vs causation?
- What is cumulative analysis (running total)?
- What is cycle time analysis?
- What is descriptive vs diagnostic vs predictive vs prescriptive analytics?
- What is driver analysis?
- What is explainability in analytics results?
- What is forecast accuracy measurement?
- What is forecasting and when should it be used?
- What is funnel analysis?
- What is hypothesis-driven analysis?
- What is index-based analysis?
- What is lead time analysis?
- What is margin analysis?
- What is month-over-month (MoM) analysis?
- What is moving average conceptually?
- What is outlier detection and why does it matter?
- What is Pareto analysis (80/20 rule) in analytics?
- What is productivity analysis?
- What is profitability analysis conceptually?
- What is ranking analysis and business use cases?
- What is retention analysis?
- What is rolling period analysis?
- What is root cause analysis using data?
- What is scenario analysis?
- What is seasonality in data?
- What is segmentation analysis?
- What is sensitivity analysis?
- What is target vs actual analysis?
- What is time series analysis conceptually?
- What is Top-N and Bottom-N analysis?
- What is trend analysis and why is it important for business decisions?
- What is variance analysis?
- What is weighted average and why is it used?
- What is what-if analysis?
- What is year-over-year (YoY) analysis?
- What risks arise from over-interpreting analytics outputs?
- What risks arise from over-interpreting analytics outputs?
- Where does advanced analytics fit in the BI lifecycle?
- Why should BAs be careful with correlation insights?
