Curated interview practice questions with answers. These are practice scenarios, not a verified list of past interview questions.
About Genpact hiring for Power BI roles
Genpact is a professional services company that began as a unit of General Electric in India. It provides business process management, finance and accounting operations, analytics, data and AI services. In India it hires for process associates, business analysts, data analysts, data engineers and data scientists.
For Power BI roles, this Genpact practice set focuses most on Visualisation and Report Design (7), Power BI Service, Sharing and Security (5), DAX Fundamentals (5), Performance Optimisation and Administration (4). It has 14 easy, 16 medium questions, so you can start easy and work up to the harder ones.
Company type
IT services
Headquarters
New York, USA
Main India offices
Gurugram, Hyderabad, Bengaluru, Noida, Kolkata
Genpact Power BI interview process
Online assessment (aptitude + English)
Technical or domain interview
Managerial round
HR round
Typical pattern based on public candidate experiences. Rounds vary by role, team and year.
Solved for GenpactStart practicing
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Incremental refresh partitions a large table by date so each refresh reloads only recent data, such as the last 10 days, while keeping older partitions, such as five years of history, unchanged. It uses the RangeStart and RangeEnd datetime parameters to filter the query, which must fold to the source. It cuts refresh time and load on sources, and can add a DirectQuery partition for real-time data.
02
Explain the typical Power BI workflow from data to insight.
First connect to sources such as Excel, SQL Server or SharePoint and clean the data in Power Query. Then build a data model with relationships, ideally a star schema, and write DAX measures. Next design report visuals and interactions in Desktop. Publish to a workspace in the Power BI Service, set scheduled refresh through a gateway if needed, apply row-level security and share through an app or dashboard.
Bookmarks capture the current state of a report page, including filters, slicers, visual visibility and sort order. They are used for storytelling, toggling between chart and table views with buttons, creating custom navigation, and resetting filters. Combined with the selection pane, they show and hide visuals. Too many bookmarks become hard to maintain, so field parameters are often a simpler alternative for switching measures.
04
What is a calculated table and when would you use one?
A calculated table is created with a DAX expression and stored in the model, recalculated at refresh. Examples are a date table using CALENDAR, a disconnected parameter table for what-if analysis, or a summary table. It is handy but adds memory, and it cannot use Power Query folding. For most shaping tasks, creating tables in the source or Power Query is preferred.
05
How does the VertiPaq engine store and compress data?
VertiPaq is the in-memory columnar engine for Import models. It stores each column separately and compresses it using dictionary encoding, which maps unique values to integers, value encoding for numbers, and run-length encoding for repeated sequences. Compression depends mostly on column cardinality, so columns with few unique values compress very well, while unique IDs and precise timestamps take most of the memory.
06
A report page takes 25 seconds to load. Walk me through how you would fix it.
I would run Performance Analyzer to find the slowest visuals, copy their DAX queries into DAX Studio and check server timings. Common fixes are rewriting measures that iterate large fact tables, removing bi-directional relationships, reducing visuals on the page, and shrinking the model by removing high-cardinality columns. If the source is DirectQuery, I would add aggregations or move to Import. Then re-measure after each change.
07
Each regional manager must see only their region, and the CEO must see everything. How do you implement this?
I would build dynamic RLS with a security table of Email and Region, related to the Region dimension, and a role filter Security[Email] = USERPRINCIPALNAME(). The CEO and other full-access users get an 'All' flag handled in the rule, or are placed in a separate role with no filter. I would test with View as role in Desktop and in the Service before publishing the app.
CALCULATE evaluates an expression in a modified filter context. Its filter arguments can add, replace or remove filters, for example CALCULATE([Total Sales], 'Product'[Category] = "Electronics") replaces any category filter with Electronics. It also performs context transition when used inside a row context, turning the current row into an equivalent filter. It is the most important function in DAX.
09
Why can too many visuals on a page slow down a report?
Each visual sends at least one DAX query when the page loads or when filters change, and visuals render in the browser. A page with 30 visuals, especially complex tables and custom visuals, sends many queries in parallel, competing for capacity and causing long load times. Reducing visuals, combining cards into one multi-row card or using tooltips and drill-through pages improves speed.
A report theme is a JSON file that sets default colours, fonts, visual styles and backgrounds for all visuals. Using a company theme keeps reports consistent with brand guidelines and saves formatting time, since new visuals adopt it automatically. Themes can be built in Desktop's theme customiser or edited as JSON and shared across the team as a standard.
11
What is the relationship between Power BI and Microsoft Fabric?
Microsoft Fabric is Microsoft's unified analytics platform that includes data engineering, data factory, data warehousing, real-time analytics and Power BI as its reporting layer. Power BI workspaces can live on Fabric capacity and use items such as lakehouses and warehouses in OneLake. Direct Lake mode lets semantic models read Delta tables in OneLake directly without a full import, combining fresh data with near-import speed.
12
What is the difference between COUNT, COUNTA, COUNTROWS and DISTINCTCOUNT?
COUNT counts non-blank values in a column, COUNTA counts non-blank values of any type, COUNTROWS counts rows in a table, and DISTINCTCOUNT counts unique values in a column. For example, COUNTROWS(Sales) gives order lines while DISTINCTCOUNT(Sales[CustomerID]) gives active customers. COUNTROWS is generally preferred for counting records because its intent is clearer.
13
What is conditional formatting and where can you apply it?
Conditional formatting changes colours, icons, data bars or font based on values or rules, helping users spot good and bad performance quickly. You can apply it to table and matrix cells, backgrounds, font colour, chart data colours and titles using field values, rules or a measure that returns a colour code. A measure returning hex colours gives full control, such as red when below target.
14
Scheduled refresh fails every night with a gateway error. How do you troubleshoot?
I would check the refresh history error details, confirm the gateway machine is on and the gateway service is running and updated, and verify data source credentials in the gateway connection have not expired. Then test connectivity from the gateway machine to the source and check that the source names in the model exactly match the gateway data source. Gateway logs and network or firewall changes are next.
15
What is a decomposition tree and when is it useful?
The decomposition tree is an AI visual that lets users break down a measure across several dimensions in any order, for example splitting a sales drop by region, then category, then channel. It can also suggest the next split automatically using high value or low value analysis. It is useful for root-cause exploration by business users, though it is less suited to fixed reporting.
16
How do you design a KPI card that shows value, target and variance?
Use the new Card visual or a KPI visual with a main measure such as Total Sales, a target measure and a variance percent measure. Add conditional formatting so the variance turns red below target and green above it, and include a small trend if space allows. Keep labels short, such as Sales vs Target, and show the comparison period in the subtitle.
17
What is a star schema and why is it recommended for Power BI?
A star schema has central fact tables holding numeric events, such as sales lines, linked to dimension tables describing them, such as Date, Product, Customer and Store. Power BI's engine and DAX are optimised for this shape: filters flow cleanly from dimensions to facts, measures are simpler, models compress better and reports run faster. Flat single tables or snowflakes usually need more complex DAX.
18
Why should you use DIVIDE instead of the division operator?
DIVIDE(numerator, denominator, alternate) handles division by zero and blank denominators safely, returning blank or the alternate value instead of an error or infinity. It makes measures like margin percentage cleaner without IF checks. The division operator is slightly faster when you are certain the denominator is never zero, but DIVIDE is the safer default in reports.
19
What are subscriptions and data alerts in the Power BI Service?
Subscriptions email a snapshot of a report page or dashboard to users on a schedule, or after data refresh, with a link to the live content. Data alerts notify users when a value on a dashboard card, KPI or gauge tile crosses a threshold, such as daily sales below a target. Paginated reports support subscriptions with attachments like PDF or Excel. Power Automate can extend alerts into workflows.
20
What are Import, DirectQuery and Live Connection modes?
Import loads a compressed copy of data into the in-memory VertiPaq engine, giving the fastest queries but requiring refresh. DirectQuery sends queries to the source at view time, so data is current but performance depends on the source and some DAX is limited. Live Connection connects a report to an existing semantic model or Analysis Services model without its own model. Composite models mix Import and DirectQuery tables.
Power Query is the data connection and transformation engine in Power BI, Excel, dataflows and Fabric Data Factory. It lets you connect to hundreds of sources and shape data with a recorded series of steps, such as removing columns, changing types, merging and unpivoting. Behind the interface each step is written in the M language. Steps re-run automatically on every refresh, making cleaning repeatable.
22
How do you manage multiple report requests from different departments with tight deadlines?
I log every request with its business goal, deadline and effort, and agree priorities with my manager instead of choosing alone. I reuse shared semantic models so new reports are faster, and I communicate realistic timelines early. In one quarter this helped me deliver eight reports, with two lower-priority ones moved by a week after discussion with requesters, without escalations.
Best Practice Analyzer, in Tabular Editor and also available in Fabric notebooks through semantic link labs, scans a semantic model against a set of rules, such as avoiding bi-directional relationships, hiding foreign keys, not summarising numeric IDs, using DIVIDE, and setting format strings. It lists violations with their severity so teams can fix them before release. Rules can be customised to match team standards.
VAR defines a named value inside an expression and RETURN gives the final result. Variables make measures easier to read, avoid repeating the same calculation, which improves performance, and help debugging because you can return an intermediate variable. A variable is evaluated once in the context where it is defined, so its value does not change if later CALCULATE filters are applied.
25
What is the difference between Power Query M and DAX?
M is the language of Power Query, used at refresh time to extract, clean and shape data before it enters the model, such as merging tables or splitting columns. DAX is used after data is loaded, to define measures, calculated columns and security that evaluate in filter context at query time. As a rule, do row-level shaping in M or the source and dynamic calculations in DAX.
26
What is the difference between a calculated column and a measure?
A calculated column is computed row by row at refresh and stored in the model, so it uses memory and can be used in slicers, filters and relationships, for example Profit = Sales[Amount] - Sales[Cost]. A measure is computed at query time in the current filter context and is not stored, for example Total Profit = SUM(Sales[Profit]). Prefer measures for aggregations and use columns only when you need to slice by the value.
Use sufficient colour contrast and do not rely on colour alone, for example add icons or labels to red and green. Set alt text on visuals, a logical tab order in the selection pane, clear titles and readable font sizes. Avoid tiny text and very dense pages. Power BI supports screen readers and keyboard navigation, and high-contrast themes help users with low vision.
28
What is cross-filter direction and why is bi-directional filtering risky?
Cross-filter direction controls which way filters travel across a relationship. Single direction, from the one side to the many side, is the default and safest. Bi-directional lets the fact table filter the dimension too, which can be useful for slicers showing only relevant values, but it can cause ambiguous paths, unexpected results and slower queries. Prefer single direction and use CROSSFILTER inside specific measures when needed.
29
How do you choose the right chart type in Power BI?
Match the chart to the question. Use bar or column charts to compare categories, line charts for trends over time, stacked bars for part-to-whole across few categories, scatter charts for relationships, maps only for true geographic patterns, cards and KPI visuals for single numbers, and tables or matrices when users need exact values. Avoid pie charts with more than four or five slices.
Parameters are named values used inside queries, such as server name, database, file path or a date range. They let you switch from a development to a production database without editing each query, and they are required for incremental refresh through RangeStart and RangeEnd. Parameters can be changed in the Service under semantic model settings, which helps deployment pipelines between environments.
Tips to crack the Genpact Power BI interview
Learn process improvement basics like Lean and Six Sigma, which have long been part of Genpact's operating style.
Revise Excel, SQL and basic statistics for analytics roles, with examples of reporting or automation you built.
Read about Genpact's origins at GE and its finance and accounting outsourcing business for company questions.
Keep a one-minute story ready for every project on your CV: problem, your part, tools, result.
Practise the hard questions on this page aloud; Genpact interviewers usually ask follow-ups on your first answer.
Frequently asked questions
How many rounds are there in the Genpact Power BI interview?
Candidates usually go through 4 stages: Online assessment (aptitude + English); Technical or domain interview; Managerial round; HR round. The exact rounds change with the role, team, location and your experience, so confirm the process with the recruiter.
Which topics should I prepare for the Genpact Power BI interview?
This practice set leans on Visualisation and Report Design (7), Power BI Service, Sharing and Security (5), DAX Fundamentals (5), Performance Optimisation and Administration (4). Revise those first, then practise explaining one or two of your own projects end to end, because most Genpact interviewers ask you to walk through real work.
Are these the exact questions asked at Genpact?
No. These are curated practice questions that match the skills and difficulty usually tested in it services interviews like Genpact's. They are not a leaked or verified list of past questions.
Where does Genpact hire Power BI professionals in India?
Genpact has large teams in Gurugram, Hyderabad, Bengaluru, Noida, Kolkata. Openings and locations change often, so check the Genpact careers page and filter by city and experience.