Tech Mahindra Power BI Interview Questions & Answers
Curated interview practice questions with answers. These are practice scenarios, not a verified list of past interview questions.
About Tech Mahindra hiring for Power BI roles
Tech Mahindra is an Indian IT services and consulting company and part of the Mahindra Group. It is known for its strong telecom and communications practice and also serves banking, manufacturing and healthcare clients. In India it hires for software engineers, test engineers, network engineers, data analysts and data engineers.
For Power BI roles, this Tech Mahindra practice set focuses most on Power Query and Data Transformation (6), DAX Fundamentals (5), Data Modelling (5), Visualisation and Report Design (4). It has 16 easy, 12 medium, 2 hard questions, so you can start easy and work up to the harder ones.
Company type
IT services
Headquarters
Pune, India
Main India offices
Pune, Hyderabad, Bengaluru, Noida, Chennai
Tech Mahindra Power BI interview process
Online assessment (aptitude + English essay)
Coding test
Technical interview
HR round
Typical pattern based on public candidate experiences. Rounds vary by role, team and year.
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01
What is the difference between static and dynamic RLS?
Static RLS hard-codes values in each role, such as one role per region, which becomes hard to manage as regions grow. Dynamic RLS uses one role with a filter based on the logged-in user, such as Users[Email] = USERPRINCIPALNAME(), with a security mapping table linking users to the regions or managers they may see. Dynamic RLS scales better and is driven by data rather than role edits.
DAX, Data Analysis Expressions, is the formula language for Power BI, Analysis Services and Power Pivot. It is used to create measures, calculated columns, calculated tables and security rules. DAX looks like Excel formulas but works on tables and columns with filter context. Key functions include SUM, CALCULATE, FILTER, ALL, RELATED, time intelligence functions and iterators like SUMX.
Only one active relationship can exist between two tables along a filter path; additional relationships become inactive and appear as dashed lines. For example, Sales may have OrderDate and ShipDate both linked to Date, with OrderDate active. An inactive relationship is used only inside a measure with USERELATIONSHIP, such as CALCULATE([Sales], USERELATIONSHIP(Sales[ShipDate], 'Date'[Date])).
04
Why should you set data types correctly in Power Query?
Correct data types make sorting, filtering, aggregation and relationships work properly; text-typed numbers cannot be summed and mismatched key types break relationships. Types also affect compression and model size, for example whole numbers compress better than decimals or text. Set types once near the end of a query and avoid repeated automatic Changed Type steps, which can fail when column names change.
Context transition happens when CALCULATE, or a measure reference which implicitly wraps CALCULATE, is evaluated inside a row context. The values of the current row are converted into filters on the model. For example, in a calculated column on Customer, [Total Sales] returns that customer's sales because the row becomes a filter. It is powerful but can be slow over large tables and surprising with duplicate rows.
06
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.
07
Every month a new Excel file arrives in a folder. How do you load all of them automatically?
Use the Folder connector, or SharePoint Folder for files on SharePoint, pointing to the folder, filter to the right file extension and naming pattern, then use Combine Files. Power Query creates a sample-file transform function applied to every file and appends the results. New files dropped into the folder are included on the next refresh, as long as their structure matches the sample.
08
How do you add a conditional column in Power Query?
Use Add Column, Conditional Column and define rules, or write M directly:
= Table.AddColumn(Source, "Band", each
if [Amount] >= 100000 then "High"
else if [Amount] >= 25000 then "Medium"
else "Low", type text)
Adding the type at the end avoids an extra Changed Type step. Conditional columns built here are computed at refresh, not at query time.
09
What is the difference between fact and dimension tables?
Fact tables store measurable events at a defined grain, such as one row per order line, with numeric columns like quantity and amount and foreign keys to dimensions. Dimension tables store descriptive attributes used for filtering and grouping, such as product name, category, region or calendar month, with one row per key. Facts are usually long and narrow; dimensions are shorter and wider.
10
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.
Deployment pipelines move content through stages, typically Development, Test and Production workspaces. Creators deploy reports and semantic models from one stage to the next, compare differences, and use deployment rules to change data source connections or parameters for each stage. This supports controlled releases and testing before users see changes. They work alongside Git integration for version control in Fabric workspaces.
12
Write a measure that shows the selected slicer value in a title.
Report Title =
VAR r = SELECTEDVALUE('Store'[Region], "All Regions")
VAR y = SELECTEDVALUE('Date'[Fiscal Year], "All Years")
RETURN "Sales for " & r & " - " & y
Use it in a visual title through conditional formatting, Title text, Field value. SELECTEDVALUE returns the fallback text when zero or multiple values are selected.
SUM aggregates a single column, such as SUM(Sales[Amount]). SUMX is an iterator: it evaluates an expression for each row of a table and then sums the results, such as SUMX(Sales, Sales[Qty] * Sales[Price]). Use SUMX when you need row-level calculations before aggregating. Other iterators include AVERAGEX, MAXX, COUNTX and RANKX.
A good dashboard answers specific questions for a specific audience. Put the most important KPIs at the top left, follow a logical flow from summary to detail, use a few consistent colours with one highlight colour, and choose simple visuals like bar and line charts. Remove clutter such as 3D effects and heavy borders, label clearly, show context like targets or last year, and keep each page to a manageable number of visuals.
15
What is the difference between Group By in Power Query and summarising in DAX?
Group By in Power Query aggregates rows at refresh time and stores only the summarised table, reducing model size, which is useful when detail is never needed. Summarising in DAX through measures keeps detail in the model and aggregates dynamically for any filter at query time. Use Power Query grouping for fixed summaries such as monthly snapshots, and DAX measures when users need flexible slicing.
16
What is a disconnected table and how is it used for what-if analysis?
A disconnected table has no relationship to the model and is used to capture a user's choice through a slicer. For example, a Discount table from 0 to 30 percent created with GENERATESERIES, or the What-if parameter feature, lets a measure read SELECTEDVALUE(Discount[Value]) and calculate projected revenue. Since it does not filter facts, the measure decides how the selection is applied.
17
Write basic measures for total sales, total cost and profit margin percentage.
Total Sales = SUM(Sales[Amount])
Total Cost = SUMX(Sales, Sales[Qty] * Sales[UnitCost])
Profit = [Total Sales] - [Total Cost]
Margin % = DIVIDE([Profit], [Total Sales])
Format Margin % as a percentage. Building measures on other measures keeps logic in one place and easy to change.
18
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.
By default month names sort alphabetically, April first. In the Date table add a Month Number column, select the Month name column, then choose Column tools, Sort by column, Month Number. The same applies to weekday names and fiscal months. The sort column must have one value per name value, otherwise Power BI shows an error.
20
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.
21
What is the difference between drill-down and drill-through?
Drill-down moves within the same visual through a hierarchy, such as Year to Quarter to Month, using the drill buttons. Drill-through moves the user to a separate detail page filtered by the selected item, such as right-clicking a customer to open a Customer Details page. Drill-through pages are set up by adding fields to the drill-through well and include a back button.
Default tooltips show field values when hovering over a data point. Report page tooltips let you design a small custom page, set as a tooltip page type, showing extra visuals like a mini trend chart for the hovered category. They add detail without cluttering the main page. Keep tooltip pages light because they run queries on every hover.
In Table view or Model view, select the date table, choose Table tools, Mark as date table, and select the date column, which must be unique, contiguous and without blanks. This tells Power BI to use it for time intelligence and disables the auto date hierarchy for that table. Also turn off Auto date/time under Options, Data Load to avoid hidden date tables for every date column.
24
What is the difference between ALL, ALLEXCEPT and REMOVEFILTERS?
ALL returns all rows of a table or column ignoring filters, and as a CALCULATE argument it removes filters, useful for percent of total. REMOVEFILTERS does the same removal but only as a CALCULATE modifier and reads more clearly. ALLEXCEPT removes all filters from a table except the listed columns, such as keeping the Year filter while removing others. ALLSELECTED keeps filters from outside the visual, like slicers.
25
Refresh takes 90 minutes because of heavy Power Query steps. How do you speed it up?
I would check query folding with View Native Query or the folding indicators and move non-folding steps after folding ones. Filter rows and remove unused columns as early as possible, push joins and aggregations into SQL views, avoid row-by-row custom functions over large tables, and disable load for staging queries. For large fact tables, set up incremental refresh so only recent partitions reload.
26
Explain how RANKX works and common mistakes with it.
RANKX iterates a table, evaluates an expression for each row and ranks the current value among them. A common pattern is RANKX(ALL('Product'[Product]), [Total Sales]). Mistakes include not using ALL, so every product ranks 1 because only one is visible, ranking over a table with duplicates, and forgetting ties handling with the Dense option. The newer RANK function supports multi-column ordering.
27
How do you explain a data model to a non-technical stakeholder?
I use a simple analogy: the fact table is the list of transactions, and dimensions are the labels we use to slice them, like date, product and region. I show the model diagram with only main tables and explain that slicers work through these links. Then I demonstrate one visual changing when a slicer changes, which makes the idea concrete quickly.
28
What is Microsoft Fabric capacity and how do capacity units work?
Fabric capacity is a pool of compute purchased as F SKUs, from F2 upward, measured in capacity units that all workloads share, including Power BI semantic models, refreshes, notebooks and pipelines. Usage is smoothed over time, so short spikes are allowed, but sustained overuse causes throttling where interactive queries are delayed or rejected. Admins use the Fabric Capacity Metrics app to monitor and plan sizing.
29
What is the difference between Reference and Duplicate in Power Query?
Duplicate copies all the steps of a query into a new independent query, so later changes to the original do not affect it. Reference creates a new query whose source is the output of the original, so it inherits any changes. Reference is useful for building several tables from one staging query, such as dimension tables from a cleaned sales table, while Duplicate is for experimenting separately.
30
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.
Tips to crack the Tech Mahindra Power BI interview
Read about telecom basics like 4G, 5G and network operations, since communications is Tech Mahindra's largest vertical.
Practise English essay and verbal ability sections, which often appear in Tech Mahindra online assessments.
Revise SQL and one programming language, and prepare a clear two-minute explanation of your project.
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; Tech Mahindra interviewers usually ask follow-ups on your first answer.
Frequently asked questions
How many rounds are there in the Tech Mahindra Power BI interview?
Candidates usually go through 4 stages: Online assessment (aptitude + English essay); Coding test; Technical interview; 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 Tech Mahindra Power BI interview?
This practice set leans on Power Query and Data Transformation (6), DAX Fundamentals (5), Data Modelling (5), Visualisation and Report Design (4). Revise those first, then practise explaining one or two of your own projects end to end, because most Tech Mahindra interviewers ask you to walk through real work.
Are these the exact questions asked at Tech Mahindra?
No. These are curated practice questions that match the skills and difficulty usually tested in it services interviews like Tech Mahindra's. They are not a leaked or verified list of past questions.
Where does Tech Mahindra hire Power BI professionals in India?
Tech Mahindra has large teams in Pune, Hyderabad, Bengaluru, Noida, Chennai. Openings and locations change often, so check the Tech Mahindra careers page and filter by city and experience.