Sales performance dashboard
Deliverable: A report over multi-year transaction data with a documented star schema, a proper date table, time-intelligence measures and a written summary of three findings.
Course
Power BI
Power BI taught as a data modelling tool rather than a chart menu — star schemas, relationships and DAX first, because that is what separates a report that scales from one that breaks.
- Duration: 3 months
- Classroom · Online live
- Level: beginner to advanced
What you will be able to do
- Design a star schema and explain why your model has the tables it does
- Transform messy multi-source data into a clean model using Power Query
- Write DAX measures including time intelligence and correct filter context
- Diagnose why a measure returns an unexpected number and fix the underlying model
- Build interactive reports with drill-through, bookmarks and useful navigation
- Publish, schedule refresh and apply row-level security appropriately
Who this course is for
- Working professionals producing recurring reports in Excel
- MIS executives, analysts and finance staff
- Commerce and management graduates entering reporting roles
- Comfort with Excel formulas and PivotTables is helpful, not mandatory
Syllabus
6 modules · 3 months
Module 1. Getting data in
- Connecting to files, folders, databases and web sources
- Power Query transformations that replay on refresh
- Merging and appending queries
- Handling data type and locale problems before they reach the model
- Incremental thinking about refresh and volume
Module 2. Data modelling
- Fact and dimension tables in plain terms
- Star schema, and why a single flat table stops working
- Relationship cardinality and cross-filter direction
- Role-playing dimensions and a proper date table
- Diagnosing ambiguous and inactive relationships
Module 3. DAX foundations
- Calculated columns versus measures, and when each is right
- Row context and filter context, taught with worked examples
- CALCULATE and filter modification
- Iterator functions and when they are needed
- Variables for readable, debuggable measures
Module 4. DAX in practice
- Time intelligence — year to date, prior period, moving averages
- Ranking and top-N patterns
- Percentage of total across different grains
- Handling blanks, division by zero and edge cases
- Performance tuning and avoiding expensive patterns
Module 5. Report design
- Choosing a visual that answers the question asked
- Layout, visual hierarchy and reducing clutter
- Slicers, bookmarks, drill-through and tooltips
- Accessibility and colour choices that survive colour blindness
- Designing for the person who will actually use the report
Module 6. Publishing and governance
- Workspaces, apps and sharing models
- Scheduled refresh and gateways
- Row-level security and testing it properly
- Version control and documenting a model for handover
Tools and technologies you will use
- Power BI Desktop
- Power Query (M)
- DAX
- Power BI Service
- Excel and CSV sources
- SQL sources
Projects you will build
Multi-source model
Deliverable: A model combining at least three differently-shaped sources through Power Query, with the cleaning steps documented and the join logic justified in writing.
Financial reporting pack
Deliverable: A management report with period comparisons, variance measures and drill-through detail, built so that a new month of data requires only a refresh.
Secured published report
Deliverable: A report published to the service with scheduled refresh and row-level security, plus evidence that the security rules were tested from the perspective of each role.
Where this course can take you
- Power BI Developer
- Data Analyst
- MIS Analyst
- Business Intelligence Analyst
- Reporting Analyst
Duration, modes and fees
- Duration
- 3 months
- Delivery modes
- Classroom · Online live
- Fees
- Share your details for the current fee
- Fees vary by batch and delivery mode. Share your details and an advisor will confirm the current fee.
Placement assistance
Every student gets placement assistance — that is what 100% placement assistance means. It is support for all, not a job for all. We do not promise a specific salary, a specific number of interviews, or placement at any named company, and you should be wary of anyone who does.
What is included
- A place in the monthly placement drive, held every third Saturday
- The readiness programme every second Saturday — mock interviews and preparation
- CV review against the specific roles you are targeting
- Portfolio review, so your project work is presented the way a reviewer will read it
- Access to the vacancy pool employers send directly to the Samyak network
- Guidance on which roles realistically fit your background and which do not
- A place in the next drive, with coaching, if you are not selected in this one
What is not included
- Any guarantee of a job, an interview, or a particular salary
- Placement at a named or partner company
- Applying to jobs on your behalf
- Support before you have completed the course and its project work
- Visa, relocation or overseas placement assistance
Why modelling comes before charts
You can learn to build a Power BI visual in an afternoon. Drag a field, pick a chart, adjust the colours. Most Power BI training stops at roughly that level, and its graduates build reports that work beautifully on the demo dataset and fall apart on the second one.
What breaks them is almost always the model. One flat table works until you have two fact tables and need to relate them. Bidirectional filters look convenient until a measure returns a number nobody can explain. A missing date table works until someone asks for year-on-year.
So this course spends its second and third modules on modelling and filter context before it spends serious time on report design. It is slower to feel productive and it is the reason our learners can debug a wrong measure instead of rebuilding the report.
Filter context is the hard part
If DAX feels arbitrary — if measures sometimes give the right answer and sometimes do not, and you cannot say why — the missing concept is filter context.
We teach it with worked examples where the same measure is placed in different visuals and returns different values, and you work out why before we explain it. It is the single highest-leverage concept in the tool, and it is what Power BI interviews probe.
On performance
Slow reports are usually a modelling problem wearing a performance costume. Before reaching for optimisation tricks, the questions are: is the model a star schema, are there calculated columns doing a measure’s job, and are filters travelling in directions they do not need to. The last module covers this with reports we have deliberately built badly for you to fix.
Questions
Power BI — frequently asked questions
Should I learn Power BI or Tableau?
For the Indian job market, Power BI appears in noticeably more job postings, largely because of Microsoft 365 adoption in Indian enterprises. The modelling and visualisation concepts transfer almost entirely, so learning one well and switching later is straightforward. Learning both shallowly is the option we would advise against.
Do I need to know DAX to get a Power BI job?
Yes, and it is usually where interviews separate candidates. Building visuals is quickly learned; writing correct measures requires understanding filter context, which is the genuinely difficult concept in Power BI. Two of the six modules here are DAX for exactly that reason.
Is Power BI enough on its own, or do I need SQL too?
Most Power BI roles expect SQL as well, because the data usually comes from a database and it is far more efficient to shape it before it reaches the model. This course covers connecting to SQL sources; our data analytics course covers writing SQL properly. The combination is what most job postings ask for.
My reports are slow. Will this course help?
Almost certainly, and usually the cause is the model rather than the visuals. Flat tables, bidirectional filters everywhere, calculated columns doing a measure's job and expensive DAX patterns are the common culprits. The modelling and DAX-in-practice modules address each of these directly.
Enquire about Power BI
Three details is all we need. A course advisor will call you back.
Related courses
- Data Analytics
A structured path from spreadsheets to SQL, Power BI and Python, built around the four things a data analyst is actually paid to do — pull the data, clean it, analyse it and explain it.
- Advanced Excel
The Excel that offices actually run on — lookup logic, PivotTables, Power Query pipelines, dashboards and enough VBA to automate the work you repeat every month.
- Data Science
Statistics, Python, SQL and machine learning taught as one connected discipline, with the emphasis on framing a problem correctly and knowing when a result is not real.
Next step
Talk to a course advisor
Tell us what you want to learn and we will help you pick the right course, batch and mode.