What is the difference between Power BI and Excel?

Excel is a spreadsheet for analysis and reporting on smaller datasets. Power BI is a business intelligence tool for building interactive dashboards on larger datasets, with automatic data refresh and sharing.

Power BI Desktop is free for Windows. Publishing and sharing reports requires a Power BI Pro or Premium licence, which is usually provided by the employer.

Data Analytics & Power BI Course in Saraswati Enclave, Gurugram

Who This Course Is For

✅ MIS and Reporting Professionals

You already work with Excel reports and want to move to SQL and Power BI for larger datasets and interactive dashboards.

✅ Graduates from Commerce / Science / Engineering

You want a practical analytics skill that employers test in interviews — and a portfolio project to prove it.

✅ Career Switchers

You are moving into analytics from another field and need structured, honest training — not a bootcamp promise of a ₹12 LPA job.

✅ Business Owners / Managers

You want to build your own sales and operations dashboards without depending on technical staff.

Honest scope: This course prepares you for entry-level analytics and reporting roles. It does not make you a senior data scientist. It does not cover machine learning, deep learning, or advanced statistics. If your goal is data science, Python + statistics + ML is a longer path — this course is a strong first step, not the whole journey.

Course Structure & Modules

Eight modules, each ending with a practical deliverable. You work on a real e-commerce/sales dataset from Module 3 onward.

Module	Topics Covered	Practical Work
1. Analytics Foundations	What data analytics is, types of analytics, data lifecycle, roles and responsibilities	Define a business question and outline the data you need to answer it
2. Excel for Analysis	Data cleaning, SUMIFS, COUNTIFS, XLOOKUP, PivotTables, charts, basic statistical summaries	Analyse a 2,000-row sales file and summarise key metrics
3. SQL Fundamentals	SELECT, WHERE, ORDER BY, GROUP BY, HAVING, DISTINCT, aliases	Write 15+ queries against a sample sales database
4. SQL Joins & Aggregation	INNER, LEFT, RIGHT, FULL joins, UNION, aggregate functions, CASE statements	Combine orders, customers, and products tables to build a report
5. Subqueries & Window Functions	Subqueries, CTEs, ROW_NUMBER, RANK, DENSE_RANK, running totals	Find top-N customers per region; compute month-over-month growth
6. Power BI — Data Preparation	Connecting to Excel/SQL, Power Query, data cleaning, relationships, star schema basics	Build a clean data model from raw sales data
7. Power BI — Visuals & DAX	Cards, bar/line charts, slicers, tables, matrices, DAX measures (CALCULATE, SUMX, time intelligence basics)	Build an interactive sales dashboard with 6+ visuals
8. Portfolio Project	End-to-end project: business question → data → analysis → dashboard → insights presentation	Deliver a complete Power BI report + 1-page insight summary

Python + Pandas introduction is included only if the batch curriculum includes it. [VERIFY WHETHER PYTHON MODULE IS INCLUDED]
Duration: Contact us for the current schedule and total teaching hours.

SQL Examples You Will Practise

Every query below is syntactically correct and runs on standard SQL (MySQL, PostgreSQL, SQL Server). Practise these against the class dataset.

Filter and sort — top 10 orders by amount

SELECT order_id, customer_name, order_date, amount
FROM orders
WHERE status = 'Delivered'
ORDER BY amount DESC
LIMIT 10;

Aggregate by group — monthly sales

SELECT DATE_TRUNC('month', order_date) AS order_month,
       COUNT(*) AS orders_count,
       SUM(amount) AS total_sales
FROM orders
WHERE status = 'Delivered'
GROUP BY order_month
ORDER BY order_month;

Join — sales with customer city

SELECT c.city,
       SUM(o.amount) AS city_sales
FROM orders o
INNER JOIN customers c ON o.customer_id = c.customer_id
WHERE o.status = 'Delivered'
GROUP BY c.city
ORDER BY city_sales DESC;

Subquery — customers who spent above average

SELECT customer_id, customer_name, total_spend
FROM (
  SELECT c.customer_id,
         c.customer_name,
         SUM(o.amount) AS total_spend
  FROM customers c
  JOIN orders o ON c.customer_id = o.customer_id
  GROUP BY c.customer_id, c.customer_name
) t
WHERE total_spend > (SELECT AVG(total_spend) FROM (
  SELECT SUM(amount) AS total_spend
  FROM orders
  GROUP BY customer_id
) x);

Window function — top 3 customers per city

WITH ranked AS (
  SELECT c.city,
         c.customer_name,
         SUM(o.amount) AS total_spend,
         ROW_NUMBER() OVER (PARTITION BY c.city ORDER BY SUM(o.amount) DESC) AS rn
  FROM customers c
  JOIN orders o ON c.customer_id = o.customer_id
  GROUP BY c.city, c.customer_name
)
SELECT city, customer_name, total_spend
FROM ranked
WHERE rn <= 3
ORDER BY city, rn;

Note: DATE_TRUNC works in PostgreSQL. In MySQL, use DATE_FORMAT(order_date, '%Y-%m'). In SQL Server, use DATEFROMPARTS(YEAR(order_date), MONTH(order_date), 1). The class covers the correct syntax for the database you install.

Power BI — DAX Measures You Will Build

Measure	DAX	Purpose
Total Sales	`Total Sales = SUM(Sales[Amount])`	Base measure for all reports
Sales LY	`Sales LY = CALCULATE([Total Sales], SAMEPERIODLASTYEAR(Dates[Date]))`	Year-over-year comparison
YoY %	`YoY % = DIVIDE([Total Sales] - [Sales LY], [Sales LY])`	Growth percentage
Orders Count	`Orders = COUNTROWS(Sales)`	Number of orders
Avg Order Value	`AOV = DIVIDE([Total Sales], [Orders])`	Average order size
Top N Products	Uses `RANKX` with `ALLSELECTED`	Ranking in visuals

Calendar table is essential: Time intelligence functions like SAMEPERIODLASTYEAR require a proper Date table marked as a date table. The course shows how to build one with CALENDAR or CALENDARAUTO and link it to the fact table.

The Portfolio Project

In Module 8, you complete an end-to-end analytics project. This becomes a portfolio piece you can present in interviews.

📁 Dataset

An e-commerce sales dataset with orders, customers, products, returns, and dates. All data is anonymised practice data, not real client data.

❓ Business Questions

Which product categories drive the most revenue? Which cities have high return rates? What is the month-over-month growth trend? Who are the top 20 customers by lifetime value?

🛠️ Tools Used

SQL for extraction and joining, Power Query for cleaning, Power BI for modelling, DAX for measures, and a 1-page written insight summary.

📦 Deliverables

A .pbix file, exported PDF report, and a 1-page written summary. Together, these form the portfolio piece you share with interviewers.

Portfolio honesty: This is a learning project, not professional work experience. Present it in interviews as coursework — honest framing earns more respect than exaggeration. Interviewers can tell the difference.

Job Roles After This Course

Job Role	Typical Tools Tested
Junior Data Analyst	SQL queries, Power BI dashboards, Excel analysis
MIS Analyst	Excel + Power BI, report automation
Reporting Analyst	SQL for data extraction, Power BI visuals
Business Analyst (entry-level)	Data interpretation, dashboard storytelling
Operations Analyst	Excel, SQL, operational KPIs

Honest salary note: Entry-level data analyst salaries in Gurugram typically range from ₹20,000 to ₹35,000 per month for freshers, depending on employer, role, and your overall qualifications (degree, communication, portfolio). This course improves your technical readiness but does not guarantee a specific salary or job. Verify current market rates during your job search.

Technical Interview Questions

Q1: What is the difference between WHERE and HAVING in SQL?

WHERE filters rows before grouping. HAVING filters groups after aggregation. Example: WHERE status = 'Delivered' filters rows; HAVING SUM(amount) > 10000 filters aggregated groups.

Q2: What is the difference between INNER JOIN and LEFT JOIN?

INNER JOIN returns only rows where the join condition matches in both tables. LEFT JOIN returns all rows from the left table, with NULL for unmatched right-table columns. Use LEFT JOIN when you want to keep unmatched records — for example, all customers including those with no orders.

Q3: What is a CTE and when would you use it?

A CTE (Common Table Expression) is a temporary named result set defined with WITH. It improves readability over nested subqueries and can be referenced multiple times in the same query. Use it when the same aggregated logic is needed in multiple places, or when a subquery would become hard to read.

Q4: What is the difference between a calculated column and a measure in Power BI?

A calculated column is computed row-by-row at data refresh and stored in the model — it increases file size. A measure is computed at query time based on filter context — it does not increase file size and is generally preferred for aggregations. Use calculated columns only when you need a row-level value (like a category bucket), and measures for everything aggregate.

Q5: What is filter context in DAX?

Filter context is the set of filters applied to a calculation — from slicers, visuals, rows, columns, or the CALCULATE function. Every measure is evaluated in a filter context. CALCULATE modifies the filter context, which is why it is the most important DAX function to master.

Q6: How do you handle duplicate rows in SQL?

Use DISTINCT to return unique rows, or ROW_NUMBER() OVER (PARTITION BY ... ORDER BY ...) to identify and filter duplicates. For deduplication, ROW_NUMBER is more flexible because you can choose which row to keep.

Q7: What is a star schema in Power BI?

A star schema has one central fact table (transactions — sales, orders) surrounded by dimension tables (customer, product, date). This layout is faster for Power BI than a flat table because relationships are simple and filters propagate cleanly. Always prefer star schema over one wide table for analytics.

Prerequisites & Course Selection

Prerequisites

Basic Excel comfort — entering data, simple formulas, opening files
Comfort with a Windows computer
No programming background required for SQL
If you have never used Excel, complete Basic Computer or Advanced Excel first

Advanced Excel first, or Data Analytics directly?

If you already handle Excel comfortably (SUMIFS, lookups, PivotTables), you can start Data Analytics directly. If your Excel is weak, take Advanced Excel & MIS first — Power BI uses the same thinking, and a shaky Excel foundation slows you down.

Data Analytics vs Python Programming

Data Analytics focuses on querying and visualising data using SQL and Power BI. Python Programming focuses on building programs and logic. Python with Pandas is used for analytics too, but that is a longer path. Choose Analytics if your target role is analyst; choose Python if your target is developer.

Is Power BI free to install?

Power BI Desktop is free for Windows. Publishing to the cloud and sharing reports requires a Power BI Pro licence — typically provided by the employer. The course uses Power BI Desktop, which is enough for the portfolio project.

Frequently Asked Questions

Do I need programming experience for this course?

No. SQL is a query language, not a programming language in the traditional sense. If you are comfortable with Excel formulas, you can learn SQL. Python + Pandas is introduced only if the batch curriculum includes it — confirm during counselling.

What is the fee for the Data Analytics & Power BI course?

Fees vary by batch type, duration, and included modules. Contact us for the current fee structure and a written breakdown. Call +91-88267-66381 or +91-80769-44810.

Can I get a data analyst job after this course?

This course prepares you for entry-level data analyst, MIS analyst, and reporting analyst roles. It does not guarantee a job. We provide placement assistance — resume guidance, portfolio review, interview practice — not a job guarantee.

Which SQL database will I use?

The class uses MySQL or PostgreSQL, both free and widely used. The SQL syntax taught applies broadly to SQL Server and Oracle as well, with minor differences noted where relevant. [VERIFY DATABASE USED IN LAB]

Is Python included?

Python and Pandas are included only if the batch curriculum includes them. If you specifically want Python, consider the dedicated Python Programming course and combine it with Data Analytics.

Can I attend a demo class before paying?

Yes. A free demo class is available. Visit the Saraswati Enclave centre, see the lab, and attend a live session before deciding. Call +91-88267-66381 to book.

Data Analytics & Power BI Course in Saraswati Enclave, Gurugram

Who This Course Is For

✅ MIS and Reporting Professionals

✅ Graduates from Commerce / Science / Engineering

✅ Career Switchers

✅ Business Owners / Managers

Course Structure & Modules

SQL Examples You Will Practise

Filter and sort — top 10 orders by amount

Aggregate by group — monthly sales

Join — sales with customer city

Subquery — customers who spent above average

Window function — top 3 customers per city

Power BI — DAX Measures You Will Build

The Portfolio Project

📁 Dataset

❓ Business Questions

🛠️ Tools Used

📦 Deliverables

Job Roles After This Course

Technical Interview Questions

Prerequisites & Course Selection

Prerequisites

Advanced Excel first, or Data Analytics directly?

Data Analytics vs Python Programming

Is Power BI free to install?

Frequently Asked Questions

Book Your Free Data Analytics Demo Class