Best Data Analytics Institute in Noida: Complete 2026 Guide

Institute | Syllabus OK | Batch fits | Route (min) | Demo date
_________ |             |            |             |
_________ |             |            |             |
_________ |             |            |             |

Questions to prepare
1. How many hours for SQL, and how many SQL exercises?
2. Which BI tool: Power BI, Tableau or both?
3. How many projects, and who reviews them?
4. Is Python included, and at what depth?
5. How do you teach the use of AI assistants in analysis?

-- A fair demo question:
-- "Show monthly revenue and the change from the previous month."
SELECT month,
       revenue,
       revenue - LAG(revenue) OVER (ORDER BY month) AS change_from_prev
FROM (
    SELECT DATE_FORMAT(order_date, '%Y-%m') AS month,
           SUM(amount) AS revenue
    FROM orders
    GROUP BY DATE_FORMAT(order_date, '%Y-%m')
) m
ORDER BY month;

Observation notes
Institute: ____________  Date: ______
Trainer clarity (1-5): ___
Hands-on practice in class: yes / no
Sample project quality (1-5): ___
Tough-question honesty (1-5): ___
Batch size seen: ___

Subject: Confirming details before enrolment
Hello, I would like to enrol in the data analytics course.
Before I pay, please confirm by email:
- Batch name, start date and timing
- Total fee including taxes and any extra costs
- Refund and batch-change policy
- Number of projects and how they are reviewed
- Placement support inclusions
Thank you.

First two weeks plan
Class days: ______
Practice slots: Tue 8-9 PM, Thu 8-9 PM, Sun 10-12
GitHub account created: yes / no
Excel installed and working: yes / no
Goal for week 2: clean and summarise one real dataset

By the end of a good course, your portfolio has:
[ ] An Excel analysis with pivots and a clear summary
[ ] A SQL project answering 10+ business questions
[ ] A Power BI or Tableau dashboard with 4+ visuals
[ ] A Python script that automates a report
[ ] A capstone combining all of the above
[ ] READMEs that explain question, method and insight

Responsible Gen AI skills an analyst should learn
[ ] Drafting SQL or formulas with an assistant
[ ] Checking AI output against the actual data
[ ] Summarising findings, then editing for accuracy
[ ] Never pasting confidential data into public tools
[ ] Explaining which parts were AI-assisted if asked

Final scorecard (1-5)  | Inst. A | Inst. B | Inst. C
Syllabus and depth     |         |         |
Trainer clarity        |         |         |
Hands-on practice      |         |         |
Project quality        |         |         |
Gen AI teaching        |         |         |
Batch and route fit    |         |         |
Written terms          |         |         |
TOTAL                  |         |         |