NEW BATCH September cohorts open across all programs — No-Cost EMI on every fee.
Free Live Masterclass +91 90888 39993
Careers Ninza — business and startup leadership training
BOOK A CALL NINZA KIDS
NINZA KIDS
Careers Ninza
ANALYTICS LONG-TERM PROGRAM

Business Intelligence & Data Analytics Course

Turn business questions into dashboards and decisions.

DURATION
6 months
FEE
₹49,999
PAYMENT
₹10,000 × 6
FORMAT
Live · online
✓ Live mentor-led classes✓ Lifetime recordings✓ Certificate + placement support
Business Intelligence & Data Analytics course training in India — Careers Ninza, Kolkata
QUICK ANSWERS

Business Intelligence & Data Analytics course fee: ₹49,999 all inclusive, or No-Cost EMI of ₹10,000 × 6 with zero interest.

Duration: 6 months, part-time, with live weekday evening sessions from 7pm IST and weekend workshops.

Format: Live online across India, plus classroom batches in Kolkata, Asansol and Durgapur. Every session recorded and yours for life.

Who it suits: Beginner to job-ready. No prior experience required.

You finish with: A portfolio of three business analyses, a verifiable certificate, and twelve months of placement support.

Roles it prepares you for: Business analyst, BI developer, Data analyst, Reporting analyst, MIS lead.

About the Business Intelligence & Data Analytics course

Analytics that starts from the question a manager actually asks — why did margin drop, which cohort churns, what should we price at — and ends with a model, a dashboard and a recommendation in plain language.

Six months of SQL, modelling and BI reporting, taught around business problems rather than sample datasets. No prior coding required.

Who this program is for

If two or more of these describe you, this is the right course.

— Working professionals moving into analyst or BI roles
— Finance, ops and sales staff who live in spreadsheets
— Managers who need to question the numbers they are given
— Founders who want reporting without hiring a data team
— Graduates targeting a data analyst job with no coding background

What you will learn

1 Write SQL that answers real business questions, not puzzles
2 Model revenue, margin, cohorts and retention
3 Build Power BI and Tableau dashboards a team acts on
4 Clean and reconcile messy operational data
5 Use Excel properly — pivots, lookups, scenario models
6 Present findings to non-technical stakeholders

Business Intelligence & Data Analytics syllabus

12 modules, each taught live and reviewed by a mentor.

1 Module 1 — Business fundamentals for analysts View
•How businesses make money: revenue models, cost structures, contribution margin, operating leverage
•Reading a P&L, balance sheet and cash flow statement well enough to question them
•Unit economics across business types: ecommerce, SaaS, services, lending, marketplace
•Metric definition discipline: why two teams report different revenue, and how to write a metric dictionary
•Framing an analytical question from a vague business request, and recognising unanswerable questions
•Stakeholder mapping: who decides, who is affected, who must be convinced
•The cost of a wrong analysis, and building verification habits before publishing numbers
2 Module 2 — Excel and spreadsheet modelling to professional depth View
•Data structure discipline: tabular data, one fact per row, avoiding merged cells and formatting as data
•Lookup and reference functions: XLOOKUP, INDEX-MATCH, nested conditions, error handling
•Aggregation and array functions: SUMIFS, COUNTIFS, SUMPRODUCT, dynamic arrays, LET and LAMBDA
•PivotTables and PivotCharts including calculated fields, grouping and slicers
•Power Query for repeatable data cleaning: unpivot, merge, append, parameterised refresh
•Building a financial model: assumptions sheet, driver-based projection, scenario switches
•Sensitivity and scenario analysis with data tables and Goal Seek
•Cohort tables, retention curves and waterfall analysis built from raw transaction data
•Auditability: documentation, named ranges, error checks and version discipline
•Dashboard construction in Excel where a BI tool is unavailable
3 Module 3 — SQL from fundamentals to advanced View
•Relational model concepts: tables, keys, normalisation, cardinality, referential integrity
•SELECT, WHERE, ORDER BY, LIMIT and predicate logic including NULL handling
•Aggregation: GROUP BY, HAVING, aggregate functions, and the difference between filtering before and after aggregation
•All join types with worked examples, plus self-joins and cross-joins and when each is correct
•Subqueries, correlated subqueries and CTEs including recursive CTEs
•Window functions in depth: ROW_NUMBER, RANK, DENSE_RANK, LAG, LEAD, running totals, moving averages, partitioned aggregates
•Date and time handling, time zones, fiscal calendars and Indian financial year logic
•String functions, pattern matching, regular expressions and data parsing
•CASE expressions, pivoting and unpivoting in SQL
•Set operations: UNION, INTERSECT, EXCEPT and their performance characteristics
•Query performance: execution plans, indexing, avoiding full scans, and rewriting a slow query
•Writing reporting tables and views, and the discipline of a semantic layer
•Data quality checks in SQL: duplicate detection, referential gaps, outlier flags
4 Module 4 — Data modelling and warehousing concepts View
•OLTP versus OLAP and why reporting on a production database causes problems
•Dimensional modelling: fact and dimension tables, star and snowflake schemas
•Grain definition and the errors caused by mixing grains in one fact table
•Slowly changing dimensions and how to handle attribute history
•Surrogate keys, conformed dimensions and shared dimension design
•ETL versus ELT, and the modern warehouse stack in outline
•Incremental loading, idempotency and handling late-arriving data
•Documentation and lineage so a dashboard number can be traced to source
5 Module 5 — Power BI end to end View
•Power BI ecosystem: Desktop, Service, Gateway, workspaces, deployment pipelines
•Data connection and transformation in Power Query, with query folding awareness
•Building a proper star-schema model rather than reporting from a single flat table
•Relationships, cardinality, cross-filter direction and the ambiguity problems to avoid
•DAX foundations: calculated columns versus measures, and why the distinction matters
•Row context, filter context and context transition — the concepts most learners never resolve
•CALCULATE and filter modifiers: ALL, ALLEXCEPT, KEEPFILTERS, REMOVEFILTERS
•Iterator functions: SUMX, AVERAGEX, RANKX and when they are necessary
•Time intelligence: year-to-date, prior period, rolling periods, custom fiscal calendars
•Advanced measures: dynamic segmentation, ranking, what-if parameters, KPI logic
•Visual design for decision-making: chart selection, layout, colour discipline, accessibility
•Performance tuning: model size, cardinality reduction, aggregations, DAX optimisation
•Row-level security, sharing, refresh scheduling and governance in the Service
6 Module 6 — Tableau and comparative BI practice View
•Tableau architecture: Desktop, Server, Public, and data source types
•Connecting, joining, blending and using extracts versus live connections
•Calculated fields, table calculations, level of detail expressions
•Parameters, sets, groups, bins and hierarchies
•Dashboard and story design, actions, filters and interactivity
•Publishing, permissions and refresh management
•Choosing between Power BI and Tableau for a given organisation and use case
7 Module 7 — Statistics and analytical reasoning View
•Descriptive statistics and the distributions that actually appear in business data
•Sampling, sampling error, confidence intervals and what a margin of error really means
•Hypothesis testing: t-tests, chi-square, and interpreting p-values without over-claiming
•Correlation, causation, confounding and Simpson’s paradox with real examples
•Regression as an analytical tool: interpretation of coefficients, R-squared, residuals, multicollinearity
•A/B test reading: sample size calculation, minimum detectable effect, peeking, and why most business tests are underpowered
•Forecasting fundamentals: trend, seasonality, moving averages, exponential smoothing, and when a simple baseline wins
•Anomaly detection and root-cause decomposition of a metric movement
8 Module 8 — Python for analysts View
•Python essentials: types, control flow, functions, comprehensions, error handling
•Pandas: loading, indexing, filtering, groupby, merge, reshape, time series resampling
•NumPy fundamentals for vectorised computation
•Data cleaning at scale: missing values, type coercion, deduplication, fuzzy matching
•Connecting Python to SQL databases and automating extract routines
•Visualisation with Matplotlib, Seaborn and Plotly for exploratory work
•Automating recurring reports and scheduling scripts
•Working with APIs and JSON, and building a small data pipeline
•Introduction to Jupyter, virtual environments and reproducible analysis
9 Module 9 — Business analytics case practice View
•Revenue decomposition: price, volume, mix and channel effects on a movement
•Margin erosion diagnosis across product, customer and geography
•Churn and retention analysis with cohort construction and survival logic
•Customer segmentation: RFM, value tiers, behavioural clustering and acting on it
•Pricing analysis: elasticity indication, discount effectiveness, promotion cannibalisation
•Marketing analytics: channel contribution, CAC by cohort, attribution limitations
•Operational analytics: capacity, utilisation, throughput, inventory turns, service levels
•Financial analytics: budget versus actual variance analysis and forecast accuracy tracking
•Fraud and anomaly cases in BFSI and ecommerce contexts
10 Module 10 — Communication, storytelling and stakeholder management View
•Structuring an analysis for a decision-maker: conclusion first, evidence second
•Writing a one-page memo that a busy executive will act on
•Visual choices that clarify rather than decorate, and the charts to avoid
•Presenting uncertainty honestly without undermining your own recommendation
•Handling challenge: when the number contradicts a senior person’s belief
•Saying "the data cannot answer that" credibly and offering what would
•Documentation and handover so your work survives your absence
•Live practice: presenting findings to a non-technical audience with feedback
11 Module 11 — Modern data stack, AI assistance and governance View
•Cloud warehouse overview: BigQuery, Snowflake, Redshift — cost model and analyst-relevant differences
•dbt concepts: models, tests, documentation and why analytics engineering emerged
•Version control with Git for analytical work
•Using AI assistants effectively for SQL, DAX and Python — and verifying their output rather than trusting it
•Where AI genuinely helps an analyst and where it produces confident errors
•Data governance: access control, PII handling, DPDP Act awareness for Indian businesses
•Reproducibility and audit trails in regulated environments
12 Module 12 — Capstone and career preparation View
•Project one: business diagnosis end to end — question, SQL, model, dashboard, written memo
•Project two: an operational or marketing analysis with a recommendation and quantified impact
•Project three: a messy public dataset cleaned and analysed with documented decisions
•Published portfolio dashboard with metric definitions an interviewer can inspect
•Live SQL interview practice including window functions and query reasoning under time pressure
•Case interview practice and structured problem-solving out loud
•Resume and LinkedIn positioning for analytics roles, with role-specific targeting
•Mock interviews with working practitioners and written feedback

Tools you will work in

SQL (PostgreSQL / MySQL)Power BITableauAdvanced ExcelGoogle SheetsPython basics

What you walk out with

OUTCOME
A portfolio of three business analyses
OUTCOME
A published executive dashboard
OUTCOME
Interview-ready SQL and case practice

Roles this prepares you for

Salary depends on your city, experience and the strength of your project, so we do not publish package figures we cannot substantiate.

Business analystBI developerData analystReporting analystMIS lead

Fees and payment

TOTAL PROGRAM FEE
₹49,999
All inclusive. No registration or material charges.
PAYMENT PLAN
₹10,000 × 6
No interest, no processing fee. First instalment at enrolment.
✓  Live classes with a working practitioner
✓  Lifetime access to every recording
✓  Weekly doubt-clearing session
✓  Certified project reviewed by a mentor
✓  Rejoin any future batch free if you fall behind

Business Intelligence & Data Analytics training across India

Batches are live online, so learners join from every state. These are the cities we hear from most — each has its own page with local batch and fee details.

See all locations across India →

Business Intelligence & Data Analytics — frequently asked questions

Still unsure? Call an advisor on +91 90888 39993.

What is the Business Intelligence & Data Analytics course fee in India?+

The Business Intelligence & Data Analytics course fee at Careers Ninza is ₹49,999, inclusive of everything. You can pay it as ₹10,000 × 6 under our No-Cost EMI plan, with no interest and no processing charge. The fee covers all live classes, lifetime recordings, weekly doubt-clearing sessions, assessments, the mentor-reviewed capstone project and placement assistance.

Is Business Intelligence & Data Analytics available online across India?+

Yes. Every batch runs live online, so you can join Business Intelligence & Data Analytics from anywhere in India. We currently have students from Kolkata, Asansol, Durgapur, Siliguri, Howrah, Gwalior, Patna, Ranchi, Bhubaneswar, Guwahati, Pune, Mumbai and many other cities, plus learners outside India. On-site delivery is available in Kolkata, Asansol and Durgapur, and on request in other cities for corporate or campus groups.

How long is the Business Intelligence & Data Analytics course and what is the weekly time commitment?+

Business Intelligence & Data Analytics runs for 6 months. Plan on six to eight hours a week: two live weekday evening sessions plus project work, with occasional weekend workshops. Working professionals complete it without taking leave.

Do I need prior experience to join Business Intelligence & Data Analytics?+

Beginner to job-ready. The course starts from first principles and the mentor calibrates pace to the batch. No technical or coding background is required. If a specific prerequisite genuinely matters for your goal, the advisor will tell you honestly on the counselling call rather than take the enrolment.

Who teaches Business Intelligence & Data Analytics?+

A working practitioner in the field, not a full-time trainer. Careers Ninza has more than 100 industry mentors who teach while still doing the job, so the examples come from current work rather than a textbook. You can ask which mentor is assigned to your batch before enrolling, or meet them at a free live masterclass.

What will I build during the Business Intelligence & Data Analytics course?+

One real capstone project, scoped in the first fortnight and carried through every module: a portfolio of three business analyses. It is reviewed by your mentor with written feedback, and it is what interviewers or clients actually discuss with you afterwards.

Is the Business Intelligence & Data Analytics certificate recognised?+

You receive a verifiable Careers Ninza industry certificate with a unique ID and a public verification link, issued by Ninza Career Solutions Pvt. Ltd. once your project is accepted. It is an industry certificate, not a government-accredited degree or diploma, and we say so plainly. Its weight comes from the reviewed project behind it.

Does Business Intelligence & Data Analytics include placement support?+

Yes. Long-term programs include portfolio review, resume and LinkedIn clinics, mock interviews with working professionals, and referrals to our hiring partner network, for twelve months after completion. There is no success fee and no income-share agreement. We do not guarantee employment, and we would be cautious of any institute that does.

What career roles does Business Intelligence & Data Analytics prepare me for?+

Business analyst, BI developer, Data analyst, Reporting analyst, MIS lead. Salary depends on your city, prior experience and the strength of your project, so we do not publish package figures we cannot substantiate; an advisor will give you an honest band for your target role and city.

What if I miss classes or fall behind in Business Intelligence & Data Analytics?+

Every session is recorded and stays yours for life. There is a weekly doubt-clearing slot where you can bring your own work, and if you fall too far behind you may rejoin any future batch of Business Intelligence & Data Analytics free of charge, with no conditions.

How is Business Intelligence & Data Analytics at Careers Ninza different from a recorded online course?+

It is live and never pre-recorded. There is no cheaper self-paced tier, because removing the live class removes the reason the course works. Batches are capped so a quiet student still gets asked questions, and the mentor reviews your project personally rather than auto-marking a quiz.

Can I see a Business Intelligence & Data Analytics class before paying?+

Yes. Careers Ninza runs free live masterclasses every week. Reserve a seat, watch a practitioner teach for ninety minutes, ask questions, and then decide. To enrol or to ask which batch suits you, call +91 90888 39993 or message us on WhatsApp.

How do I enrol in Business Intelligence & Data Analytics?+

Call +91 90888 39993, email [email protected], or send an enquiry on WhatsApp from this page. An advisor confirms whether Business Intelligence & Data Analytics fits your goal, then sends written confirmation of your batch, the fee and No-Cost EMI of ₹10,000 × 6. Seats are capped, so batches close once full.

Business Intelligence & Data Analytics across India — city questions

Same class, same fee, same mentor, wherever you are.

Is Business Intelligence & Data Analytics available in my city?+

Yes. Every batch runs live online, so learners across India attend the same class in real time — including Visakhapatnam, Guwahati, Patna, Raipur, Ahmedabad, Surat, Vadodara, Gurugram, Ranchi, Bengaluru and every other city and town. There is no separate recorded version for students outside Kolkata, and no city has a different curriculum.

Does the Business Intelligence & Data Analytics course fee change by city?+

No. The fee is ₹49,999 everywhere in India, with the same No-Cost EMI of ₹10,000 × 6. We do not price differently for metro and non-metro learners, and there are no travel or centre charges for online batches.

Do you have a classroom centre near me?+

Classroom batches run in Kolkata, Asansol and Durgapur. Everywhere else in India is served by live online delivery, which most working professionals and students prefer. On-site delivery in other cities is available for corporate teams and college groups on request.

What are the batch timings for people in different time zones within India?+

India runs on a single time zone, so timings are identical nationwide: weekday evening sessions from 7pm IST with weekend workshops. Every session is recorded and stays yours for life, so a late shift or travel never costs you a module.

Will placement support help me find work in my own city?+

Yes. Our hiring partner network covers roles across Indian cities, and a growing share of openings are remote and open to candidates anywhere in India. We share your profile only with your consent, for a specific role. We do not guarantee employment.

Other programs you might consider

ENTREPRENEURSHIP Ecompreneurship 6 months · ₹49,999 MARKETING Digital Marketing Entrepreneur 6 months · ₹49,999 GROWTH Performance Marketing & Growth Hacking 3 months · ₹24,999

Seats in every batch are capped

Talk to an advisor for fifteen minutes. We will tell you whether Business Intelligence & Data Analytics fits your goal — or which program does instead.

APPLY NOW CALL +91 90888 39993