Technology Training • Data & Analytics
Data & Analytics Training for Institutions & Organizations
Training that follows data from the database to the decision: writing solid SQL, analysing data in Python, building dashboards people actually use, and moving on to predictive models and the pipelines that feed them.
What the training covers
Modules are selected and sequenced for each cohort. A short workshop may use one or two; a semester course or corporate program can cover all of them.
Module 1
SQL mastery
From the first SELECT to window functions and query tuning, using realistic multi-table datasets rather than toy examples.
- Joins, aggregation and subqueries
- Window functions
- Reading query plans
Module 2
Python for analytics
Cleaning, reshaping and exploring data in code so analysis is repeatable rather than a one-off spreadsheet.
- Pandas
- NumPy
- Exploratory data analysis
Module 3
Business intelligence and dashboards
Designing dashboards around the questions a manager or HOD asks, then building them in the tool your organization uses.
- Power BI
- Tableau
- Data modelling for reports
Module 4
Data warehousing and engineering
How analytical data is stored and moved: modelling a warehouse and building the pipelines that load it.
- Warehouse modelling
- Modern data engineering pipelines
- Data quality checks
Module 5
Predictive modelling
Building, evaluating and explaining a first predictive model on a real dataset, with attention to what can go wrong.
- Regression and classification
- Model evaluation
- Communicating results
Who it is for
Colleges & universities
Students in CSE, IT, AI/DS and MCA programs, plus MBA analytics cohorts, who need practical SQL, Python and BI skills alongside theory.
Organizations & engineering teams
Analysts, reporting teams and engineers moving into data roles, and managers who need to read and question dashboards with confidence.
Prerequisites and lab setup
What learners should know beforehand, and what your lab or IT team needs to have ready. We confirm the final checklist with you before the program starts.
Learner prerequisites
- Comfort with spreadsheets and basic statistics (averages, percentages)
- Python basics for the analytics and modelling modules; the SQL and BI modules need no programming background
Lab and infrastructure
- One laptop per learner (Windows is needed for Power BI Desktop)
- A database such as PostgreSQL or MySQL installed locally or available on a shared server
- Python with Jupyter, or access to a hosted notebook environment
- Licences for Power BI or Tableau if your organization requires them; free editions cover the lab work
How it is delivered
The same data & analytics content can be delivered in different formats, on-site or live online.
Technical workshops
A workshop suits a single skill with a visible result, such as SQL fundamentals or building a first Power BI dashboard.
Semester training
A semester course can run from SQL through Python analysis to a predictive-modelling project on one continuous dataset.
Faculty development (FDP)
Faculty sessions focus on teaching SQL and analytics with realistic datasets and designing assessments that test analysis, not memorisation.
Corporate training
Corporate programs can use your own reporting questions and, where approved, anonymised extracts of your data.
Data & Analytics Training FAQs
Power BI or Tableau: which do you teach?
Either. We teach the one your organization or placement targets use; the data-modelling principles carry over between them.
Can non-CS students take the SQL and dashboard modules?
Yes. The SQL and BI modules assume spreadsheet comfort, not programming. Python-based modules need basic Python, which we can add as a short starter block.
Can we use our own data?
For corporate cohorts we can work on anonymised extracts you approve. For colleges we use public datasets unless the institution provides its own.
Does the program cover data engineering or only analysis?
Both are available. Most cohorts start with SQL and analysis; warehousing and pipelines are added for students or teams heading toward data engineering roles.
What will learners have at the end?
Typically a set of SQL exercises, a Python analysis notebook and a working dashboard built on the same dataset, plus a modelling project for longer programs.
Planning a broader program? See all technology training programs.
Plan Data & Analytics training for your cohort
Share your cohort, current skill level, timeline and lab setup. We will prepare a tailored syllabus and proposal.