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Data Analytics Course in Bangalore

Learn to collect, clean, analyse and visualise data with Excel, SQL, Python, Power BI and Tableau at Ascent Software Training Institute (ASTI). The course is built for beginners, fresh graduates and working professionals moving into analytics, and no prior programming experience is required.

  • Statistics, Excel and SQL foundations, then dashboards in Power BI and Tableau
  • Practical assignments and real-world data projects
  • Placement & Career Support: resume building, interview preparation & job opportunities
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Illustration: the kind of SQL + Power BI sales dashboard students learn to build. Figures are sample data.
  • 20,829+learners listed for this course on ascentcourses.com
  • 4.5 Google rating, 973 reviews (checked 6 Oct 2026)
  • ≈ 4 monthsClassroom at BTM Layout or live online
  • CertificateCourse completion certificate from Ascent Software Training Institute
Quick overview

Data Analytics Course at a Glance

In short

ASTI's Data Analytics course is a beginner-friendly program of about four months. It covers statistics, Excel, SQL, Tableau, Power BI and Python for data analysis, and it includes practical projects, a course completion certificate and Placement & Career Support. You can learn in the classroom in BTM Layout, Bangalore, or through live instructor-led online classes.

Course
Data Analytics Course
Suitable for
Students, fresh graduates, non-IT & working professionals, career switchers
Learning mode
Classroom (BTM Layout, Bangalore) or live instructor-led online
Duration
Approximately 4 months
Level
Beginner to advancedNo prior programming experience required
Projects
Real-world data projects & practical assignments
Certification
Course completion certificate from Ascent Software Training Institute
Career support
Resume preparation, mock interviews, interview guidance & placement assistance
Tools covered
Excel · SQL · Python · Power BI · Tableau · Statistics

Fees: ask a career advisor for the current fee  ·  Source for course facts: ASTI Data Analytics course page on ascentcourses.com

See batch timings
Why learn data analytics

What Is Data Analytics?

Definition

Data analytics is the process of collecting, cleaning, analysing and visualising data so that people can make better decisions. A data analyst turns raw data such as sales records, website visits or customer feedback into clear answers, reports and dashboards.

Why do companies use data analytics?

  • To understand what is happening: tracking sales, costs, customers and operations in one view instead of scattered spreadsheets.
  • To find out why it happened: spotting the product, region or customer group behind a rise or a drop.
  • To decide what to do next: comparing options with evidence rather than guesswork, from pricing to staffing to marketing spend.
  • To measure the result: checking whether a change actually worked.

The four types of analytics

These four types are covered in Module 2 of the ASTI syllabus. Each one answers a different question.

01

Descriptive

What happened?

Summaries, totals and trends, such as last quarter's sales by month.

02

Diagnostic

Why did it happen?

Drilling down to find causes, such as which region caused a dip.

03

Predictive

What is likely to happen?

Using patterns and statistics to estimate future outcomes.

04

Prescriptive

What should we do?

Recommending actions based on the evidence.

What does a data analyst do day to day?

  • Talks to a team (sales, finance, marketing, operations) to understand the question they need answered.
  • Pulls data from databases with SQL or from spreadsheets and business systems.
  • Cleans the data by fixing duplicates, missing values and inconsistent formats.
  • Analyses it with Excel, SQL, statistics or Python to find patterns and answers.
  • Builds reports and dashboards in tools such as Power BI or Tableau.
  • Explains the findings in plain language so decision-makers can act on them.

Where does data analytics fit in an organisation?

  1. Step 1

    Data sources

    Billing, CRM, websites, apps, spreadsheets and operations systems create data every day.

  2. Step 2

    Data storage

    Data is stored in databases and data warehouses, often maintained by data engineers.

  3. Step 3 · Data analyst

    Analysis & reporting

    Analysts query, clean, analyse and visualise the data to answer business questions.

  4. Step 4

    Decisions

    Managers, finance, marketing and operations teams act on the insights.

Data Analyst vs Business Analyst vs Data Scientist

The three roles overlap, but each has a different focus. This is a general industry overview, not ASTI-specific information.

AspectData AnalystBusiness AnalystData Scientist
Main questionWhat does the data tell us?What does the business need, and how should the process change?What will happen, and can we build a model to predict it?
Typical workCleaning data, analysis, reports, dashboardsRequirements, process mapping, stakeholder communicationStatistical modelling, machine learning, experiments
Core toolsExcel, SQL, Power BI / Tableau, some PythonExcel, documentation tools, some SQL and BIPython or R, SQL, machine-learning libraries
Coding levelLow to moderateLowModerate to high
Good starting point forBeginners and career switchers who like working with numbersPeople with domain or business-process experiencePeople with strong maths or programming foundations

Interested in models and AI? See the Data Science with Agentic AI & Gen AI course.

Make an informed decision

Is Data Analytics a Good Career for You?

Short answer

Data analytics suits people who are curious, patient with detail and comfortable explaining what they find. You don't need to be a programmer or a maths expert to start, but you do need to enjoy working through problems step by step.

It's a good fit if you…

  • Like working with numbers and dataYou don't mind spreadsheets and enjoy getting figures to add up.
  • Enjoy finding patternsYou notice trends and like asking "why did that change?"
  • Want a technology careerAnalytics is a practical entry point into IT that doesn't require heavy programming.
  • Come from an IT or non-IT backgroundCommerce, science, arts, engineering or work experience can all be useful.
  • Like solving problemsYou enjoy breaking a messy question into smaller steps.
  • Want to work with business dataSales, customers, finance and operations questions interest you.

You may not enjoy it if you…

  • Dislike detail-oriented workChecking data quality is a big part of the job.
  • Prefer to avoid presentingAnalysts regularly explain findings to managers and teams.
  • Don't want to keep learningTools and features change, and good analysts keep practising.
  • Expect results without practiceJob-readiness comes from projects and repetition, not from a certificate alone.
Curriculum

What Will You Learn in the Data Analytics Course?

The course moves from statistics and Excel to SQL, visualisation and Python, finishing with projects and interview preparation. Open a module to see what you learn, what you practise and why it matters in a real job.

M1

Business Statistics & Foundations

Probability, sampling, hypothesis testing, regression
  • Statistical analysis
  • Probability & distributions
  • Sampling techniques
  • Hypothesis testing & estimation
  • Correlation & regression
  • ANOVA & chi-square
  • Data cleaning & imputation
  • Visualisation for decision-making
You learn

How to describe data and test whether a difference is real or just chance.

You practise

Summarising a dataset and testing a simple business hypothesis.

Why it matters

It stops you reporting a "trend" that is really noise.

M2

Introduction to Data Analytics

Types of analytics, descriptive statistics, central limit theorem
  • Descriptive, diagnostic, predictive & prescriptive analytics
  • Business applications
  • Central tendency & dispersion
  • Skewness, kurtosis & graphical techniques
  • Sampling funnel & central limit theorem
You learn

The analytics workflow and the measures used to understand any dataset.

You practise

Profiling a dataset with averages, spread and distribution charts.

Why it matters

Every analysis starts with understanding the shape of the data.

M3

Excel for Data Analysis

Beginner to advanced: functions, pivot tables, dashboards
  • Functions
  • Data cleaning & validation
  • Conditional formatting
  • Text & date functions
  • IF & logical operations
  • Pivot tables & pivot charts
  • Filtering, sorting & slicers
  • Advanced charts & dashboards
You learn

To clean, summarise and chart data quickly in Excel.

You practise

Turning a messy sales sheet into a pivot-based summary dashboard.

Why it matters

Excel remains the everyday analysis tool in most business teams.

M4

SQL for Data Analytics

Queries, joins, subqueries, aggregation
  • Databases & SQL
  • SELECT queries
  • Filtering, sorting & joins
  • Subqueries & set operations
  • DML & DDL commands
  • Functions & conditional expressions
  • Aggregation & group functions
  • Managing database objects
You learn

To retrieve and combine data from relational databases.

You practise

Joining orders, customers and products tables to answer business questions.

Why it matters

Most company data lives in databases, and SQL is how analysts reach it.

M5

Advanced SQL & Data Handling

Multiple tables, transformation, large datasets, time-based analysis
  • Working with multiple tables
  • Data extraction & transformation
  • Regular expressions
  • Large dataset handling
  • Time-based data analysis
You learn

To prepare larger, messier data for analysis.

You practise

Writing month-over-month and year-over-year trend queries.

Why it matters

Real business data is big, messy and time-based.

M6

Tableau: Data Visualisation

Connections, charts, dashboards & storytelling
  • Connecting to data sources
  • Data blending & joins
  • Bar, line, pie, heatmap, histogram, funnel, Gantt & dual-axis charts
  • Dashboards & storytelling
  • Filters & parameters
  • Maps & geographic data
  • Calculations
You learn

To choose the right chart and build interactive views.

You practise

Building a filterable dashboard that tells a clear story.

Why it matters

Insights only help when people can understand them quickly.

M7

Tableau Dashboards & Server

Layout, interactivity, publishing
  • Dashboard creation & layout design
  • Interactive filters
  • Publishing dashboards
  • Tableau Server & Online
You learn

To design and share dashboards for other people to use.

You practise

Publishing a dashboard for a stakeholder audience.

Why it matters

A dashboard is only useful when the team can open and use it.

M8

Power BI

Transformation, data modelling, DAX, reports & sharing
  • Setup, data sources & connections
  • Data transformation
  • Reports & dashboards
  • Filters, slicers & custom visuals
  • Publishing reports
  • Data modelling
  • DAX functions
  • Power BI Service & sharing
You learn

To model data and build interactive business reports.

You practise

Writing DAX measures for a KPI report and publishing it.

Why it matters

Power BI is widely used for business reporting and dashboards.

M9

Python for Data Analytics

Python basics through an introduction to data analysis
  • Python basics & syntax
  • Data types & data structures
  • String operations
  • Input/output handling
  • Operators & functions
  • Introduction to data analysis with Python
You learn

Enough Python to read, process and summarise data with code.

You practise

Writing a script that reads a file and produces a summary.

Why it matters

Python automates repetitive work and handles data beyond spreadsheet limits.

+

Projects & Interview Preparation

Real-world projects, resume, mock interviews
  • Real-world data projects
  • Resume preparation
  • Mock interviews
  • Interview guidance
You learn

To present your projects and explain your analysis clearly.

You practise

Mock interviews and project walkthroughs.

Why it matters

Employers hire people who can show and explain their work.

Tools you will use

Data Analytics Tools Covered in the Course

In one line

The course covers Excel, SQL, Python, Power BI and Tableau, along with the statistics needed to use them well.

  • Microsoft Excel

    Cleaning data, formulas, lookups, pivot tables and charts. Most analysis starts in a spreadsheet.

    Module 3
  • SQL

    Querying databases: filtering, joining, grouping and summarising large tables.

    Modules 4–5
  • Python

    Python basics for reading, processing and summarising data with code.

    Module 9
  • Power BI

    Data modelling, DAX, interactive reports and sharing through Power BI Service.

    Module 8
  • Tableau

    Visual analysis, calculated fields and publishing dashboards.

    Modules 6–7
  • Statistics

    Averages, spread, distributions and sampling, so you can trust what the numbers say.

    Modules 1–2

Tool list from ASTI's published Data Analytics syllabus.

Learning journey

From Beginner to Job-Ready: How the Course Progresses

Each stage builds on the one before it. You start with fundamentals and finish by presenting projects and preparing for interviews.

  1. 01

    Beginner

    No coding background needed

  2. 02

    Statistics & fundamentals

    Modules 1–2

  3. 03

    Excel

    Module 3

  4. 04

    SQL & data handling

    Modules 4–5

  5. 05

    Tableau & Power BI

    Modules 6–8

  6. 06

    Python

    Module 9

  7. 07

    Projects, portfolio & interview prep

    Resume and mock interviews

  8. 08

    Career

    Apply for analyst roles

Order follows ASTI's published Data Analytics syllabus.

Real-world projects

Data Analytics Project Examples

How to read this

These are example projects showing the kind of problems analysts solve with the tools in this course. Each one follows the same path: problem → data → analysis → output → insight. Ask a career advisor about the projects in the current batch.

Sales performance dashboard

Example project
Problem
Monthly sales dropped, but nobody knows which region or product caused it.
Data
Order-level sales with date, region, product, quantity and price.
Analysis
Clean in Excel, compare month-on-month by region and category in SQL.
Output
Power BI dashboard with KPIs, trend line and region filters.
Insight
Pinpoints which segments drove the drop so the team knows where to act.

Customer behaviour analysis

Example project
Problem
A store wants to know which customers buy repeatedly and which stop.
Data
Customer IDs, purchase dates and order values.
Analysis
Group customers by recency, frequency and spend using SQL and Python.
Output
Customer segment table and a Tableau view of each segment.
Insight
Shows which customer groups to retain and which to win back.

Marketing campaign analysis

Example project
Problem
Several campaigns ran; which ones were worth the spend?
Data
Campaign spend, clicks, leads and conversions by channel.
Analysis
Calculate cost per lead and conversion rate in Excel; compare channels.
Output
Channel comparison report with charts.
Insight
Identifies the channels with the best return for the next budget.

Financial budget vs actuals

Example project
Problem
Department spending is going over budget in some months.
Data
Monthly budget and actual expense by department and cost head.
Analysis
Variance calculation and trend review with DAX measures.
Output
Variance report in Power BI with drill-down by department.
Insight
Highlights the cost heads that need attention first.

Operations delivery delays

Example project
Problem
Customers complain about late deliveries.
Data
Order, dispatch and delivery timestamps with warehouse and route.
Analysis
Calculate delivery times in SQL; compare by warehouse, route and weekday.
Output
Operations dashboard showing on-time rate and delay hotspots.
Insight
Shows where delays come from so operations can fix the right step.

E-commerce funnel analysis

Example project
Problem
Many visitors add items to the cart but don't buy.
Data
Session events: product view, add to cart, checkout, purchase.
Analysis
Build the funnel and drop-off rates by device and category with Python.
Output
Funnel chart and drop-off summary.
Insight
Points to the step where most buyers are lost.
Teaching approach

How the Data Analytics Course Is Taught

  • Instructor-led classes

    Live sessions in the BTM Layout classroom or online with a trainer.

  • Industry-experienced trainers

    Trainers who bring industry experience into the classroom.

  • Hands-on practice

    You work in the tools during class, not only watch slides.

  • Practical assignments

    Exercises after each topic to apply what you learned.

  • Real-time projects

    Projects with business-style datasets that you can discuss in interviews.

  • Doubt clearing

    Students mention patient doubt clearing in their reviews.

  • Study material

    Course notes and reference material.

  • Interview preparation

    Resume preparation, mock interviews and interview guidance.

Try a free demo class first

ASTI offers a free demo class so you can see the teaching style before you enrol. Weekday and weekend batches are available.

Data Analytics batch timings
DaysBatch timings
Mon – Fri8–10 AM12–2 PM6–8 PM7–9 PM
Sat – Sun8–10 AM12–2 PM
Next batchAsk on WhatsApp
Placement & Career Support

Resume Building, Interview Preparation & Job Opportunities

Career support runs alongside the course so you're ready to apply when you finish. ASTI shares job opportunities and arranges interviews for eligible students.

Important

Placement assistance does not guarantee a job. Hiring decisions depend on the employer and the candidate.

See companies where ASTI students work.

  • Career guidance

    Advice on which analyst roles match your background and how to position yourself.

  • Resume building & profile optimisation

    Help presenting your projects and skills on your resume and LinkedIn profile.

  • Mock interviews

    Practice technical and HR rounds, with feedback on what to improve.

  • Interview guidance

    Common SQL, Excel and Power BI questions, and how to explain your projects.

  • Placement assistance & job opportunities

    Job openings and interview opportunities shared with eligible students.

Eligibility

Who Can Join the Data Analytics Course?

Short answer

Anyone comfortable with basic computer use can join. No prior programming experience is required.

  • Fresh graduates

    Start a career in analytics after your degree.

  • Non-IT professionals

    Move into a data role from sales, finance, operations or support.

  • Working professionals

    Switch careers or add data skills to your current role.

  • Business & marketing professionals

    Make better decisions with your team's own data.

  • Entrepreneurs

    Understand sales, customers and costs in your business.

Coding experience

Not required

Training mode

Classroom or live online

Batches

Weekday & weekend

Career options

Jobs You Can Apply for After a Data Analytics Course

Short answer

Common entry roles are Data Analyst, Business Analyst, Reporting Analyst, MIS Analyst and Business Intelligence (BI) Analyst. Salaries vary by company, city, skills and experience, so we don't quote salary figures here.

  • Data Analyst

    Cleans and analyses data to answer business questions and reports the findings.

    SQL · Excel · Python
  • Business Analyst

    Turns business needs into requirements and uses data to recommend changes.

    Excel · SQL · Power BI
  • Reporting Analyst

    Builds and maintains regular reports so teams can track performance.

    Excel · Power BI
  • MIS Analyst

    Manages management information systems and periodic MIS reports.

    Excel · SQL
  • BI Analyst

    Designs dashboards and data models that teams use to make decisions.

    Power BI · Tableau · SQL
Sectors that hire analysts:ITE-commerceBanking & financeHealthcareMarketing
Self-check

Data Analyst Skills Checklist

Tick the skills you already have. It's a quick way to see where you are starting from. Nothing is saved or sent anywhere.

Student testimonials

What ASTI Power BI Students Say

Power BI is one of the tools in this course. These reviews are from ASTI's Power BI learners, published on ascentcourses.com and shown as written.

Power BI
I joined for Power BI training under the trainer Asif Hussain sir the way he teaches is awesome. He even helped us in getting placed. The…
Soft skills, resume & interview preparation
FNFaizan NachanPower BI learner
Power BI
I joined for POWER BI training at Ascent Software Training Institute. I got very good support from my trainer and from institute too. My doubts were…
Interviews scheduled after course completion
SCSai Krishna ChowdaryPower BI learner
Power BI
I have completed Power BI from ASCENT SOFTWARE TRAINING INSTITUTE . Very good institute. Trainer is Asif Hussain he is very good at teaching. The placements…
CMChandra MohanPower BI learner
Power BI
I have completed Power BI course at Ascent Software Training Institute under Asif Sir. Training was really good, knowledgeable and I suggest everyone to take up…
AGAmogh GaonkarPower BI learner
Power BI
I did Power BI course in Ascent Software Training Institute, trainer (Asif Hussain) teaching was absolutely good and I would suggest everyone to join here and make your investment worthy.
MSMohammed SufiyanPower BI learner
Power BI
Hello , this is Yashwanth Sharma. I took a courses on Power BI at Ascent Software Training Institute. I thank to Asif sir ,for providing such…
YSYashwanth SharmaPower BI learner
Student videos

Student Feedback & Inside an ASTI Power BI Class

Student feedback videos and recorded Power BI classes from ASTI's official YouTube channel.

Watch more on YouTube
Student experience

Here's my honest experience at Ascent

Student experience

My honest experience at Ascent

Class recording

Power BI Dashboard Tutorial for Beginners

Class recording

Power BI Class 13: Build Interactive Dashboards & Reports

Source: ASTI official YouTube channel
Google Reviews

Google Reviews from ASTI Students

4.5 Based on 973 Google reviews (checked 6 Oct 2026)

Independent reviews from ASTI's Google Business Profile, covering all courses. Shown exactly as written.

SA Shaik ApsanaGoogle review
I took SQL and Power BI training. The trainer is excellent with deep knowledge in both subjects. He explains every concept from basic to advanced in a very simple and…
PS prathit sahuGoogle review
Accent Software Training Institute is a very good place to learn IT skills like Power BI, SQL, PowerApps, and Power Automate and other IT skills as well. Even if you…
AV Abishek VGoogle review
I had a very good learning experience at Ascent Software Training Institute. The trainers explained Java, Selenium, Manual Testing and SQL concepts clearly with practical examples. They were patient while…
Why you can trust this page

About Ascent Software Training Institute (ASTI)

Ascent Software Training Institute (ASTI) is an IT training institute in BTM Layout, Bangalore, offering classroom and live online courses in data analytics, data science, cyber security, cloud and full stack development.

EExperience
  • 20,829+ learners trained, as published by ASTI
  • Classroom training in BTM Layout plus live online batches
EExpertise
  • Industry-experienced trainers
  • Published 9-module syllabus with downloadable PDF
AAuthority
  • 4.5★ from 973 Google reviews
  • Student videos on ASTI's official YouTube channel
TTrust
  • No job guarantee claims; placement assistance only
  • Reviews shown with their source
  • Clear address, phone and email

Institute details

Name
Ascent Software Training Institute (ASTI)
Address
#96, 2nd Floor, 100 Ft Ring Road
Near Mico Layout, Above Apollo Pharmacy
BTM 1st Stage, Bengaluru, Karnataka – 560029
Phone
080-4219 1321 · 90350 37886
Email
hr@ascentcourses.com
Hours
Mon–Sat 8:00 AM – 7:30 PM · Sun 8:00 AM – 2:00 PM
Certificate
Course completion certificate from ASTI

Visit or message us

Walk in for a free demo class, call during office hours, or message us on WhatsApp any time.

FAQ

Data Analytics Course FAQs

Can't find your answer? A career advisor can help you decide whether this course fits your goals.

What is a data analytics course?

A data analytics course teaches you to collect, clean, analyse and visualise data so you can answer business questions. At ASTI it covers statistics, Excel, SQL, Tableau, Power BI and Python, with practical projects.

How long is the Data Analytics course at ASTI?

The course runs for approximately 4 months. A career advisor can share the schedule for the next batch.

What are the fees for the Data Analytics course?

Fees depend on the batch and the training mode (classroom or online). Talk to a career advisor or message us on WhatsApp for the current fee and any offers.

Do I need coding experience to join?

No. No prior programming experience is required. SQL and Python are taught from the basics.

Which tools will I learn?

Microsoft Excel, SQL, Tableau, Power BI and Python, plus the statistics needed to interpret data correctly.

Is the course available online?

Yes. You can join classroom training at ASTI in BTM Layout, Bangalore, or live instructor-led online training.

What are the batch timings?

Weekday batches run Monday to Friday at 8–10 AM, 12–2 PM, 6–8 PM and 7–9 PM. Weekend batches run Saturday and Sunday at 8–10 AM and 12–2 PM.

Will I work on real projects?

Yes. The course includes real-time, hands-on projects using business-style datasets, so you have work to show and discuss in interviews.

Does ASTI provide placement assistance?

Yes. ASTI provides placement assistance, including career guidance, resume building, profile optimisation, mock interviews, interview guidance and job opportunities.

Is there a job guarantee?

No. Placement assistance does not guarantee a job, because hiring decisions depend on the employer and the candidate.

Will I get a certificate?

Yes. You receive a course completion certificate from Ascent Software Training Institute.

Can freshers and non-IT professionals join?

Yes. The course suits fresh graduates, non-IT professionals, working professionals changing careers, business and marketing professionals, and entrepreneurs.

What jobs can I apply for after this course?

Common roles include Data Analyst, Business Analyst, Reporting Analyst, MIS Analyst and Business Intelligence (BI) Analyst, across sectors such as IT, e-commerce, banking and finance, healthcare and marketing.

What is the difference between data analytics and data science?

Data analytics focuses on explaining what happened and why, using tools like SQL, Excel and Power BI. Data science goes further into predictive models and machine learning, and usually needs more programming and maths.

Is data analytics hard to learn?

It is learnable for most people who practise regularly. The tools are approachable, and the main challenge is building the habit of checking data carefully and explaining results clearly.

Can I attend a demo class before joining?

Yes. ASTI offers a free demo class. Use the Talk to a Career Advisor button or call 080-4219 1321 to book one.

Where is ASTI located?

Ascent Software Training Institute is at #96, 2nd Floor, 100 Ft Ring Road, near Mico Layout, above Apollo Pharmacy, BTM 1st Stage, Bengaluru, Karnataka – 560029.

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