Data Analytics

Master Data Analytics Online: Professional Certification and Practical Training with ASAP Kerala

Master data-driven decision-making with our top online Data Analytics course. Skillspark provides expert training in Excel, SQL, Tableau, and Power BI…

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Upgrade your skills and be competent for the on demand jobs with this Data Analytics Course

Syllabus - What will you learn in Data Analytics course

Advanced Excel for Data Analytics

Master Data Organisation and Formatting

Clean and structure datasets using tables, filters, and data validation
Use conditional formatting to highlight trends, exceptions, and deadlines
Design standardised templates for recurring tasks across departments

Perform Advanced Calculations and Analysis

Apply key formulas such as VLOOKUP, XLOOKUP, IF, INDEX-MATCH, TEXT, DATEDIF, and ARRAY formulas
Use SUMIFS, COUNTIFS, and AVERAGEIFS to create data summaries for multiple criteria
Perform cross-sheet and multi-file lookups to consolidate information

Visualize and Summarize Data for Decision-Making

Build Pivot Tables, Pivot Charts, and interactive dashboards
Use slicers, timelines, and linked charts to drill into key metrics
Automate report generation and refresh with dynamic formulas

Apply Excel Skills in Different Departments

1. Finance & Accounting

Automate monthly budgeting and reconciliation
Analyze expense patterns and predict overspending
Project: Create a budget vs. actual variance tracker with auto-highlighting of discrepancies

2. Human Resources (HR)

Manage attendance, leave, payroll, and attrition reports
Analyze employee turnover trends and headcount movement
Project: Build an HR dashboard to monitor employee status, probation, and resignation patterns

3. Marketing & Campaign Analysis

Track campaign performance across channels
Analyze ROI based on leads, conversions, and cost per acquisition
Project: Design a campaign effectiveness dashboard with traffic, cost, and conversion trends

4. Operations & Inventory Management

Monitor stock levels, reorder points, and wastage
Automate inventory inflow-outflow reports and procurement needs
Project: Develop a real-time inventory tracker with stock alerts and movement logs

5. Sales & Business Development

Track team-wise, product-wise, and region-wise sales targets
Analyze sales funnels, performance ratios, and closure rates
Project: Build a sales pipeline dashboard with monthly targets, conversion rates, and forecast

Ensure Accuracy and Team Collaboration

Use data protection, and track changes for secure collaboration
Share auto-updating reports through OneDrive, Google Drive, or Teams integration
Implement backup, versioning, and printing standards for documentation

AI Prompt Engineering for Data Analytics Professionals

This course enables working professionals in Data Analytics to use Prompt Technology as an analytical assistant to:

understand complex datasets
build accurate formulas and queries
debug errors faster
design advanced calculations confidently
translate business logic into analytical logic

The focus is not on replacing analytical skills, but on augmenting human reasoning with AI.

Module 1: Prompt Engineering Fundamentals for Analytical Work

Pain Point:
Analysts receive wrong answers from AI due to poorly framed questions.

How It Helps:
Teaches how to instruct AI with proper data context, rules, and expectations.

Industry Impact:
AI literacy is now expected from modern analysts.

Practical Projects:
Analytics prompt testing | Logic breakdown exercise | AI validation practice

Module 2: Analytical Prompt Frameworks for Complex Logic

Pain Point:
Complex formulas break because logic is unclear.

How It Helps:
Forces AI to explain logic before writing formulas.

Industry Impact:
Improves calculation accuracy and confidence.

Practical Projects:
Logic-first prompting | Formula explanation workflow | Error-prevention checklist

Module 3: Understanding Complicated Datasets Using AI

Pain Point:
Analysts often work on data they did not create.

How It Helps:
AI explains dataset structure and business logic quickly.

Industry Impact:
Reduces dependency on others and speeds onboarding.

Practical Projects:
Dataset explanation prompt | KPI definition mapping | Data dictionary creation

Module 4: AI-Assisted Data Cleaning & Transformation

Pain Point:
Data preparation consumes most project time.

How It Helps:
AI creates and explains cleaning logic clearly.

Industry Impact:
Faster and more reliable analysis cycles.

Practical Projects:
Cleaning logic generation | SQL transformation explanation | Data quality checklist

Module 5: Prompt Technology for Complex Excel Formula Creation

Pain Point:
Complex Excel formulas are difficult to design and troubleshoot.

How It Helps:
AI breaks formulas into step-by-step logic before writing them.

Industry Impact:
Significantly improves Excel efficiency and accuracy.

Practical Projects:
Complex salary calculation formula | Multi-condition lookup | Formula debugging workflow

Module 6: Prompt Technology for Advanced SQL Query Building

Pain Point:
SQL queries fail due to logic confusion.

How It Helps:
AI converts business logic into clean SQL structure.

Industry Impact:
Improves query performance and accuracy.

Practical Projects:
Complex reporting SQL | CTE-based transformation | SQL error diagnosis

Module 7: Prompt Engineering for DAX & Power BI Measures

Pain Point:
DAX measures often produce incorrect results.

How It Helps:
AI explains filter context and builds logic step-by-step.

Industry Impact:
Essential for Power BI analysts.

Practical Projects:
Sales growth measure | YTD/MTD calculation | DAX debugging guide

Module 8: Exploratory Data Analysis (EDA) Using Prompts

Topics Covered:
EDA roadmap | Trend detection | Segment analysis | Root cause exploration | Hypothesis testing prompts

Pain Point:
Analysts don’t know where to begin analysis.

How It Helps:
AI suggests structured exploration paths.

Industry Impact:
Improves analytical thinking depth.

Practical Projects:
EDA plan creation | Insight discovery worksheet | Pattern identification report

Module 9: Insight Writing & Business Storytelling

Topics Covered:
Executive summaries | KPI explanations | Recommendation writing | Risk articulation | Visualization narration

Pain Point:
Strong analysis fails due to poor explanation.

How It Helps:
AI translates technical findings into business language.

Industry Impact:
Enhances analyst visibility and promotion potential.

Practical Projects:
Management insight report | Dashboard narration | Recommendation summary

Module 10: AI Integration with Analytics Tools

Topics Covered:
Excel Copilot | Power BI Copilot | SQL AI tools | Python notebooks | Automated insight generation

Pain Point:
AI is used outside analytics tools.

How It Helps:
Brings AI directly into workflows.

Industry Impact:
Major productivity advantage in analytics teams.

Practical Projects:
Copilot-driven analysis | Auto-insight generation | Prompt reuse system

Module 11: AI Validation, Data Governance & Ethics

Topics Covered:
Hallucination control | Data privacy | Bias detection | Validation framework | Audit documentation

Pain Point:
Blind trust in AI risks incorrect decisions.

How It Helps:
Ensures analyst-controlled outputs.

Industry Impact:
Protects professional credibility.

Practical Projects:
AI validation checklist | Bias risk review | Governance documentation

Module 12: Capstone Project – AI-Assisted Analytics Simulation

Pain Point:
Analysts struggle to combine skills into one workflow.

How It Helps:
Simulates real corporate analytics projects.

Industry Impact:
Creates job-ready AI-enabled analysts.

Practical Projects:
End-to-end analytics case | Prompt library | Executive presentation

Data Visualization and Reporting Using Power BI

Import and Clean Data for Analysis

Connect Power BI to data sources such as Excel, Google Sheets, CSV, or cloud databases
Use Power Query to clean, transform, and merge datasets
Create data models by building relationships across multiple tables

Create Interactive Dashboards and Visual Reports

Build live dashboards with visuals like:
- Bar, line, and pie charts
- Cards, slicers, filters, and gauges
- Tree maps, matrix tables, and trend lines
Make dashboards interactive for user-driven analysis

Automate Business Reporting

Set up scheduled data refresh and auto-generated reports
Share dashboards with managers or clients through Power BI Service
Use role-level security to manage who sees what

Apply Power BI in Real-World Business Fields

1. Finance & Accounting

Track expenses, income, profit margins, and financial KPIs
Visualize trends in monthly spending and budget adherence
Project: Create a financial performance dashboard showing monthly income vs. expense with variance indicators

2. Human Resources (HR)

Monitor hiring, retention, attendance, and training metrics
Visualize attrition rate, headcount trends, and performance distributions
Project: Build an HR analytics dashboard displaying employee lifecycle metrics and department-wise turnover

3. Marketing & Campaign Performance

Analyze lead sources, campaign ROI, ad spend, and conversion funnels
Visualize engagement metrics over time, geography, and platform
Project: Design a marketing campaign performance dashboard showing cost-per-click, leads, and conversion efficiency

4. Operations & Logistics

Monitor stock movement, delivery time, procurement cycles, and usage trends
Identify bottlenecks and wastage across stages
Project: Build an operations dashboard to track supply chain performance and material availability

5. Sales & Business Development

Visualize team-wise sales performance, targets, and customer acquisition
Forecast sales trends based on historical data
Project: Create a sales performance dashboard with filters by team, product, and region showing progress toward targets

Publish, Collaborate, and Present Data-Driven Insights

Publish reports to the web or organization-wide Power BI workspace
Collaborate in real time using shared dashboards
Present insights in meetings with interactive, drill-down capabilities

Smart Data Collection Techniques

Google Forms for Data Collection

Design professional, user-friendly forms for:
- Surveys
- Registrations
- Feedback
- Internal requests and approvals
Customize themes, response types, and validation rules to ensure clean data entry

Automate Workflow with Form Settings and Logic

Enable email notifications, confirmation messages, and form branching (conditional questions)
Set up limited access forms and response tracking
Use pre-filled links for personalized data collection

Link Responses to Google Sheets for Real-Time Analysis

Automatically capture form responses in Google Sheets
Use filters, formulas, and conditional formatting to analyze collected data
Prepare instant reports or dashboards based on live input

Apply Google Forms in Real-World Business Fields

1. Finance & Office Admin

Collect petty cash claims, invoice approvals, or budget requests
Project: Design a finance request form linked to a summary sheet for monthly expense tracking

2. Human Resources (HR)

Conduct employee feedback surveys, onboarding checklists, and leave applications
Project: Create a 360° feedback form with automated response analysis for appraisal support

3. Marketing & Customer Interaction

Collect leads, customer feedback, and event registrations
Project: Build a customer satisfaction survey with real-time Google Sheet reporting

4. Operations & Inventory

Track supply requests, equipment usage, or maintenance logs
Project: Develop a store request form integrated with stock update sheets

5. Sales & CRM

Capture inquiry forms, pre-sales assessments, or demo booking requests
Project: Create a sales lead generation form with Google Sheet tracking and status filtering

Share, Embed, and Collaborate with Ease

Share forms via links, email, or embed them in websites or intranets
Collaborate with team members to edit forms and access responses
Export responses for reporting or integrate with other tools like Google Data Studio

Data Management and Analysis Using Google Sheets

Organize and Manage Real-Time Data

Structure data using tables, freeze panes, and filters
Use data validation, drop-down lists, and protected ranges to prevent data errors
Collaborate live with teammates using version history and comment threads

Apply Advanced Formulas for Business Use

Perform calculations using IF, VLOOKUP, XLOOKUP, ARRAYFORMULA, TEXT, and DATE functions
Summarize large data sets with SUMIFS, COUNTIFS, and AVERAGEIFS
Automate recurring tasks using dynamic ranges and linked sheets

Visualize Data for Better Decision-Making

Create bar charts, line graphs, pie charts, and combo charts for visual reporting
Use sparkline visuals, progress bars, and conditional formatting to highlight key metrics
Share printable and real-time dashboards with stakeholders

Integrate Google Sheets with Other Tools

Connect with Google Forms to automatically collect and analyze data
Use IMPORTRANGE and QUERY functions to link multiple sheets
Export Sheets to Excel or PDF for external sharing and reporting

Apply Google Sheets Across Business Domains

1. Finance & Budgeting

Monitor budgets, expenditures, and profit margins
Project: Create a monthly expense tracker with category-wise filters and visual insights

2. HR & People Management

Track leave balances, onboarding checklists, and employee data
Project: Build a live HR dashboard linked to a Google Form-based leave application system

3. Marketing & Campaign Tracking

Monitor ad spend, lead conversions, and campaign KPIs
Project: Develop a campaign tracker that calculates ROI and engagement metrics in real-time

4. Operations & Workflow Tracking

Maintain inventory, procurement status, and delivery timelines
Project: Build a supply chain tracker with alerts for low stock and delays

5. Sales & CRM Support

Record leads, sales activity, and revenue targets
Project: Design a sales tracker with automatic performance calculations and target monitoring

Enhance Efficiency Through Automation & Collaboration

Use conditional formatting, formulas, and pivot tables to minimize manual work
Assign edit/view rights and collaborate seamlessly with remote teams
Store backups with version control and prevent data loss

Professional Dashboard Creation

Design Real-Time Dashboards for Business Monitoring

Create dashboards that update automatically using live data from:
- Excel files
- Google Sheets
- Power BI data sources
Display department-specific KPIs clearly for stakeholders

Build Function-Based Dashboards Across Fields

1. Finance Dashboard

Monitor budget utilization, revenue flow, and expense breakdowns
Project: Build a real-time finance tracker showing monthly income, cost centers, and variance alerts

2. HR Dashboard

Track attendance, leave balance, headcount, and attrition
Project: Design an HR dashboard linked with data entry sheets and leave trackers

3. Sales Dashboard

Monitor daily sales, targets, conversion rates, and team-wise performance
Project: Create a sales performance dashboard with filters for region, team, and product

4. Marketing Dashboard

Analyze campaign effectiveness, ROI, lead sources, and cost per lead
Project: Develop a marketing performance dashboard using real or simulated campaign data

5. Operations Dashboard

Visualize stock movement, delivery performance, vendor reliability, and task completion
Project: Build a dashboard to track procurement cycle, pending deliveries, and alerts

Combine Multiple Data Sources into One View

Merge sheets using QUERY, IMPORTRANGE, or Power BI relationships
Consolidate data from multiple branches, teams, or projects in a unified view
Schedule automatic updates to reduce manual reporting

Deliver Reports That Drive Action

Prepare dashboards for management review, team briefings, or client updates
Export dashboards as PDF reports, live shareable links, or printed summaries
Provide insights that support data-driven decisions

Python for Data Analytics

Understand Python for Practical Use

Set up Python and write your first scripts using tools like Jupyter Notebook or Google Colab
Use basic syntax for:
- Variables and data types
- Conditional logic (if, else)
- Loops (for, while)
Automate repetitive tasks like renaming files or filtering data

Work with Data Using Python Libraries

Use Pandas to:
- Import data from Excel, CSV, and Google Sheets
- Clean, sort, and filter large datasets quickly
- Perform group-wise operations (e.g., total sales by region)
Use NumPy for numerical operations on arrays and business metrics

Visualize Data with Python

Create charts using Matplotlib and Seaborn
Visualize trends, comparisons, and categories with:
- Line graphs
- Bar charts
- Histograms
- Heatmaps
Save graphs as images for presentations or reports

Apply Python Across Business Fields

1. Finance

Automate generation of expense reports and reconcile budgets
Project: Write a script to compare budget vs. actual and flag overspending

2. HR

Analyze employee data and generate leave or attendance summaries
Project: Filter and summarize employee leave by department using Pandas

3. Marketing

Clean campaign data and analyze performance metrics
Project: Visualize lead conversion rates and ad performance trends

4. Sales

Segment customers, track sales patterns, and forecast targets
Project: Build a sales report that summarizes weekly performance by product

5. Operations

Track inventory levels, vendor delays, or service metrics
Project: Create a dashboard-ready summary of stock usage and reorder alerts

Prepare Reports and Automate Workflows

Export processed data to Excel or PDF using Python scripts
Automate daily report generation and email delivery (intro to Python + SMTP)
Build a basic data pipeline from input to output for recurring office tasks

SQL for Data Retrieval and Analysis

Understand the Basics of SQL and Databases

Learn the structure and components of a relational database
Understand tables, columns, rows, primary keys, and foreign keys
Use SQL clients like MySQL Workbench, SQLite, or online SQL editors for practice

Retrieve and Filter Business Data Using SELECT Queries

Use SELECT, FROM, WHERE to extract specific data from tables
Apply filters using conditions like AND, OR, IN, BETWEEN, LIKE
Sort and limit results using ORDER BY and LIMIT

Summarize Data with Aggregations and Grouping

Use aggregate functions: SUM, COUNT, AVG, MIN, MAX
Group data using GROUP BY to generate departmental summaries
Filter groups with HAVING to extract specific insights

Join Multiple Tables for Cross-Functional Insights

Perform INNER JOIN, LEFT JOIN, and RIGHT JOIN to combine data from related tables
Merge employee, department, sales, and finance records for reporting
Understand the logic of data relationships in HR, sales, and operations

Apply SQL in Real-World Business Fields

1. Finance

Query expense logs, revenue tables, and cost centers
Project: Generate a monthly expense summary by department and payment type

2. HR

Analyze employee records, leave databases, and recruitment data
Project: Extract a report of employees with more than 3 absences in a month

3. Sales

Track sales performance by product, region, and customer
Project: Create a table showing top-selling products by region and revenue

4. Operations

Monitor stock movement, vendor transactions, and supply timelines
Project: Identify items with below-minimum stock and pending reorder status

5. Marketing

Analyze leads, campaign interactions, and customer feedback
Project: Query the lead database to find conversion rates by source and campaign

Use SQL to Build and Share Analytical Reports

Export query results to Excel or reporting tools
Create repeatable query templates for team reporting
Integrate SQL with BI tools like Power BI or Google Data Studio for real-time dashboards

Project

The project will be selected by the student based on their area of interest or relevant industry domain. It should reflect the practical application of the HR concepts, tools, and techniques learned during the course.

Pre-Placement Training

Build an Impressive Resume and LinkedIn Profile

Create a professional, job-focused resume tailored for HR and administrative roles
Highlight practical skills, project experience, certifications, and achievements
Develop a strong LinkedIn profile to enhance online visibility and attract recruiters

Prepare for Interviews with Confidence

Practice answering HR-specific and behavioural interview questions
Understand how to structure answers using the STAR method
Participate in mock interviews with personalised feedback

Develop Strong Communication and Presentation Skills

Speak clearly and professionally in interviews and meetings
Present your ideas with confidence during group discussions and HR briefings
Handle questions with clarity and maintain positive body language

Understand Workplace Expectations and Etiquette

Learn about corporate culture, professional behaviour, and dress code
Understand what employers expect during probation and performance evaluations
Maintain email and meeting etiquette in formal environments

Enhance Time Management and Professionalism

Plan and prioritize tasks during onboarding or internship
Set career goals and stay accountable for daily performance
Demonstrate dependability, initiative, and discipline at work

What Makes This Course Different from Other Courses in Kerala?

Accelerate your career with Skillspark’s online Data Analytics course. This industry-aligned digital program provides mastery over data visualization, statistical analysis, and database management, empowering you to solve complex business problems from anywhere in the world.

Data Analytics Course Benefits

In the modern business landscape, data is the new oil. Organizations across the globe are no longer relying on intuition alone; they are seeking professionals who can transform raw numbers into actionable insights. The online Data Analytics course at Skillspark The Finishing School is crafted to turn students into proficient data storytellers. This program bridges the gap between complex mathematical concepts and practical business applications, ensuring you can interpret trends and predict future outcomes with precision.

Throughout this curriculum, you will engage with the most in-depth tools and methodologies used by data professionals today. From cleaning messy datasets and performing exploratory data analysis to creating high-impact visual dashboards, the course covers the entire data lifecycle. We focus on a “hands-on” approach, where you move beyond theory to work on real-world datasets from industries like e-commerce, finance, and healthcare. By enrolling in this online Data Analytics course, you gain the technical prowess and analytical mindset required to help companies optimize their operations and maximize their ROI in a digital-first world.

Course Highlights

Why Choose Data Analytics?

Comprehensive Tool Stack: Intensive training in Microsoft Excel (Advanced), SQL, Power BI, and Tableau.
Project-Based Learning: Build a professional portfolio by working on live industry capstone projects.
Statistical Foundations: Master the core mathematics and logic behind data interpretation and forecasting.
Data Visualization: Learn to create interactive, executive-level dashboards that tell a compelling story.
Flexible Digital Learning: Access high-quality lectures and technical support through our virtual campus.

Certificates You'll Earn

Upon successful completion of this course, you will receive a recognised certificate from our accredited partners.

ASAP Kerala (Additional Skill Acquisition Programme) is a skill development initiative of the Higher Education Department, Government of Kerala, aimed at improving employability through industry-relevant training and certification. On successful completion of the course and assessment, learners receive a digitally verifiable certification, validating their skills and enhancing their career opportunities.

Who Should Enroll?

The online Data Analytics course is ideal for curious minds who enjoy problem-solving and have an affinity for patterns and logic.

Graduates in STEM or Commerce: Individuals looking to enter the high-paying tech and analytics industry.
Marketing & Finance Professionals: Those who want to use data to justify budgets and track performance metrics.
Business Analysts: Professionals looking to upgrade their technical toolkit with SQL and BI tools.
Aspiring Data Scientists: Anyone seeking a strong foundational start in the world of big data.

Career Opportunities

What’s Next?

Completing the online Data Analytics course opens doors to some of the most in-demand roles in the global job market.

Data Analyst: Interpreting data and turning it into information which can offer ways to improve a business.
Business Intelligence (BI) Developer: Designing and maintaining high-level data visualization solutions.
Operations Analyst: Using data to improve the internal workflows and efficiency of an organization.
Market Research Analyst: Studying market conditions to examine potential sales of a product or service.

Reporting Analyst: Specialized in creating and maintaining automated reports for stakeholders.

What our students say

Frequently Asked Questions on Data Analytics

Do I need a background in coding to join the online Data Analytics course?

Not necessarily. While we teach SQL, the course is designed to take you from the very basics. A logical mindset is more important than prior coding experience.

Which tools are covered in the online Data Analytics course?

Our curriculum focuses on the industry “Big Four”: Advanced Excel, SQL for databases, and both Power BI and Tableau for visualization.

Is the online Data Analytics course certificate valid internationally?

Yes, Skillspark The Finishing School provides a certificate that validates your practical skills, which is recognized by employers across various global markets.

Can I attend the online Data Analytics course while working a full-time job?

Yes, our online batches are designed with flexibility in mind, offering evening or weekend sessions to suit working professionals.

Will I work on real data during the online Data Analytics course?

Absolutely. You will work with sanitized real-world datasets to ensure you understand how to handle “dirty” data and extract meaningful insights.

What is the average duration of this online program?

The course typically takes 3 to 4 months to complete, depending on the depth of the projects and the batch schedule.

How does the online Data Analytics course help with placements?

We offer extensive placement support, including portfolio reviews, technical interview coaching, and connecting you with our network of hiring partners.

Is there a focus on Python or R in this course?

This specific program focuses on the core BI and SQL stack. However, we do introduce how these tools integrate into the broader data science ecosystem.

How do I get started with the online Data Analytics course?

You can book a free counseling session through our website to understand if this career path is right for you and then proceed with enrollment.