Data Analytics Blogs, Tools, Projects and Career Tips

Explore Data Analytics concepts, tools, projects, skills and career resources in one place. Learn about Excel, SQL, Python, Power BI, Tableau, statistics and AI; explore practical Data Analytics applications and projects, understand relevant career skills and roles, and find learning options for building your Data Analytics knowledge.
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Data Analytics covers a wide range of skills, from working with Excel, SQL and Python to analysing data, creating dashboards and using AI-powered tools. For beginners and professionals, knowing where to start can be difficult when concepts, tools, project ideas and career information are spread across different resources. Understanding how these areas connect is important for building practical Data Analytics knowledge.

Explore Data Analytics concepts, tools, projects, skills and career opportunities, with resources covering statistics, Excel, SQL, Python, Power BI, Tableau and AI. Find practical project ideas, learn about commonly used technologies and understand the skills associated with Data Analytics roles. Information about the Data Analytics with AI programme in collaboration with Microsoft is also included for those looking for a dedicated learning option.

Data Analytics Concepts and Learning Resources

Data Analytics involves working with data across multiple stages, including statistical analysis, programming, data handling, visualisation and business reporting. Explore key areas and topics to build knowledge across the Data Analytics workflow.

Learning Area

Topics Covered

Data Analytics Fundamentals

Core concepts, methods and analytical approaches

Statistics

Statistical concepts, interpretation and analysis

Excel

Data analysis, formulas and spreadsheet-based reporting

SQL

Queries, databases, joins and data retrieval

Python

Programming, data processing and analysis

Data Visualisation

Charts, dashboards and data storytelling

Business Intelligence

Reporting, dashboards and business-focused analysis

AI in Data Analytics

AI-assisted analysis and emerging applications

Tools and Technologies Covered in PW Skills Data Analytics with AI 

The PW Skills Data Analytics with AI programme covers commonly used tools for data analysis, visualisation, business intelligence and AI-assisted workflows.

Tool or Technology

Application

Excel with Copilot

Spreadsheet analysis and AI-assisted workflows

SQL

Database querying and data retrieval

Python

Data processing and analysis

Power BI with AI Features

Business intelligence and interactive dashboards

Tableau Pulse

Data visualisation and insights

ChatGPT

AI-assisted analytics and productivity

Microsoft Copilot

AI-assisted data and productivity workflows

Gemini

Generative AI applications

ETL

Extracting, transforming and preparing data

What Data Analytics Projects Are Included in the PW Skills Programme?

The PW Skills Data Analytics with AI programme includes 20+ projects covering different applications of data analysis, reporting, visualisation and AI. Selected projects include:

Project

Application Area

Unilever Sales Data Analysis

Sales Analytics

Employee Performance Analysis

Employee Analytics

Healthcare Analytics

Healthcare Data Analysis

ETL Pipeline and Reporting

ETL and Reporting

Regional Insights Dashboard

Dashboard Development

Smart City Insights Dashboard

Data Visualisation

Business Intelligence Data Visualisation

Business Intelligence

FashionPulse: E-Commerce Web Scraping and Data Analysis

E-Commerce Analytics

Future of AI in Analytics

AI in Data Analytics

Student Performance and Learning Style Analysis

Education Analytics

These projects cover practical applications across sales, healthcare, e-commerce, business intelligence, education and AI, giving learners opportunities to apply Data Analytics concepts and tools to different use cases.

PW Data Analytics with AI: Course Offerings and Curriculum

PW Skills offers Data Analytics with AI in collaboration with Microsoft for learners who want to build foundational Data Analytics skills. The beginner-level programme covers essential analytics concepts, industry-relevant tools, AI applications and practical projects.

Programme Feature

Details

Duration

5 months

Level

Beginner

Technical Learning

120+ hours

Soft Skills & Aptitude

40+ hours

Projects

20+

Basic Mode

Self-paced

Premium Mode

Live sessions over weekends

Pro Mode

Live sessions over weekends

The curriculum includes Excel, SQL, Statistics, Python, ETL, Power BI, Tableau and AI-powered features. Along with technical concepts, the programme includes practical projects, soft skills and aptitude learning to support broader professional development.

The programme is intended for final-year college learners, fresh graduates, early professionals and career switchers who want to develop skills in Data Analytics and related tools.

What Are the PW Data Analytics with AI Plans, Certification and Eligibility?

The PW Data Analytics with AI programme is available in three plans with different learning modes, fees and certification options. The eligibility criteria and certification requirements vary based on the programme format and applicable assessments.

Plan

Fee

Learning Mode

Certification

Basic

Rs. 6,999

Self-paced

PW Skills

Premium

Rs. 29,999

Weekend live sessions

PW Skills + Microsoft + NSDC

Pro

Rs. 34,999

Weekend live sessions

PW Skills + Microsoft + NSDC

EMI options are available for the Premium and Pro plans.

What Are the Certification Requirements?

To meet the programme requirements for certification, learners need to fulfil the specified academic and assessment criteria, including:

  • At least 70% attendance in live sessions

  • At least 60% quiz performance

  • At least 60% assignment performance

  • Completion of the specified requirements for applicable dashboard and project components

The programme also includes practical applications such as the Regional Insights Dashboard and other project-based work as part of the learning and assessment process.

Who Can Explore the PW Data Analytics with AI Programme?

The programme is designed for learners and professionals from different academic and career backgrounds, including:

  • Final-year learners: B.Tech, BCA and B.Sc learners from Mathematics, Statistics, Computer Science and IT backgrounds

  • Fresh graduates: B.Com, BBA, B.Sc, B.Tech and MCA graduates

  • Early professionals: Professionals working in operations, MIS, marketing, finance and support functions

  • Career switchers: Professionals from sales, HR, banking, consulting and related areas

The programme brings together technical learning, practical projects and AI applications for learners looking to build or strengthen their Data Analytics skills.

Preparing for a career in Data Analytics can begin with choosing a programme that matches your learning needs, background and preferred mode of study. The PW Data Analytics with AI programme offers three plans, practical projects and certification options, allowing learners to select an option based on their learning format and programme requirements.

FAQ

What skills are required for Data Analytics?

Which tools are commonly used in Data Analytics?

Is Python necessary for learning Data Analytics?

Python is not always required at the beginning, but learning Python can help with data cleaning, analysis, automation and working with larger datasets.

What is the difference between Data Analytics and Data Science?

Data Analytics generally focuses on examining existing data to identify patterns, trends and insights, while Data Science also involves areas such as predictive modelling, machine learning and advanced statistical methods.

Can beginners learn Data Analytics?

Yes. Beginners can start with fundamentals such as Excel, basic statistics and SQL before progressing to Python, data visualisation and more advanced analytics concepts.

What projects can be done while learning Data Analytics?

Projects can include sales dashboards, customer analysis, financial reports, marketing analytics, regional performance dashboards and other applications based on real-world datasets.
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