Who should take the Data Analytics Certification Training?

This program is suitable for students, graduates, working professionals, business professionals, and beginners who want to develop skills in data analysis, reporting, and visualization. It can also help professionals who want to transition into data analytics or improve their ability to work with business data.

What topics are covered in the Data Analytics Certification Training?

Topics may include Data Analytics Fundamentals, Microsoft Excel for Data Analysis, SQL and Database Queries, Python for Data Analytics, Data Cleaning and Data Preparation, Statistics and Exploratory Data Analysis, Data Visualization and Reporting, Power BI and Tableau, and Real-World Projects and Business Case Studies.

Are there any prerequisites for the Data Analytics Certification Training?

No advanced technical background is necessary to begin learning the fundamentals. Basic computer skills and an interest in working with data are helpful. Familiarity with mathematics or spreadsheets can be beneficial, but the required prerequisites depend on the selected course level.

What is the course duration and format?

The course duration and delivery format depend on the selected training program. Online learning may include instructor-led sessions, recorded lessons, practical exercises, assignments, and project-based learning. Contact Securium Academy for the confirmed schedule and duration.

How is the certification assessment structured?

Assessment requirements depend on the certification provider. Depending on the program, assessment may include multiple-choice questions, practical assignments, data analysis exercises, dashboard projects, or case studies. Confirm the applicable exam format before enrollment.

What tools and technologies are included in the training?

The curriculum may include Microsoft Excel, SQL and relational databases, Python, Pandas and NumPy, Matplotlib and Seaborn, Microsoft Power BI, Tableau, and Jupyter Notebook. The final list depends on the selected training package.

What is the course fee in India?

The Data Analytics Certification Training fee depends on the selected course, training format, learning resources, and certification inclusions. Contact Securium Academy for the latest course fee and available payment options.

What career opportunities does this program offer?

Learners may pursue opportunities such as Data Analyst, Junior Data Analyst, Business Intelligence Analyst, Reporting Analyst, Business Analyst, Power BI Developer, and Data Visualization Analyst. Job eligibility and salary depend on experience, technical skills, location, and employer requirements.

Which platform is recommended for online Data Analytics training?

Securium Academy provides training resources and expert guidance for learners interested in developing professional skills. The most suitable learning format depends on your background, schedule, and career goals. Contact the academy to confirm the available Data Analytics program, delivery format, and learning support.

Will the training include practical projects?

The proposed curriculum includes practical exercises and project ideas involving sales analysis, customer behavior, business performance, and dashboard development. Confirm the final project list and practical training inclusions with Securium Academy before publishing.

Will I receive a certificate after completing the course?

Certificate eligibility depends on the selected program and its completion requirements. Confirm whether the course includes a certificate of completion, an external certification assessment, or both.

Can beginners learn Data Analytics?

Yes. Beginners can start with Excel, basic statistics, and data interpretation before progressing to SQL, Python, and dashboard development. Regular practice with datasets and practical projects helps learners build confidence and develop job-relevant skills.

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Data Analytics Certification Training

Data Analytics is an essential part of modern business decision-making. Organizations use data to understand customer behavior, monitor performance, improve operations, identify market trends, and make strategic decisions.

This program helps learners develop practical expertise in data preparation, statistical analysis, SQL, Python, data visualization, and business intelligence.

Learn how to transform raw data into useful information, create clear reports, and present findings that help businesses make informed decisions.

Businesses across industries rely on data to measure results, understand market trends, and improve operational efficiency. This program helps you build the technical and analytical skills needed to work with data and explore opportunities in analytics and business intelligence.

Work with practical datasets and business case studies involving sales performance, customer behavior, financial reporting, operational metrics, and market analysis. Apply your knowledge to data cleaning, exploratory analysis, dashboard creation, and insight generation.

Build skills relevant to roles such as Data Analyst, Business Intelligence Analyst, Reporting Analyst, Junior Business Analyst, and Power BI Developer, depending on your experience and technical proficiency.

Who Should Attend?

Students and graduates interested in data analytics
Working professionals looking to upskill
IT professionals transitioning into analytics roles
Business and finance professionals seeking analytical skills
Professionals working with reports, spreadsheets, and business data
Beginners interested in learning data analytics from the fundamentals

Course Objectives

Understand data analytics concepts, data types, descriptive statistics, data collection, data cleaning, and exploratory data analysis.

Learn to use Excel, SQL, and Python libraries such as Pandas and NumPy to organize, process, query, and analyze datasets.

Create charts, reports, and interactive dashboards using Power BI, Tableau, and relevant visualization tools to communicate analytical findings.

Work with real-world datasets to analyze sales, customer behavior, financial performance, and operational trends. Prepare reports and present actionable business insights.

Course Syllabus

Understanding data analytics concepts, data types, and data sources
Introduction to descriptive statistics and analytical thinking
Data collection, organization, and interpretation
Understanding business requirements and analytical questions
Identifying trends, patterns, and key performance indicators (KPIs)

Data cleaning, formatting, sorting, and filtering
Formulas and functions for data analysis
PivotTables and PivotCharts
Lookup functions and conditional formatting
Creating reports and analyzing business performance

Understanding relational databases and tables
Writing SQL queries to retrieve and filter data
Using WHERE, GROUP BY, ORDER BY, and JOIN operations
Aggregate functions and subqueries
Analyzing structured datasets using SQL

Python fundamentals for data analysis
Working with NumPy and Pandas
Data cleaning, transformation, and manipulation
Exploratory data analysis
Creating visualizations using Matplotlib and Seaborn

Connecting and importing data from different sources
Data transformation and preparation
Creating interactive dashboards and reports
Building charts, graphs, and KPI visualizations
Developing business intelligence reports
Presenting analytical findings through visual storytelling

Sales and revenue performance analysis
Customer behavior and segmentation analysis
Financial and business performance reporting
E-commerce data analysis
Dashboard development using Power BI or Tableau
Portfolio projects, resume preparation, and interview practice

Lokesh Dandamudi

★★★★★

The Data Analytics course introduces key concepts in a clear, structured way. Learning about data preparation, analysis, and visualization helped me understand how raw data can be turned into useful business insights.

Lajin C P

The SQL and Excel topics provide a practical starting point for exploring datasets. The examples helped me understand how to organize information, identify patterns, and answer business questions with data.

Malle Ganesh

I found the Python analytics topics useful for learning data cleaning and exploratory analysis. Practicing with tools such as Pandas and NumPy helped make the concepts more approachable.

Alka Sajeevan P

The visualization lessons explain how to present findings clearly. Building charts and dashboards helped me see how data storytelling can support better business decisions.

Sreelakshmi Suresh

The project topics bring together analysis, reporting, and dashboard development. They provide a useful outline for building a portfolio and practicing skills used in data analytics roles.

Data Analytics Master Program — Excel • SQL • Python • Power BI • Tableau

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Program Highlights

Why Choose Data Analytics Certification Training?

Master Data Analysis, Visualization and Business Intelligence

Data Analytics Certification Training

What You Will Learn

1️⃣ Data Analytics Foundations

Excel for Data Analysis

SQL and Database Analysis

Python for Data Analytics

Power BI and Tableau

Hands-on Projects and Career Preparation

Core Traits You’ll Build

Your Analyst Style

Data Analytics Certification

Become a Certified Data Analytics Professional

Tools & Technologies Covered

Microsoft Excel

SQL & Databases

Python

Power BI

Tableau

Pandas

NumPy