Join Data Analytics Course in Rajkot with Excel, SQL, Python, Power BI, Tableau, dashboards, real-time projects, internship & placement support.
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In Current time digital business world, data plays a major role in decision-making, customer analysis, sales forecasting, and business growth. Companies use data analytics tools to understand customer behavior, improve performance, track KPIs, and generate business insights for smarter decisions.
From dashboards and reporting systems to business intelligence and predictive analysis, Data Analytics has become one of the most in-demand skills in the IT and corporate industries. Organizations are actively hiring professionals who can analyze data, create reports, and develop interactive dashboards for business operations.
The Professional Program in Data Analytics & Business Intelligence at MDIDM Infoway is specially designed for BCA, MCA, B.Tech, BCom, MSc IT, Diploma students, freshers, job seekers, working professionals, and IT beginners who want to build successful careers in analytics and business reporting.
This industry-focused course helps students learn Microsoft Excel, SQL, Python, Power BI, Tableau, dashboard creation, business reporting, and data visualization with practical implementation and real-time projects.
Students receive:
The course focuses on practical learning where students work on real business datasets, KPI reports, dashboards, and analytics projects to gain industry-level experience.
Introduction to Data Analytics
Learn the fundamentals of Data Analytics and understand how businesses use data for decision-making and reporting. Students explore analytics life cycles, business applications, and the role of Data Analysts.
Microsoft Excel for Analytics
Master Excel formulas, functions, pivot tables, charts, dashboards, and MIS reporting techniques.
Students build sales dashboards and business reports using real-world datasets.
SQL & Database Management
Learn database concepts and SQL queries used for data extraction and reporting systems.
Students practice CRUD operations, JOINs, subqueries, and real-time database queries.
Python for Data Analytics
Understand Python basics, NumPy, Pandas, and data analysis techniques for business datasets.
Students perform data cleaning, visualization, and analytical operations using Python.
Data Cleaning & Preparation
Learn how to clean, organize, and transform raw business data into usable formats.
Students work with missing values, duplicate handling, outlier detection, and data formatting.
Exploratory Data Analysis (EDA)
Analyze datasets using charts, graphs, heatmaps, and trend analysis techniques.
Students generate business insights from customer analytics and sales datasets.
Statistics for Analytics
Understand statistical concepts used in business reporting and data analysis.
Students learn mean, median, variance, probability, and correlation techniques.
Power BI & Tableau
Learn interactive dashboard creation and KPI reporting using industry tools.
Students build business dashboards, HR analytics dashboards, and visual reports.
Business Analytics
Understand sales analytics, customer analytics, financial analytics, and reporting techniques.
Students learn how companies use analytics for business growth and strategic decisions.
Portfolio & Placement Preparation
Build professional portfolios, resumes, LinkedIn profiles, and presentation skills.
Students receive interview preparation and placement support for analytics careers.
Join the Professional Program in Data Analytics & Business Intelligence at MDIDM Infoway and gain industry-ready skills in Excel, SQL, Python, Power BI, Tableau, dashboards, and business reporting with practical training and placement support.
Contact MDIDM Infoway to start your journey with practical training, internship support, and industry-focused learning.
Students learn the basics of Data Analytics, business reporting, and decision-making systems.
Training starts with Excel dashboards, formulas, SQL queries, and database management.
Students learn Python libraries and perform data analysis using real-world datasets.
Students build Power BI and Tableau dashboards with KPI reporting systems.
Students work on analytics projects and business reporting implementations.
Resume building, interview preparation, and placement guidance help students become job-ready.
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Find clear and concise answers to common questions about our IT services, support, and solutions helping you make informed decisions faster.
Students, freshers, working professionals, and beginners can join this course. No advanced coding knowledge is required to start learning.
Yes, Excel is one of the most important tools for reporting and dashboard development. It is widely used in business analytics and MIS reporting.
Yes, students work on dashboards, analytics reports, and business datasets. Projects help students gain practical industry experience.
Students learn Excel, SQL, Python, Power BI, Tableau, and analytics visualization tools. These tools are widely used in the analytics industry.
Students can apply for Data Analyst, BI Analyst, MIS Executive, and Dashboard Developer roles. Analytics professionals are highly demanded across industries.
Yes, Excel is one of the most important tools for reporting and dashboard development. It is widely used in business analytics and MIS reporting.
Data Analytics is the process of analyzing raw data to find useful insights and support business decision-making.
Data Analytics focuses on analyzing historical data and generating reports. Data Science includes advanced technologies like Machine Learning, prediction systems, and AI mod
SQL is a database language used to store, manage, and retrieve data from databases. Data Analysts use SQL for filtering, reporting, joins, and data analysis tasks.
Data Visualization means representing data using charts, dashboards, graphs, and reports. It helps businesses understand trends, patterns, and performance easily.
Power BI is a business intelligence tool used to create interactive dashboards and reports. It helps companies monitor KPIs, business growth, and data insights in real time.
Data Cleaning is the process of removing missing values, duplicate records, and incorrect data from datasets. It improves data accuracy and helps generate better business insights.