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Business Analytics - Syllabus, Fees & Duration

Business Analytics Course Syllabus (60 Hours)

Mode: Live Online / Offline
Level: Beginner to Intermediate
Certification: Yes
Placement Assistance: Included


Module 1: Introduction to Business Analytics (3 Hours)
  • What is Business Analytics?

  • Importance of data-driven decision making

  • Types of analytics: Descriptive, Predictive, Prescriptive

  • Analytics in different business functions (HR, Marketing, Finance)


Module 2: Statistics and Data Interpretation (6 Hours)
  • Basic statistics: mean, median, mode, range, standard deviation

  • Probability concepts

  • Data distribution and sampling

  • Hypothesis testing

  • Use of Excel/SPSS for basic statistics


Module 3: Excel for Business Analytics (6 Hours)
  • Advanced Excel functions: VLOOKUP, HLOOKUP, INDEX-MATCH

  • PivotTables, PivotCharts

  • Conditional formatting, What-If analysis

  • Excel Dashboards for data visualization


Module 4: SQL for Data Extraction (6 Hours)
  • Introduction to relational databases

  • Writing queries: SELECT, WHERE, GROUP BY, JOIN

  • Aggregation and filtering data

  • Real-time data extraction exercises


Module 5: Data Visualization (6 Hours)
  • Importance of visualization in analytics

  • Introduction to Tableau / Power BI

  • Charts, filters, dashboards

  • Visual storytelling with data


Module 6: Predictive Analytics & Forecasting (9 Hours)
  • Linear regression

  • Logistic regression

  • Time series forecasting

  • Model evaluation techniques (R², RMSE)

  • Use of tools: Excel, Python (optional introduction)


Module 7: Business Intelligence Concepts (5 Hours)
  • ETL process overview

  • BI systems in enterprises

  • KPIs & performance metrics

  • Case studies from domains: retail, finance, healthcare


Module 8: Real-Time Projects & Capstone (10 Hours)
  • Project planning & requirement gathering

  • Work on real datasets

  • Build a dashboard/report

  • Present findings to a panel

  • Individual or group project submission


Module 9: Career Preparation & Certification (3 Hours)
  • Resume building with analytics skills

  • Mock interview & Q&A

  • Job roles in business analytics

  • Final test & certification issue


Tools Covered

  • Microsoft Excel (Advanced)

  • SQL (MySQL/PostgreSQL)

  • Tableau / Power BI

  • Optional: Basics of Python for analytics

Download Syllabus - Business Analytics
This syllabus is not final and can be customized as per needs/updates
   
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Business Analytics Jobs in Kottayam

Enjoy the demand

Find jobs related to Business Analytics in search engines (Google, Bing, Yahoo) and recruitment websites (monsterindia, placementindia, naukri, jobsNEAR.in, indeed.co.in, shine.com etc.) based in Kottayam, chennai and europe countries. You can find many jobs for freshers related to the job positions in Kottayam.

  • Business Analyst
  • Data Analyst
  • Business Intelligence Analyst
  • Market Research Analyst
  • Financial Analyst
  • Operations Analyst
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Business Analytics Internship/Course Details

Business Analytics internship jobs in Kottayam
Business Analytics Delivered through live interactive sessions by industry experts, it includes a capstone project, certification, and placement assistance for eligible candidates. Nestsoft’s Business Analytics Course is designed to equip learners with the analytical tools and decision-making skills needed in today’s data-driven business environment. Start your journey to becoming a data-savvy decision-maker and gain a competitive edge in the business world. Whether you’re a student, professional, or entrepreneur, this course is ideal for anyone looking to enhance their analytical thinking and career prospects. The course covers essential topics like descriptive and inferential statistics, data visualization, business intelligence, and the basics of predictive analytics. This 60-hour program combines theory with hands-on training in Excel, SQL, Tableau/Power BI, and real-world business scenarios to help you turn data into actionable insights. Students will learn to interpret data, apply statistical techniques, build dashboards, and use predictive models for informed decision-making.

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