– Understanding the concept of business analytics

– Significance and relevance of business analytics in decision-making

– Diverse categories of analytics: Descriptive, Predictive, and Prescriptive

– The role of data visualization in business analytics

– Understand data warehousing, data lakes, and data marts. 

– Understanding business matrices & KPIs

– Business Analytics with ChatGPT & Prompt Engineering

– Fundamentals of business data representation using Microsoft Excel

– Learn to collect, manage, and store company data effectively

– Data preparation and cleaning techniques

– Formulas, functions, and their application in data analysis

– Exploring the power of Pivot Tables for data summarization

– Leveraging advanced Excel features for effective analytics

– Creating dynamic dashboard with Pivot Charts

– Understanding the role of Power BI in data visualization

– Exploring Power BI’s user interface and functionalities

– Identifying Key Performance Indicators (KPIs) for business insights

– Utilizing DAX functions for complex calculations and modeling

– Advanced techniques for data transformation using Power Query

– Creating interactive dashboards and reports with Power BI

– Integrating geographical data through mapping techniques

– Forecast future trends and patterns using Power BI

– Crafting interactive dashboards and reports

– Database Management System OverView

– Database Structure and SQL Select statements

– Filtering Data in SQL Joins and subqueries in SQL

– Data definition language (DDL)

– Sorting data & Functions in SQL

– Connecting database to Power BI

– Understanding Data warehousing

– KNIME for data preprocessing, transformation and modelling 

– Building predictive analytics workflows using machine learning algorithms in KNIME

– Building machine learning models (e.g., regression, decision trees, SVMs)

– Feature engineering and selection techniques for predictive modelling 

– Model evaluation and validation using KNIME analytics platform