Business Analytics
Business Analytics Professional
Description
The process of gathering, analyzing, and processing data in order to make wise business decisions is known as business analytics. To analyze data and find trends or insights, it combines data mining, statistical analysis, and predictive modeling. Assisting businesses in making data-driven decisions that can boost productivity, boost profits, and lower risks is the aim.
Important Business Analytics Elements:
1. Descriptive analytics: Offers information about historical events that have occurred within the company. To identify trends and patterns, it involves reporting, summarizing, and aggregating data.
2. Diagnostic analytics: This approach aims to determine the cause of an event. It entails more in-depth data analysis, frequently with correlations, data discovery, and drill-down methods.
3. Predictive analytics: Based on past data, this approach forecasts future events using statistical models and machine learning methods. This aids companies in projecting future trends, consumer behavior, and possible hazards.
4. Prescriptive analytics: Makes suggestions for how to achieve desired results. To recommend the optimum course of action, optimization techniques and simulation are frequently used.
5. Data visualization: The process of displaying data in a graphical manner to facilitate fast understanding of insights by stakeholders. Dashboards, charts, and graphs are examples of frequently used tools.
What You will Learn?
- Descriptive Analytics
- Diagnostic Analytics
- Predictive Analytics
- Prescriptive Analytics
- Data Visualization
Topics for this course
Total learning: 160 Topics
Module 1: Advanced Formulas and Functions
• Array Formulas: Introduction and practical applications
• Logical Functions: Advanced use of IF, AND, OR, NOT
• Lookup Functions: Mastering VLOOKUP, HLOOKUP, XLOOKUP, MATCH, INDEX, and
• Text Functions:
• Date and Time Functions:
• Statistical Functions: Using AVERAGEIF, AVERAGEIFS, SUMIF, SUMIFS, COUNTIF, COUNTIFS
• Array Functions: FILTER, UNIQUE, SORT, SORTBY, SEQUENCE
Module 2: Data Analysis and Visualization
• PivotTables: Creating, customizing, and advanced techniques (calculated fields, grouping, slicers)
• Pivot Charts: Dynamic charting with PivotTables
• Advanced Charting
• Conditional Formatting: Custom rules, formulas in conditional formatting, data bars, icon sets, and color scales
• Data Validation: Advanced data validation rules, creating dropdown lists with dynamic ranges, custom validation messages
Module 3: Data Import, Cleaning, and Transformation
• Data Import Techniques: Importing data from text files, CSV, databases, web queries, and other sources
• Power Query: Introduction, data transformation, merging and appending queries, cleaning data with Power Query
• Text to Columns: Splitting and combining data
• Remove Duplicates: Identifying and removing duplicate data
• Flash Fill: Automatically filling data based on examples
• Working with Tables: Creating, formatting, and using structured references
Module 4: Advanced Data Analysis with Power Pivot
• Introduction to Power Pivot: Enabling the add-in, importing data, and creating data models
• Relationships: Creating and managing relationships between tables
• DAX (Data Analysis Expressions): Introduction to DAX, calculated columns, and measures (Using Power BI also)
• Creating Complex Reports
Module 5: Advanced Excel Techniques
• What-If Analysis: Using Scenario Manager, Goal Seek, and Data Tables
Dynamic Named Ranges: Creating and using dynamic ranges in formulas and charts
Module 6: Excel Integration with Other Tools
• Integrating Excel with Power BI: Importing Excel data into Power BI, using Excel as a data source
Module 1: Introduction to SQL Server
• Overview of SQL Server: Editions and components
• SQL Server architecture: Database engine, SQL Server instances, and services
• Installing and configuring SQL Server
• SQL Server Management Studio (SSMS): Interface, tools, and utilities
• Understanding databases, tables, schemas, and objects
• Overview of T-SQL (Transact-SQL)
Module 2: Database Design and Implementation
• Introduction to database design: Normalization, primary keys, foreign keys
• Creating and managing databases
• Creating and altering tables: Data types, constraints, indexes
• Relationships and referential integrity
• Designing views and stored procedures
• Implementing triggers and user-defined functions (UDFs)
Module 3: Querying and Manipulating Data with T-SQL
• Writing basic T-SQL queries: SELECT, WHERE, ORDER BY, GROUP BY
• Joins and subqueries: INNER JOIN, LEFT JOIN, RIGHT JOIN, CROSS JOIN, and correlated subqueries
• Aggregate functions: SUM, COUNT, AVG, MIN, MAX
• Set operators: UNION, INTERSECT, EXCEPT
• Working with NULLs and complex expressions
• Modifying data: INSERT, UPDATE, DELETE, and MERGE
Module 4: Indexing and Query Performance Tuning
Module 7: SQL Server Backup and Recovery
Module 1: Introduction to Power BI
• Overview of Power BI: Components and workflow
Power BI Desktop vs. Power BI Service vs. Power BI Mobile
• Installation and setup of Power BI Desktop
• Overview of Power BI architecture
• Key concepts: Dashboards, Reports, and Datasets
Module 2: Getting Started with Power BI Desktop
• Power BI interface and navigation
• Connecting to data sources: Excel, CSV, databases, web data, and cloud services
• Data import and data refresh in Power BI
• Understanding data types and Power Query Editor
• Overview of relationships and the data model
Module 3: Data Transformation and Preparation
• Data cleaning and transformation with Power Query
• Handling missing data, filtering, and sorting
• Merging and appending queries
• Unpivoting and pivoting columns
• Creating custom columns and using advanced transformation techniques
• Understanding applied steps and query dependencies
Module 4: Data Modeling in Power BI
• Introduction to data modeling concepts
• Creating relationships between tables
• Understanding cardinality and cross-filter direction
• Using calculated columns and calculated tables
• Hierarchies and their use in data models
• Introduction to DAX (Data Analysis Expressions): Basic syntax and functions
Module 5: Advanced DAX in Power BI
• Deep dive into DAX functions: Logical, mathematical, statistical, and text functions
• Time intelligence functions: YEAR, MONTH, QUARTER, YTD, MTD, etc.
• Advanced DAX functions: CALCULATE, ALL, FILTER, RELATED, RELATEDTABLE
• Creating and using measures for dynamic reporting
Performance optimization with DAX: Best practices
Module 6: Data Visualization and Reporting
• Introduction to Power BI visuals: Tables, matrices, charts, and maps
• Customizing visualizations: Formatting, sorting, and filtering visuals
• Creating and using slicers and filters
• Drill-down and drill-through reports
• Using bookmarks, buttons, and selection panes for navigation
• Creating interactive dashboards and storytelling with Power BI
Module 7: Advanced Visualization Techniques
• Custom visuals: Importing and using third-party visuals
• Conditional formatting in visuals
• Using KPIs and gauges for performance tracking
• Advanced charting techniques: Waterfall, funnel, scatter, and bullet charts
Module 8: Power BI Service
• Introduction to Power BI Service (PowerBI.com)
• Publishing reports from Power BI Desktop to Power BI Service
• Creating and managing workspaces
• Sharing reports and dashboards with stakeholders
• Introduction to Power BI Apps and App Workspaces
Module 1: Introduction to Tableau
• Overview of Tableau: Desktop, Server, Online, and Public
• Installing and setting up Tableau Desktop
• Understanding Tableau’s interface: Workspace, menus, and toolbars
• Connecting to data sources: Excel, CSV, SQL databases, cloud data
• Introduction to Tableau data types and structures
• Basic concepts: Dimensions, measures, and data types
Module 2: Data Connection and Preparation
Connecting to different data sources: Relational databases, web data, cloud services
• Live connections vs. data extracts
• Understanding data blending and joins in Tableau
• Using Tableau’s Data Interpreter to clean and prepare data
• Managing metadata: Renaming fields, assigning aliases, and modifying data types
• Creating calculated fields, hierarchies, and groups
Module 3: Working with Data in Tableau
• Introduction to Tableau’s data model: Relationships and joins
• Filtering data: Filters on dimensions, measures, dates, and table calculations
• Sorting data: Alphabetical, manual, and by field
• Working with hierarchies: Drill-downs and roll-ups
• Using sets and groups for advanced data segmentation
• Introduction to Tableau’s built-in functions: String, number, date, logical, and aggregate functions
Module 4: Data Visualization Basics
• Creating basic charts: Bar charts, line charts, and pie charts
• Working with text tables and heat maps
• Understanding and using Tableau’s Show Me panel
• Dual-axis and combination charts
• Using colors, labels, and tooltips for enhanced visualization
• Customizing visualizations: Formatting options, reference lines, and annotations
Module 5: Advanced Visualizations
• Creating and working with maps: Geographic data and custom geocoding
Creating and customizing scatter plots and bubble charts
• Building tree maps, box plots, and Gantt charts
• Using advanced chart types: Waterfall charts, Pareto charts, bullet graphs
• Visual analytics: Trend lines, forecasting, and reference bands
• Using parameters for interactive visualizations and dynamic filtering
Module 6: Dashboard Design and Best Practices
• Introduction to dashboards: Layout, sizing, and best practices
• Creating interactive dashboards with multiple worksheets
• Adding interactivity: Actions, filters, and highlights
• Designing for different devices: Desktop, tablet, and mobile layouts
• Using dashboard objects: Text, images, web objects, and containers
• Best practices for dashboard performance and user experience
Module 7: Tableau Calculations and Advanced Analytics
Module 9: Tableau Server and Online
• Introduction to Tableau Server and Tableau Online
• Publishing and sharing workbooks to Tableau Server or Online
• Managing user permissions and security
• Creating and managing data sources on Tableau Server
Module 10: Performance Optimization in Tableau
Module 11: Tableau Integration and Extensions
• Integrating Tableau with other BI tools and platforms
After completion of Training.
Assignments - 4
Real Time Projects - 3
Certifications – Microsoft & IBM, NSDC
Fully job supports
Opportunities after this course completion
Price: INR 35000
This Course Includes
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Skill level : Advanced
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Duration : 6 Months
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Chapters : 5
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Topics : 160
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Language : English
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Certificate : Yes
