Professional Certificate course in Business Intelligence and Digital Marketing

130,000.00 +GST

Category:

Course Details :

  • Course Type: Online Live Delivery with self paced courses
  • Duration: 72 hours (3.5 Months for weekdays & 6 months for weekend)
  • Total Lectures: 36 Lectures
  • Skill Level: Intermediate
  • Assessments: Daily Assessments
  • Certificate: Yes

Outcome Expected :

  • Business Analysis Skills:
    Outcome: Develop a strong foundation in business analysis, including requirements gathering, process modeling, and stakeholder communication.
  • Data Analysis and Interpretation:
    Outcome: Acquire skills in analyzing data to extract meaningful insights, make informed business decisions, and identify trends and patterns.
  • Digital Marketing Fundamentals:
    Outcome: Gain a comprehensive understanding of digital marketing concepts, including SEO, social media marketing, email marketing, and content marketing.
  • Customer Relationship Management (CRM):
    Outcome: Learn how to implement and leverage CRM systems to manage customer relationships, improve customer satisfaction, and drive business growth.
  • Digital Marketing Tools and Platforms:
    Outcome: Gain hands-on experience with digital marketing tools and platforms, such as Google Analytics, AdWords, social media management tools, and marketing automation platforms.
  • Data Visualization:
    Outcome: Ability to create meaningful visualizations using tools like Tableau, Power BI, or other visualization tools to communicate insights effectively.
  • Analytics and Reporting:
    Outcome: Learn to use analytics and reporting tools to track key performance indicators (KPIs) and assess the success of digital marketing initiatives.
  • Career Readiness:
    Outcome: Prepare for a career in business analysis and digital marketing with a well-rounded skill set, combining analytical thinking, business acumen, and digital marketing expertise.

Requirements :

  • Daily Assessments
  • Mini projects (module wise)
  • Live Evaluation
  • Online classes on Zoom

Target Audience :

  • Undergraduate and postgraduate students in any domain/field

Key Features :

  • Requires no programming or technical skills. Students with no technical background can join
  • Cover various data science topics in detail such as Excel, Databases, Data Wrangling, Statistics, Search Engine Optimization, Predictive Analytics, and many more
  • Placement Support is provided for all the students who pass the eligibility criteria
  • Industry support for every student

Curriculum

Module 1: Introduction to Analytics

This curriculum provides a comprehensive introduction to business analytics, covering foundational concepts, models, roles, and the distinction between business analytics and business intelligence.

  • Introduction to Business Analytics
  • Models in Business Analytics
  • Roles and Responsibilities in Business Analytics
  • Understanding Business Intelligence (BI)
  • Business Analytics vs. Business Intelligence

Module 2: Statistics Fundamentals

This module covers key statistical concepts such as descriptive statistics, probability, inference, hypothesis testing, estimation techniques, and identifying relationships between datasets.

  • Descriptive Statistics: Central Tendency (Mean, Median, Mode) and Dispersion (Variance, Standard Deviation)
  • Probability Concepts
  • Statistical Inference
  • Hypothesis Testing
  • Estimation Techniques: Point Estimation and Interval Estimation
  • Finding Statistical Relationships Between Sets of Data

Module 3: Data Wrangling with Excel

This module introduces fundamental Excel functionalities, including data searching and filtering, formula usage, data merging, pivot chart creation, and text function-based data cleaning.

  • Basic Excel Functionalities
  • Searching and Filtering Data
  • Excel Formulas
  • Merging Data in Excel
  • Pivot Charts in Excel
  • Cleaning Data with Text Functions

Module 4: Advanced Excel & Integrating ChatGPT with Excel

This module covers advanced Excel functions. It also explores creating waterfall charts, using ChatGPT for insights, automating tasks using ChatGPT.

  • Advanced Excel Functions and Features
  • VLOOKUP, HLOOKUP, INDEX-MATCH
  • Logical Functions (IF, AND, OR)
  • Statistical Functions (AVERAGEIFS, COUNTIFS, SUMIFS)
  • Text Manipulation Functions (CONCATENATE, TEXTJOIN)
  • Waterfall Charts in Excel
  • Using ChatGPT to Generate Insights and Summaries from Excel Data
  • Automating Repetitive Tasks in Excel using ChatGPT

Module 5: Data Visualization with Excel

This module will help you gain the skills and knowledge to leverage Excel’s data visualization capabilities to communicate insights and trends in data effectively.

  • Reading Complex JSON Files
  • Styling Tabulation
  • Distribution of Data: Histogram, Box Plot
  • Pie Chart, Donut Chart
  • Stacked Bar Plot, Relative Stacked Bar Plot
  • Stacked Area Plot, Scatter Plots
  • Bar Plot, Continuous vs. Continuous Plot
  • Line Plot

Module 6: Basics of SQL

This module covers fundamental concepts and techniques necessary for querying and manipulating data in a database management system (DBMS). 

  • Database Introduction and Installation
  • Data Modeling and Normalization
  • ACID Transactions and Data Types
  • Data Definition Language (DDL) and Data Manipulation Language (DML)
  • Data Control Language (DCL) and Transaction Control Language (TCL)
  • SQL Constraints and Operators
  • Clauses in SQL (Where, Having, Group By, Order By)

Module 7: Advanced SQL

This module covers SQL essentials like joins, functions (mathematical, conversion, general, date/time, numeric/string), conditional expressions, subqueries, and rank/window functions.

  • Joins (Inner, Left, Right, Full, Equi, Non-Equi, Self)
  • Mathematical Functions
  • Conversion Functions
  • General Functions
  • Conditional Expressions
  • Date and Time Functions
  • Numeric and String Functions
  • Subqueries
  • Rank and Window Functions

Module 8: Business Intelligence Tool: PowerBI

This module covers Power BI essentials, including importing and cleaning data, modeling relationships, using DAX for calculations and measures, advanced visualization, time intelligence functions, and publishing options.

  • Power BI Overview and Components
  • Importing Data into Power BI from Various Sources
  • Data Transformation and Cleaning using Power Query Editor
  • Modeling Data Relationships in Power BI
  • Introduction to DAX Functions and Calculated Columns
  • Creating Custom Measures and KPIs in Power BI
  • Advanced Visualization Techniques
  • Working with Time Intelligence Functions in DAX
  • Power BI Publishing and Sharing Options

Module 9: Business Intelligence Tool: Tableau

This module covers the fundamental concepts and functionalities of Tableau, enabling you to create interactive and insightful visualizations from various data sources. 

  • Introduction to Tableau and Its Components
  • Connecting to Data Sources in Tableau
  • Data Preparation and Transformation in Tableau Prep Builder
  • Building Basic and Advanced Visualizations
  • Implementing Interactive Dashboards
  • Introduction to Tableau Calculations
  • Geospatial Analysis and Mapping
  • Using Tableau’s Forecasting Features
  • Introduction to Tableau Server and Tableau Online

Module 10: Predictive Analytics

This  module delves into the realm of predictive modeling techniques, equipping you with the knowledge and skills to forecast future trends and outcomes based on historical data. 

  • Introduction to Predictive Analytics and Machine Learning
  • Types of Machine Learning Problems
  • Introduction to Regression Analysis
  • Implementing Regression using Excel
  • Interpretation of Regression Models
  • Introduction to Clustering
  • Exploring Excel Add-ins for Predictive Analytics

Module 11: Building the Business Case Document

This module equips participants with a structured approach to articulate the benefits, assess risks, and estimate the return on investment (ROI).

  • Understanding Business Objectives
  • Developing Scope, Plan, Budget, and ROI Calculations
  • Gathering Requirements and Risk Assessment
  • Developing a Business Case Document
  • Analyzing Industry-Specific BI Case Studies
  • Maximizing ROI from BI Investments

Module 12: Governance & Security in BI

This module explores risk management strategies within BI environments, focusing on identifying, assessing, and mitigating risks to ensure the successful implementation and operation of business intelligence initiatives.

  • Risk Management Strategies in BI Environments

Module 13: Data Interpretation & Reporting

This module equips individuals with skills to interpret data from diverse sources, derive key insights, and effectively communicate findings through storytelling, reports, and presentations.

  • Introduction to Data Interpretation
  • How to identify the Data sources-databases, files, APIs, web services, and streaming data sources.
  • API Integrations for Data Access
  • Deriving KPIs from a Business Perspective
  • Communicating Insights Through Storytelling
  • Report Preparation and Presentation

Module 14: Emerging Trends in Business Intelligence

This module explores AI and ML in BI, covering algorithm integration for advanced analytics and automation, future trends, and ChatGPT for Business Analysts. It offers prompt tips and addresses AI implementation challenges.

  • Artificial Intelligence and Machine Learning in BI
  • Integrating AI and ML Algorithms for Advanced Analytics
  • AI-Driven Automation in BI Processes
  • Future Trends in AI-Powered BI
  • ChatGPT for Business Analysts
  • Tips for Effective Prompts
  • Challenges and Considerations in AI Implementation

Digital Marketing

Module 15: Marketing & Digital Marketing Foundations

This module covers marketing basics such as business types, the marketing funnel (AIDA model), and the transition from traditional to digital marketing. It emphasizes leveraging digital channels for growth, online reputation management, and key website design elements.

  • Fundamentals of Marketing
  • Business Types in Marketing
  • Marketing Funnel (Consumer Journey  AIDA Model)
  • Introduction to Digital Marketing and its Importance 
  • Traditional Marketing Vs Digital Marketing
  • Leveraging Digital Marketing Channels for Business Growth
  • Online Reputation Management (ORM)
  • Designing and Building a Web Presence
  • How do websites work?
  • Key website ingredients
  • Website design dos and don’ts

Module 16: Search Engine Marketing (SEM)

This module provides an overview of search engines, including their operation and the distinction between organic and paid search. It covers essential SEO concepts such as on-page and off-page optimization, technical SEO, local SEO tactics, and tools like Google Search Console.

  • Search Engine Basics
  • How Search Engines Work  Crawling, Indexing & Serving Results
  • Organic vs Paid Search
  • Fundamentals of SEO
  • OnPage SEO & Keyword Research
  • OffPage SEO & Link Building
  • Technical SEO
  • SEO for Local Business (Local SEO)
  • Google Search Console
  • SEO Reporting & Analytics
  • SEO Case Study.

Module 17: Paid Marketing

This module provides a comprehensive overview of paid marketing, from account setup to ad creation and targeting strategies, supported by real-world case studies for practical insights.

  • Introduction to Paid Marketing: Understanding the Basics
  • Understanding the Role of Paid Marketing in Business Growth
  • Setting Up Your Paid Marketing Accounts: Google Ads, Meta Ads(Facebook and Instagram), LinkedIn Ads.
  • Keyword Research and Selection for PPC (Google Ads, YouTube Ads)
  • Predictive Analytics for Paid Marketing: Forecasting Campaign Performance
  • Creating Compelling Ad Copy and Visuals
  • Ad Targeting Options: Demographics, Interests, and Behaviors
  • Bid Strategies and Budget Management
  • Tracking Conversions and ROI Measurement
  • Video Advertising on Google, Meta, and LinkedIn
  • Case Studies and RealWorld Examples of Successful Paid Marketing Campaigns

Module 18: Social Media Strategy & Content Marketing

This module covers social media and content marketing essentials, including platform strategies, content creation, and email marketing integration. It emphasizes LinkedIn and Twitter for B2B growth and provides insights into email marketing strategies and performance measurement.

  • Introduction to Social Media and Content Marketing for Business Growth
  • Understanding the Role of Social Media Platforms (LinkedIn, Facebook, Instagram, Twitter) in Business Growth
  • Crafting a Comprehensive Social Media Strategy: Goals, Audience, and Brand Voice
  • Developing a Content Marketing Plan: Integrating Social Media and Email Marketing
  • Leveraging LinkedIn for B2B Growth: Networking, Lead Generation, and Thought Leadership
  • Twitter for Business: Realtime Engagement, Trends, and Customer Service
  • Creating Engaging and Relevant Content for Social Media Platforms
  • Effective Email Marketing Strategies for Business Growth
  • Crafting Compelling Email Content: Newsletters, Promotions, and Announcements
  • Measuring Success: Key Metrics and Analytics for Social Media and Email Marketing
  • Case Studies and Best Practices in Social Media Strategy and Content Marketing for Business Growth

Module 19: Marketing Analytics & Digital Marketing Tools

This module covers digital marketing metrics, GA4, GTM, PPC, and social analytics, along with crafting effective strategies and integrating AI tools.

  • Digital Marketing Metrics
  • Google Analytics 4 (GA4)
  • Google Tag Manager (GTM)
  • PPC Analytics
  • Social Analytics
  • Creating a Digital Marketing Strategy
  • AI Tools for Digital Marketing

Module 20: Google Looker Studio:An enterprise platform for BI and Data Visualization

This module covers Google Looker Studio, including its benefits, interface, and data connectivity. Participants learn to create dashboards, reports, and charts, exploring visualization techniques and sharing options.

  • Introduction to Google Looker Studio
  • Benefits and Limitations of Looker Studio
  • Understand the basics and key features of Looker Studio.
  • Home Page Interface Walkthrough and Connecting to Data Sources.
  • Learn how to connect to various data sources using different types of connectors.
  • Gain knowledge about Looker Studio’s data collection and transformation options.
  • Creating Dashboards, Reports & Charts
  • Explore visualization techniques and adding interactions in Looker Studio.
  • Discover how to share Looker Studio reports with others.

FAQs

Q. Are there any benefits with the certification ?

Ans. The certification is provided by IFACET – IIT Kanpur

Q. Will the certification help in Placements ?

Ans. Yes, 100% placement Support is provided for all the students who pass the eligibility criteria

Q. Does the certification lead to an alumni status from IITK ?

Ans. No

Instructor Profile

Name: Kousik Krishnan

Quantitative Trader working with a high-frequency trading firm. Skilled in C++ and Python. Experienced in building proprietary trading strategies. Strong research professional with an academic degree focused on Mathematics and Computer Science.