Certified Data & Business Analyst (CDBA) Program

    Sign Up For A Callback

    CFI – India’s Leading Finance and Analytics Training Institute

    CFI’s 3-month “Certified Data & Business Analyst (CDBA)” program prepares you to become a Certified Data & Business Analyst CDBA equips you with the skills and insights needed to thrive in today’s data-driven business landscape. This comprehensive program is designed to empower professionals and aspiring analysts with the knowledge and expertise required to extract actionable insights, drive informed decision-making, and propel organizational success.

    The Business and Data Analysis Mastery course goes beyond traditional analytics, providing a holistic approach that intertwines business acumen with advanced data techniques. Whether you are an aspiring data analyst eager to enter the field or a seasoned professional looking to upskill, this course is your gateway to mastering the symbiotic relationship between business strategy and data analytics.

    Top Hiring companies

    genpact
    Wipro

    Who Should Enroll?

    Our training is open to ambitious candidates who come from a range of backgrounds and will typically be

    Graduates / Engineers

    Post-Graduates / MBAs

    CAs/CFAs or equivalents

    Analysts / Executives

    Business Decision Makers

    Speak to our Counselor to know if you are good fit for the program at +91-9354266554 or Mail Us at [email protected]

    Course Format

    Duration:

    12 - 15weeks


    Format:

    Blended learning with a mix of live lectures, hands-on workshops, and real-world case studies

    Assessments:

    Practical assignments, quizzes, and a final project applying learned concepts to a business scenario.

    Technologies / Covered

    MS Excel

    Power BI

    SQL

    Python and its libraries

    Data Analytics

    Statistics

    Key Areas of Learning

    Business Strategy Integration

    Data Exploration and Visualization

    Statistical Analysis for Decision-Making

    Data-Driven Decision-Making

    Financial Modeling and Valuation Analysis CDBA Program

    1. Working with Name Range:
    • What does naming a cell range mean?
    • Rules for naming cells and ranges
    • Naming cell range(s) in a worksheet
    • Navigating through workbooks using named ranges
    • Creating named ranges automatically based on cell values

    2) Numeric/Statistial Functions/ Lookup Function:-

    • SUM, SUMIF, SUMIFS
    • AVERAGE, AVERAGEIF, AVERAGEIFS
    • COUNT, COUNTIF, COUNTA, COUNTBLANK
    • MAX, MIN, Vlookup, HLookup

    3) Understanding References

    • Understanding References
    • Relative References
    • Absolute References
    • Mixed References
    • Utilizing names for writing formulae.

    4) Filtering / Sorting

    • Filtering and Sorting
    • Concept and Implementation

    5) Logical Functions

    • If Function
    • AND, OR Function
    • Nested Functions

    6) Conditional Formatting

    • Create Conditional Formatting
    • Rule 1 to 6

    7) Creating Dropdown List

    • Simple Dropdown List
    • Conditional Dropdown List

    8) Date & Time Functions

    • TODAY, NOW
    • DAY, MONTH, YEAR
    • WEEKDAY

    9) Working with PivotTables Charts

    • Creating Pivot Table
    • Exploring Table Design Tab
    • Slicers
    • Creating Chart
    • Formatting Chart

    Day 1

    Module 1: Understanding Analytics & Business Intelligence (BI) Concept

    This module will guide the candidate through the basics of Analytics. Learn about the Data & Analytics

    • Data & Analytics
    • Introduction to Business Intelligence
    • Importance of Business Intelligence
    • Overview of Self-Service BI

    Module 2: Microsoft Power BI Introduction
    • Power BI introduction and Overview
    • Power BI Desktop – Installation
    • Explain Power BI Desktop
    • Power BI Screen Elements and Toolbars

    Module 3: Connecting Power BI with Different Data Source
    • Connect to CSV files in Power BI
    • Connect to Excel in Power BI
    • Connect to PDF in Power BI
    • Connect to Web Page in Power BI

    Module 4: Data Cleaning with Power Query
    • Power Query Introduction
    • Query Editor interface
    • Column Transformations
    • Combining Data: Append Query
    • Combining Data: Merge Query
    • Number, Date and Time Calculations
    • Text Transformation
    • Sorting & Filters Data
    • Splitting & Merging Data
    • Transforms Data
    • Pivot and Unpivot Data
    • Adding Columns
    • M Built-in Function

    Day 2

    Module 5: Data Modelling in Power BI
    • What is a PowerPivot?
    • What Is a Data Model?
    • What is a Relationship?
    • Introduction to DAX
    • Detecting and Creating Relationships of Tables
    • Understanding the Star Schema
    • Creating Calculated Columns
    • Creating Tables
    • Creating Measure
    • Row Context vs Set Context
    • Working with DAX Functions
    • Getting Data from Related Tables


    Module 6: Creating Report & Visualization Type in Power BI
    • Create a New Power BI Report
    • Report Editor in Power BI
    • Add, Rename, Delete & Duplicate Page to Power BI Report
    • Save Report in Power BI
    • Change how visuals interact in a report
    • Open a Power BI in Reading View
    • Page Display Setting in Power BI report
    • Type of Visualization in Power BI ReportAdding Visuals
    (Bar, Column, Line, Area, Ribbon, Pie, Scatter, Tree Map, Waterfall, Combo,
    Funnel, KPI, Radial Gauge, Doughnut Chart etc.)
    • Data Categories, Geo-Data and Maps
    • Creating and Working with Tables and Matrix Views
    • Customizing Visuals by Field, Format & Analytic
    • Filtering Visual, Page, All Pages
    • Using Interactive Slicers – Dropdowns and Searches
    • Number, Date, Text Slicers
    • Applying Conditional Formats to Visualizations
    • Drill Visualizations to see underlying Data
    • Date Hierarchies
    • Show Values as and Quick Measures
    • Custom Visualization in Power BI
    • Selection Pane
    • Lock Objects
    • Adding Graphics
    • Bookmarks
    • Spotlight
    • Report Themes
    • Using Security by Creating Role Based Views
    • Insight – Explain Increase/Decrease
    • Export Power BI Data to CSV

    Day 3

    Module 6: Creating a Power BI Dashboard
    • Dashboard vs Reports
    • Creating a Power BI Dashboard
    • Dashboard Tiles in Power BI
    • Pin a Tiles to Power BI Dashboard from a report
    • Power BI publisher in Excel
    • Data alert in Power BI Service
    • Add Image, Text box, Video or web code to your dashboard
    • Tips for designing a great Power BI Dashboard
    • Create Phone View of a Dashboard
    • Power BI Q&A
    • Quick Insights with Power BI

    Module 7: Refreshing Data
    • Configure schedule refresh data
    • Refresh a dataset created from Power BI Desktop (Local)
    • Refresh a dataset created from Power BI Desktop (Cloud)
    • Disable privacy setting

    Module 1: Introduction to SQL and Relational Databases

    • Relational database management systems (RDBMS)
    • Comparison of SQL and Excel features and use cases


    Module 2: SQL Basics
    • SQL syntax, keywords, and conventions
    • Data types and operators (arithmetic, comparison, logical)
    • SQL constraints (Primary/check/default/null….)
    • SELECT statement, projection, and filtering data with WHERE aliases and expressions
    • Sorting data with ORDER BY


    Module 3: Working with Joins and Unions
    • Different types of joins (INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL JOIN, CROSS JOIN) ON,
    USING, and NATURAL keyword usage
    • UNION and UNION ALL set operations


    Module 4: Aggregating Data and Group Functions
    • GROUP BY clause and grouping sets
    • HAVING clause for filtering aggregated results
    • Aggregate functions: SUM, COUNT, AVG, MIN, MAX


    Module 5: Advanced SQL Queries
    • EXISTS and NOT EXISTS operators
    • Window functions: RANK, DENSE_RANK, ROW_NUMBER, NTILE, etc.
    • Index in SQL
    • Nested Stored procedure


    Module 6: SQL for Data Management
    • Data Manipulation Language (DML): INSERT, UPDATE, DELETE
    • Transactions: BEGIN, COMMIT, ROLLBACK
    • Optimization SQL Query
    • Procedure/Function


    Module 7: SQL for Data Analysis and Reporting
    • Pivoting data: transforming rows to columns
    • Unpivoting data: transforming columns to rows
    • GROUP BY extensions (ROLLUP, CUBE, and GROUPING SETS)

    • Discussion on Statistics concepts and theories
    • Correlation, Var-Covar, Beta, Regression, Monte Carlo Simulation
    • DATA ANALYSIS WITH PYTHON
      Explore the world of data analysis with Python! Learn to dissect data using multi-dimensional arrays in numpy, harness the power of Data Frames in pandas, leverage the SciPy library for mathematical routines, and delve into machine learning with scikit-learn. This course provides hands-on experience through labs using real Python tools like Jupyter notebook in JupyterLab, making your journey into data
      analytics both insightful and practical.

      MODULE 1
      – Introduction
      – Datatypes, Variables, and Operators
      – String and its Associated Functions
      – If-Else Statement

      MODULE 2
      – Regular Expressions
      – Looping Statements
      – Nested Loop
      – Pattern-Based Problem

      MODULE 3
      – Data Structure in – Python:
      – List
      – Tuple
      – Dictionary
      – Functions in  Python:
      – Recursion
      – Functions Return Statement
      – Modules in Python

      MODULE 4
      – List Comprehension
      – File Handling in Python:
      – Reading, Writing, and Appending into Files
      – Comparing Files
      – Classes and Objects
      – Inheritance and Polymorphism

      MODULE 5
      – Numpy for Creating Arrays
      – Data Analysis Using Pandas
      – Matplotlib for Graphical Representation

       

      DATA ANALYSIS WITH PYTHON
      COURSE SYLLABUS

      MODULE 1
      – IMPORTING DATASETS
      – Learning Objectives
      – Understanding the Domain
      – Understanding the Dataset
      – Python package for data science
      – Importing and Exporting Data in Python
      – Basic Insights from Datasets

      MODULE 2
      CLEANING AND PREPARING THE DATA
      – Identify and Handle Missing Values
      – Data Formatting
      – Data Normalization

      MODULE 3
      SUMMARIZING THE DATA FRAME
      – Descriptive Statistics
      – Basics of Grouping
      – ANOVA
      – Correlation
      – More on Correlation

      MODULE 4
      MODEL DEVELOPMENT
      – Simple and Multiple Linear Regression Model
      – Evaluation Using Visualization
      – Polynomial Regression and Pipelines
      – R-squared
      – MSE for In-Sample Evaluation
      – Prediction and Decision Making

     

    • MODULE 5
      MODEL EVALUATION
      – Model Evaluation
      – Over-fitting
      – Under-fitting
      – Model Selection
      – Ridge Regression
      – Grid Search

      D A T A  V I S U A L I Z A T I O N  W I T H  P Y T H O N

      COURSE SYLLABUS

      MODULE 1
      INTRODUCTION TO VISUALIZATION TOOLS**
      – Introduction to Data Visualization
      – Introduction to Matplotlib
      – Basic Plotting with Matplotlib Line Plots

      MODULE 2
      BASIC VISUALIZATION TOOLS
      – Area Plots
      – Histograms
      – Bar Charts

      MODULE 3
      SPECIALIZED VISUALIZATION TOOLS
      – Pie Charts
      – Box Plots
      – Scatter Plots
      – Bubble Plots
    •  
    • MODULE 4
      ADVANCED VISUALIZATION TOOLS
      – Waffle Charts
      – Word Clouds
      – Seaborn and Regression Plots

    – Soft Skills Training
    – Linkedin Profile Update
    – CV Samples to follow.
    – Mock Interviews

    Why CFI Education

    Case Study Approach

    Real life cases for most effective and skill based learning.

    Case Study Approach

    Real life cases for most effective and skill based learning.

    Individual Attention

    Focus on building technical expertise and ensure the learning of all candidates.

    Capstone Projects

    A month long project work post classroom sessions to gain confidence in their domain area.

    Soft Skill Development

    Helps candidates in understanding best practices and soft skills development for cracking interviews.

    100% Placement Assistance

    Have a dedicated team of placement who work towards, CV building and scheduling interviews.

    Financial Modeling & Valuation - Course Fee

    Classroom / Live Online Self-Paced
    INR 55000 INR 30000
    Classroom / Live Zoom Yes
    Class Recordings Yes Yes
    Detailed Study Material Yes Yes
    Case Studies Yes Yes
    Capstone Project Yes Yes
    App Access (Android) Yes Yes
    100% Placement Support* Yes Yes
    CV & Interview Prep Yes Yes
    Live Doubts Sessions Yes
    Whatsapp Group Yes
    Email Support Yes
    BUY NOW BUY NOW

    100% Placement Support*

    CFI Education provides placement assistance to all the candidates who complete our in-house Financial Modeling or Investment banking programs. Apart from technical classroom training, we prepare candidates for soft skills, and conduct mock interviews. Once they feel confident, they can start applying for various job opportunities provided by our dedicated placement team. The placement process is usually start at 8th week of the training program.

    We charge a placement fee of 5% of annual fixed ctc. This fee is applicable only when candidates is selected through our placement team efforts and accepts the job offer. Contact our team to know more about how CFI Education can help you launch your career in core finance domain.

    After completing CBDA course, students will be able to pursue diverse and rewarding career paths across various industries including:

    Financial modeling

    1. Data Analyst:

    As a data analyst, you will play a crucial role in interpreting and analyzing data to help organizations make informed decisions. You'll work with data visualization tools, statistical techniques, and reporting frameworks.

    2. Business Analyst:

    Business analysts bridge the gap between business needs and technological solutions. With a strong understanding of both business strategy and data analysis, you can analyze processes, identify areas for improvement, and recommend data-driven solutions.

    3. Business Intelligence Analyst:

    Specializing in business intelligence, you'll focus on collecting, analyzing, and visualizing data to help businesses gain insights into their operations, customers, and market trends.

    4. Data Scientist:

    For those interested in a more advanced role, data science involves using machine learning and advanced statistical Techniques to extract deeper insights and predict future trends, contributing to strategic decision-making.

    5. Market Research Analyst:

    Leveraging your skills in data analysis, you can work as a market research analyst, helping companies understand market trends, consumer behavior, and competitive landscapes.

    6. Operations Analyst:

    Operations analysts use data to optimize business processes and improve efficiency. Your skills in data analysis can help organizations streamline operations and reduce costs.

    7. Financial Analyst:

    If you have a keen interest in finance, your analytical skills can be applied in financial analysis roles, where you'll assess the financial health of organizations, analyze investment opportunities, and contribute to strategic financial planning.

    8. Consultant:

    With expertise in both business and data analysis, you can work as a consultant, advising organizations on optimizing their operations, implementing data-driven strategies, and solving complex business challenges.

    9. Entrepreneur or Business Owner:

    Armed with a deep understanding of how data can drive business decisions, you may choose to start your own business, leveraging your skills to make informed strategic choices.

    Success Stories

    Students Speak

    Financial Modeling & Valuation Program - Certification

    Financial Modeling Course