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Master the Fundamental Concepts of Business Analytics. Enroll today and become a skilled Business Analytics expert.

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30 Hrs.

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  • The Business Analytics course in Canada is designed to teach students how to analyze business data and make informed decisions based on insights. This course covers key skills, including data analysis, statistical methods, and the use of analytics tools such as Excel, SQL, Tableau, and Power BI. You will learn how to analyze trends, create reports, and use data to improve business strategies.

Business Analytics Course in Canada

About-Us-Course

  • The Business Analytics Training in Canada aims to equip students with the technical skills to analyze business data effectively and make data-driven decisions. Some of the key learning objectives include:
    • Master the Core Tools: Learn to use industry-standard tools like Excel, SQL, Tableau, and Power BI.

      Data Collection and Processing: Understand how to gather, clean, and organize data from various sources.

      Statistical Analysis: Learn basic statistics to interpret data, spot trends, and predict future outcomes.

      Data Visualization: Gain skills to create interactive dashboards and reports using Tableau and Power BI.

      Problem Solving with Data: Use data analysis to find solutions to business challenges and improve decision-making.

      Predictive Analytics: Learn to build models to predict future trends based on data

  • After completing the Business Analytics Training in Canada, freshers can expect a good salary depending on their role. On average, salaries for entry-level positions are as follows:
    • Entry-Level Business Analyst: CAD 50,000 to CAD 65,000 per year.

      Junior Data Analyst: CAD 45,000 to CAD 60,000 per year.

      Business Intelligence Analyst: CAD 55,000 to CAD 70,000 per year.

  • Upon completion of the Business Analytics Training in Canada, your career can grow in several ways:
    • Junior Analyst to Senior Analyst: With more experience, you can move into senior roles managing complex data projects.

      Specializing in Business Intelligence: You may become an expert in data visualization tools like Tableau and Power BI.

      Data Scientist: Transition into more advanced data roles like data scientist, which involves machine learning and statistical modeling.

      Consultant or Manager: Move into leadership roles, where you help businesses make strategic decisions based on data.

  • The Business Analytics Training in Canada is growing in popularity because data is becoming an essential part of decision-making for businesses. Heres why its so popular:
    • High Demand for Analytics Professionals: Almost every industry needs skilled analysts to help them make better decisions using data.

      Versatile Career Paths: The skills learned in the course can be applied to various roles across industries like finance, healthcare, and retail.

      Data-Driven Business: Companies are increasingly relying on data, which makes business analytics a high-demand skill.

      Career Opportunities: With the rise of data-driven decision-making, the need for business analysts is expected to increase.

      Hands-On Learning: The course includes practical training on real-world analytics tools like Excel, Tableau, and SQL.

  • After completing the course, you will be prepared for various roles in business analytics, including:
    • Business Analyst: Identifying business needs, gathering data, and providing actionable insights for decision-making.

      Data Analyst: Analyzing data to identify trends and patterns that help businesses make better decisions.

      Business Intelligence Analyst: Creating reports and dashboards using tools like Tableau and Power BI to visualize data for management.

      Data Scientist: Using advanced statistical techniques and machine learning to analyze complex data and predict future trends.

      Consultant: Advising companies on how to use data to improve their business operations and strategies.

  • Business analysts are in demand across many industries, including:
    • Finance: Banks, investment firms, and insurance companies use analytics to assess risk, improve customer service, and optimize operations.

      Healthcare: Healthcare providers and organizations use analytics to improve patient care and operational efficiency.

      Retail and E-Commerce: Retailers analyze customer data to optimize inventory, marketing, and sales strategies.

      Consulting: Consulting firms need data analysts to help clients use data to improve their business operations.

      Technology: IT companies use analytics to improve products, services, and customer experiences.

  • Upon successful completion of the Business Analytics Training in Canada, students will receive a Certificate of Completion. This certificate demonstrates your proficiency in business analytics and can help you stand out to employers.

  • CAD 1,500 - CAD 5,000

  • CAD 300 - CAD 600

  • The placement process for Business Analytics students typically includes:
    • Resume Building: We help you create a professional resume tailored to business analytics roles.

      Interview Preparation: Youll receive guidance on how to perform well in interviews, with mock interview sessions to boost your confidence.

      Job Placement Assistance: We partner with top companies in various industries to help you find job opportunities.

      Job Fairs and Networking: Access job fairs and networking events where you can meet potential employers.

      Post-Course Support: Even after completing the course, we provide ongoing support to help you with job placement.

Why should you get started with the Business Analytics Course?

Not just learning –

we train you to get hired.

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CURRICULUM & PROJECTS

Business Analytics Training Program

    Understanding the evolution of analytics in business

    What is Business Analytics Definitions and relevance

    Components of Business Analytics: People, Process, Technology

    Difference between Data Science, Business Analytics, and Business Intelligence

    Types of analytics: Descriptive, Predictive, Prescriptive

    Overview of the Analytics Lifecycle

    Business Analyst roles and responsibilities

    Tools used in Business Analytics (Excel, SQL, Python, Power BI, Tableau)

    Industry applications of Business Analytics

    Case studies: Banking, Retail, Healthcare, Manufacturing

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    Excel interface and data navigation tips

    Working with structured datasets in Excel

    Data formatting, conditional formatting, and data validation

    Formulas and Functions:

    • Text Functions (LEFT, RIGHT, MID, CONCATENATE)
    • Logical Functions (IF, AND, OR, NOT)
    • Lookup Functions (VLOOKUP, HLOOKUP, INDEX, MATCH)
    • Statistical Functions (AVERAGE, MEDIAN, MODE, STDEV)

    Data Cleaning Techniques

    Sorting, Filtering, and Advanced Filters

    Using Named Ranges for clarity and speed

    Charts and Graphs: Column, Line, Bar, Pie, Combo, Sparklines

    Creating PivotTables and PivotCharts

    Using slicers and timeline filters

    Introduction to Power Query for data transformation

    Goal Seek, Scenario Manager, and Data Tabl

    Creating interactive dashboards with Excel

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    Types of data: Structured vs Unstructured, Qualitative vs Quantitative

    Levels of Measurement: Nominal, Ordinal, Interval, Ratio

    Measures of Central Tendency: Mean, Median, Mode

    Measures of Dispersion: Range, Variance, Standard Deviation

    Skewness and Kurtosis

    Basics of Probability and probability distributions

    Normal Distribution, Binomial and Poisson Distributions

    Sampling techniques and sample size determination

    Central Limit Theorem

    Confidence intervals and margin of error

    Hypothesis Testing:

    • Null and Alternate Hypotheses
    • One-tailed vs Two-tailed tests
    • Z-test, t-test (one-sample, two-sample)
    • ANOVA
    • Chi-square test

    Correlation analysis and Pearson's coefficient

    Linear Regression analysis

    Interpreting statistical outputs in business context

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    Basics of databases and relational database design

    Understanding ER models and data schemas

    Introduction to SQL syntax and queries

    SELECT statements and filtering with WHERE clause

    Sorting results using ORDER BY

    Aggregate functions: SUM, AVG, COUNT, MIN, MAX

    GROUP BY and HAVING clauses

    Using ALIAS for readability

    Understanding JOINs: INNER, LEFT, RIGHT, FULL OUTER

    Subqueries and Nested queries

    Common Table Expressions (CTEs)

    Window functions (ROW_NUMBER, RANK, LEAD, LAG)

    Case expressions and IF conditions

    Date and string functions

    Creating and modifying views

    Basic data manipulation (INSERT, UPDATE, DELETE)

    Practice with large datasets

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    Introduction to BI tools: Differences between Power BI and Tableau

    Connecting to multiple data sources

    Data modeling and data relationships

    Measures vs calculated columns

    Data transformation and cleaning using Power Query

    Designing basic and advanced charts:

    • Line, Bar, Column, Pie, Scatter, Heat Maps, Tree Maps, Waterfall, KPI Cards

    Using filters, slicers, and date hierarchies

    Drill-downs and drill-through reports

    Tooltips and interactions

    Using DAX in Power BI:

    • CALCULATE, FILTER, ALL, RELATED, Time Intelligence functions

    Creating dashboards and layouts

    Publishing and sharing dashboards

    Real-world dashboarding use cases:

    • Sales dashboards
    • Marketing campaign performance
    • Financial KPI dashboards
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    Introduction to Python and Anaconda environment

    Data types, variables, control structures (if, for, while)

    Functions and Lambda expressions

    Working with lists, tuples, dictionaries

    Reading and writing files

    Introduction to NumPy:

    • Arrays, array operations, indexing

    Introduction to Pandas:

    • Series and DataFrame objects
    • Reading data from CSV, Excel, SQL
    • Data selection, filtering, sorting
    • Handling missing values and duplicates
    • GroupBy operations
    • Merging and joining datasets

    Exploratory Data Analysis (EDA)

    Data visualization with:

    • Matplotlib: Line plots, bar charts, histograms
    • Seaborn: Pairplots, heatmaps, boxplots

    Automating Excel/CSV reports with Python

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    Overview of Machine Learning in Business

    Supervised vs Unsupervised Learning

    Linear Regression:

    • Model creation, evaluation (R-squared, MAE, RMSE)

    Logistic Regression:

    • Probability interpretation, ROC Curve, AUC

    Decision Trees and Random Forests

    K-Means Clustering

    Model evaluation metrics:

    • Confusion Matrix, Accuracy, Precision, Recall, F1 Score

    Overfitting and Underfitting

    Train-test split and Cross-validation

    Feature selection and engineering basics

    Business case applications:

    • Customer churn prediction
    • Sales forecasting
    • Market segmentation
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    Choosing a real-world capstone project (Retail, Finance, HR, Marketing, etc.)

    Defining the business problem statement and KPIs

    Data collection and preparation

    Exploratory Data Analysis and visualization

    Building dashboards and simple predictive models

    Final project presentation with business insights

    Peer and mentor reviews

    Resume building tailored to Business Analyst roles

    Interview preparation:

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30 Hrs.
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Prepare & Practice for real-life job interviews by joining the Mock Interviews drive at Croma Campus and learn to perform with confidence with our expert team.Not sure of Interview environments? Don’t worry, our team will familiarize you and help you in giving your best shot even under heavy pressures.Our Mock Interviews are conducted by trailblazing industry-experts having years of experience and they will surely help you to improve your chances of getting hired in real.
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FAQ's

You will learn to use tools like Excel, SQL, Tableau, Power BI, and more to analyze and visualize data.

No, this course is designed for beginners, so you don’t need any prior experience in analytics or data science.

Yes, many institutions offer the Business Analytics course online, allowing you to study from anywhere.

We offer resume building, interview preparation, job placement assistance, and access to job fairs and networking events.

This course will provide you with the skills to enter the growing field of business analytics and increase your chances of landing a job with top companies.

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  • - Get Tips from Trainer to Clear Interviews
  • - Attend Mock-Up Interviews with Experts
  • - Get Interviews & Get Hired

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