Certified Business Analytics Professional

SF-DA-CBAP-1412

  • (220 Reviews)

  • Skills: Acquire essential data analysis techniques, statistical modelling, and data visualization skills crucial for the current business environment.
  • Careers: Unlock doors to lucrative career opportunities as a business analyst, data analyst, or market research analyst in diverse industries worldwide.
  • Internship: Kickstart your journey with a 1-month unpaid internship, gaining hands-on experience and real-world insights under the guidance of seasoned professionals.
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Overview

Skillfloor offers a complete set of business analytics courses tailored to meet the needs of aspiring professionals seeking to delve into business analysis. With a focus on practical skills and real-world applications, Skillfloor's business analyst courses provide participants with a solid foundation in key areas such as data analysis, statistical modelling, and decision-making frameworks. Whether you're a novice looking to break into the industry or a seasoned professional aiming to sharpen your analytical prowess, Skillfloor offers a diverse range of courses for business analysts at every skill level. From foundational business analytics courses designed to introduce fundamental concepts to advanced seminars exploring cutting-edge methodologies, Skillfloor equips learners with the tools and knowledge needed to excel in today's competitive business environment.


At Skillfloor, the course is not only on theoretical knowledge but also on hands-on experience and practical insights. Through a blend of interactive lectures, case studies, and hands-on projects, participants in Skillfloor's business analytics course gain valuable expertise in data-driven decision-making and strategic planning. Whether you're interested in mastering data visualization techniques, honing your predictive analytics skills, or understanding the intricacies of business intelligence tools, Skillfloor offers a diverse selection of courses to suit your specific interests and career goals. With experienced instructors and a supportive learning environment, Skillfloor's business analysis courses provide a transformative educational experience that empowers individuals to thrive in the changing field of business analytics.

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₹60,000

₹14,900

Skill Level

Advanced

Internship

1-month Unpaid

Live Project

35

Certificate

Yes

Live Training

Yes

Career Assistance

Yes

Expiry Period

Lifetime
Enrol Now
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Course Highlights

  • Introduction to Business Analytics: Students are introduced to the foundational concepts of business analytics, including its importance in today's data-driven business environment.

  • Data Management Techniques: This section covers methods for collecting, storing, and managing data effectively to ensure its quality and accessibility for analysis.

  • Fundamentals of Statistical Analysis: Learners explore basic statistical concepts and techniques that are crucial for interpreting data and deriving meaningful insights.

  • Excel for Analytics: The course delves into the use of Excel, a key tool in analytics, teaching students how to utilize its advanced features for data analysis.

  • Introduction to Python for Data Analysis: Participants are introduced to Python, a leading programming language in data analytics, focusing on its applications in handling and analyzing data.

  • Data Visualization: This module emphasizes the importance of visualizing data effectively to communicate insights clearly and persuasively using tools like Tableau and Power BI.

  • Predictive Analytics Basics: Students learn about predictive analytics techniques, including regression analysis, to forecast future trends and behaviours from historical data.

  • Decision-Making Models: The course covers various models and frameworks that aid in making informed business decisions based on analytical findings.

  • Case Studies in Business Analytics: Through real-world case studies, learners apply the concepts and techniques learned to solve business problems, enhancing their practical understanding.

  • Ethics and Privacy in Analytics: This essential part of the course addresses the ethical considerations and privacy concerns involved in handling and analyzing data.

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Certification

This program, the Certified Data Analysis Associate, teaches people the essential skills and knowledge needed for a successful career in data analysis. Participants will learn how to find important insights in different sets of data, become experts in statistical techniques, and use modern tools for visualizing data. The program covers important topics like cleaning data, exploring data, and using statistics to understand complex data sets. This certification shows that individuals are skilled in using relevant software and methods, which helps them make decisions based on data. Completing this program proves that individuals are good at data analysis, making them valuable in many industries. The Certified Data Analysis Associate certificate shows a commitment to being excellent at using data for smart decision-making, making graduates important in today's professional world where data is crucial.

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Internship Certificate

certificate

Completing this Analytics Course certifies your proficiency in data analysis, statistical methods, and essential analytics tools. This certification shows you can transform raw data into actionable insights, improving decision-making in various business contexts. It indicates your understanding of data visualization, predictive modelling, and data-driven strategy development, providing you with the skills to excel in analytics. This credential reflects your dedication to continuous learning and commitment to leveraging data for strategic advantage.

Tools Covered

Tableau, Power BI, Pandas, SQL, TensorFlow and Keras, Matplotlib, GitHub and RStudiotools_covered Tableau, Power BI, Pandas, SQL, TensorFlow and Keras, Matplotlib, GitHub and RStudio

Top 10 reasons

  1. Industry-Relevant Skills: You will gain knowledge and practical skills in analytics methodologies and tools from our Certified Business Analytics Associate course, which are immediately applicable to the business world of today.

  2. Promotion in Career: Obtain a distinguished certification that boosts your reputation and provides access to a wide range of employment options in business analytics positions across sectors.

  3. Data-driven Decision Making: Acquire the skills necessary to use data to guide choices, propel strategic projects, and obtain a competitive advantage in the market.

  4. Gain insights: the capacity to derive useful insights from data to streamline procedures, spot patterns, and locate chances for expansion and creativity.

  5. Excellence in Problem-Solving: To effectively handle business difficulties, develop your strong problem-solving abilities by evaluating intricate data sets and creating workable solutions.

  6. Quantitative Analysis Proficiency: Gain proficiency in quantitative analysis techniques, including statistical methods and predictive modeling, to derive meaningful conclusions from data.

  7. Strategic Planning: Understand how to use analytics to support strategic planning and decision-making processes, aligning business objectives with data-driven insights.

  8. Effective Communication: Learn how to effectively communicate analytical findings and recommendations to stakeholders, fostering collaboration and buy-in for data-driven initiatives.

  9. Continuous Improvement: Embrace a culture of continuous improvement by using analytics to monitor performance, identify areas for optimization, and drive ongoing innovation.

  10. Future-Proofing: Invest in skills that are in high demand and essential for the future of business, as organizations increasingly rely on data analytics to inform their strategies and operations.

Why SKILLFLOOR ?

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Syllabus

Overview of Business Analytics: Definition, scope, and importance of business analytics in decision-making.

Types of Analytics: Descriptive, Predictive, and Prescriptive analytics.

Data in Business Analytics: Understanding data types, sources, and collection methods.

Role of a Business Analyst: Key responsibilities and skills required for business analytics.

Business Intelligence (BI) vs Business Analytics: Differences and how they complement each other.

Applications of Business Analytics: Use cases in various industries (finance, marketing, healthcare, etc.).

Data Cleaning: Handling missing data, outliers, and inconsistencies.

Data Transformation: Normalization, aggregation, and encoding.

Exploratory Data Analysis (EDA): Techniques for summarizing the main characteristics of datasets.

Data Visualization Basics: Introduction to visualization tools (e.g., Excel, Tableau, Power BI).

Creating Effective Visuals: Best practices for charts, graphs, and dashboards.

Communicating Insights with Data: Presenting data-driven insights to stakeholders.

Basic Statistical Concepts: Mean, median, mode, variance, standard deviation.

Probability Theory: Understanding probability distributions and events.

Hypothesis Testing: Significance testing, p-values, and confidence intervals.

Correlation and Regression: Simple and multiple regression analysis for prediction.

ANOVA and Chi-Square Tests: Group comparisons and categorical data analysis.

Statistical Software: Introduction to using software like R or Python for statistical analysis.

Introduction to Machine Learning: Overview of supervised and unsupervised learning.

Classification Algorithms: Decision trees, logistic regression, and k-nearest neighbors (KNN).

Regression Models: Linear and nonlinear regression techniques.

Clustering Techniques: K-means, hierarchical clustering for segmenting data.

Model Evaluation and Validation: Accuracy, precision, recall, and F1 score.

Predictive Modeling Tools: Hands-on with tools like Python (scikit-learn) or R.

Data-Driven Decision Making: How to use analytics to make strategic business decisions.

Case Studies in Business Analytics: Real-world examples from different industries.

Scenario Analysis: Techniques for modeling "what-if" scenarios and forecasting.

Optimizing Business Processes: Using analytics to improve operational efficiency.

Text Analytics and Sentiment Analysis: Basics of analyzing unstructured data from sources like social media.

Data Ethics and Privacy: Understanding data governance, privacy laws, and ethical considerations.

Capstone Project Introduction: Explanation of project guidelines and expectations.

Problem Formulation and Data Collection: Selecting a business problem and gathering relevant data.

Model Building and Analysis: Applying analytics methods learned in the course to solve the problem.

Presentation of Results: How to effectively communicate your analysis and findings.

Final Exam Review: Key concepts and areas of focus for a certification exam.

Certification Exam: Mock exam and feedback session to prepare for the final certification.

FAQ

A certified business analytics associate is someone who has completed a recognized certification program in business analytics, demonstrating their proficiency in analyzing data to make informed business decisions.

Obtaining certification in business analytics can validate your skills, enhance your credibility, and increase your job prospects in fields where data-driven decision-making is essential.

To become certified, you typically need to complete specific training courses and pass an exam that assesses your knowledge and understanding of business analytics concepts and tools.

Skills such as data analysis, statistical analysis, problem-solving, critical thinking, and proficiency in analytical tools like Excel, SQL, or Tableau are important for business analytics.

With a business analytics certification, you can pursue roles such as business analyst, data analyst, financial analyst, marketing analyst, or operations analyst across various industries.

The time it takes to become certified varies depending on the program and your prior knowledge, but it typically ranges from a few months to a year of study and preparation.

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