SkillFloor’s Business Analyst Course in Gorakhpur is a comprehensive program tailored for both beginners and professionals aiming to excel in business analytics and make informed, data-driven decisions. The course covers essential topics such as data analysis, statistical techniques, and proficiency in tools like Excel, SQL, and Power BI. Through hands-on practice and real-world examples, students will learn to extract meaningful insights from data and effectively communicate their findings. This course is perfect for individuals seeking to advance in business strategy, operations, or consulting, addressing the rising demand for skilled business analysts.
SkillFloor offers an advanced Business Analytics Course in Gorakhpur, designed for those seeking to develop strong technical and analytical skills. This program covers key areas like predictive modeling, machine learning, big data analysis, and tools such as Hadoop and Python. Students will gain expertise in managing large datasets, making data-driven predictions, and solving complex business problems. With a focus on practical applications, this course is ideal for professionals or graduates pursuing careers in data analytics, business intelligence, or data science, equipping them with the skills needed to succeed in today’s data-centric business world.
₹60,000
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The Business Analytics Certification in Gorakhpur is designed to equip participants with essential skills in data analysis and business intelligence. The program covers key topics such as data visualization, statistical analysis, and the use of popular tools like Tableau and Power BI. Participants will learn how to analyze data efficiently and make informed decisions based on their insights. With a focus on practical training and hands-on projects, students will gain real-world experience in applying analytics techniques. Upon completion, participants will receive a certification that validates their expertise in analytics, providing a competitive advantage in the job market.
Real-World Applications: The course focuses on solving actual business problems using data. Students work on live projects, applying their knowledge to practical scenarios, preparing them for future job roles.
Networking Opportunities: Build a strong professional network by connecting with instructors, peers, and industry professionals. SkillFloor also organizes events that allow students to collaborate with industry experts.
Flexible Learning Environment: With both online and classroom options, SkillFloor enables you to learn at your own pace. Choose the learning format that best fits your schedule and lifestyle.
Strong Career Prospects: Completing a business analysis or data analytics course opens doors to lucrative job opportunities with growth potential. These roles are essential in today’s data-driven world.
High Demand for Business Analysts: As businesses increasingly rely on data-driven decisions, the demand for skilled business analysts and data analysts continues to grow, creating numerous job opportunities across industries like finance, healthcare, and technology.
Industry-Relevant Skills: Learn in-demand tools such as Excel, SQL, Power BI, and Tableau, and develop vital skills in data visualization and statistical analysis. These skills significantly boost your employability.
Comprehensive Training: The program offers a balanced mix of theoretical knowledge and practical experience, ensuring you’re equipped to tackle real-world challenges in business analysis and decision-making.
Customized for All Levels: Whether you're a beginner or looking to enhance your skills, SkillFloor’s courses cater to learners at all levels, with a flexible learning approach to suit diverse needs.
Affordable Pricing: SkillFloor offers high-quality training at affordable rates, with flexible payment options to make professional development accessible and valuable for all learners.
- Overview of data analysis and its importance in business
- Types of analytics: Descriptive, Predictive, Prescriptive
- Role of data in decision-making processes
- Introduction to common tools: Tableau, PowerBI, Excel
- Ethical considerations in data collection and analysis
- Data sources: Primary and secondary data
- Data collection methods (surveys, web scraping, databases)
- Data cleaning techniques (handling missing values, outliers)
- Data transformation and feature engineering
- Data storage concepts (structured vs. unstructured data)
- Descriptive statistics: Mean, median, mode
- Data visualization basics (histograms, scatter plots)
- Identifying data patterns and trends
- Outlier detection and handling methods
- Correlation and causation analysis
- Inferential statistics and probability theory
- Hypothesis testing (t-tests, chi-square tests, ANOVA)
- Measures of central tendency and variability
- Confidence intervals and margin of error
- Regression analysis: Linear and logistic regression
- Principles of effective data visualization
- Types of charts and their uses (bar, line, pie, heatmaps)
- Designing dashboards for different audiences
- Interactive visualization techniques
- Data storytelling for impactful presentations
- Time series analysis and forecasting methods
- Clustering and segmentation analysis
- Decision trees and classification techniques
- Introduction to machine learning in business analytics
- Model evaluation and selection
- Basics of SQL for data manipulation
- Creating databases and relationships
- Aggregating data with SQL (GROUP BY, JOIN)
- Data modeling for business intelligence (star and snowflake schemas)
- Case study: Building a business model with SQL
- Connecting and preparing data in Tableau
- Creating basic visualizations (charts, maps)
- Advanced Tableau functions (LOD calculations, table calculations)
- Building interactive dashboards and stories
- Publishing and sharing visualizations on Tableau Server/Online
- Introduction to PowerBI workspace and components
- Data import and transformation with Power Query
- Data modeling and relationships in PowerBI
- Creating and customizing visualizations
- Publishing and collaborating on PowerBI Service
- Selecting a real-world dataset for analysis
- Defining business questions and objectives
- Conducting data analysis and visualization
- Presenting findings in a comprehensive dashboard
- Peer review and feedback on project