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Certified Data Analyst Training Program
Overview:
Introduction:
This program is tailored specifically to prepare participants for the certification exam. It provides a thorough grounding in the key skills and knowledge required for success in data analysis. Participants will gain hands-on experience with tools such as Power BI, learning to extract, analyze, and visualize data effectively to support informed, data-driven business decisions.
Program Objectives:
By the end of this program, participants will be able to:
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Apply advanced data analysis techniques to interpret and extract insights from complex datasets.
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Create interactive and visually appealing reports and dashboards using Power BI.
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Develop sophisticated data models to support analysis and reporting.
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Apply principles of data governance to ensure data quality, security, and compliance.
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Prepare for and achieve certification as a professional data analyst.
Target Audience:
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Data Analysts.
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Business Intelligence Professionals.
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Data Scientists.
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IT Specialists.
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Professionals Seeking Data Analysis Skills.
Program Outline:
Unit 1:
Introduction to Data Analysis:
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Overview of data analysis and its role in business decision-making.
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Identifying different types of data and their sources.
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Techniques for collecting and preparing data for analysis.
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Conducting Exploratory Data Analysis (EDA) to summarize and visualize data.
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Analyzing real-world examples of successful data analysis projects.
Unit 2:
Fundamentals of Power BI:
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Overview of Power BI and its components.
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Installing and setting up Power BI Desktop.
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Importing data from various sources into Power BI.
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Using Power Query to clean and transform data.
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Creating basic charts and graphs in Power BI.
Unit 3:
Data Preparation and Transformation:
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Handling missing data, outliers, and inconsistencies.
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Advanced data transformation techniques using Power Query.
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Merging and appending data from multiple sources.
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Introduction to DAX and its application in data modeling.
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Real-world examples of effective data preparation.
Unit 4:
Advanced Data Analysis Techniques:
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Applying statistical methods to analyze data.
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Building and evaluating predictive models using historical data.
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Analyzing time-series data to identify trends and patterns.
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Understanding and applying regression techniques for predictive modeling.
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Exploring advanced data analysis projects in various industries.
Unit 5:
Data Modeling in Power BI:
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Understanding data models and their importance.
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Establishing relationships in Power BI models.
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Implementing hierarchies and drill-downs for detailed analysis.
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Using DAX to create calculated columns and measures.
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Analyzing successful data models in business applications.
Unit 6:
Advanced Power BI Visualization:
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Adding and customizing visuals in Power BI.
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Designing interactive dashboards that enhance user experience.
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Sharing and collaborating on Power BI reports and dashboards.
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Integrating Power BI reports into other applications.
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Reviewing advanced visualization techniques in real-world scenarios.
Unit 7:
Data Governance and Security:
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Understanding data governance and its importance.
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Ensuring the accuracy, completeness, and reliability of data.
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Implementing data security measures to protect sensitive information.
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Understanding and adhering to data privacy regulations.
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Exploring examples of effective data governance strategies.
Unit 8:
Reporting and Communication of Results:
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Designing reports that clearly communicate data insights.
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Using data to tell compelling stories and drive decision-making.
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Ensuring clarity, accuracy, and accessibility in report design.
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Using Power BI to distribute reports within an organization.
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Reviewing successful data reporting and communication strategies.
Unit 9:
Exploring and Applying Advanced Data Analysis Tools:
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Exploring the latest tools and techniques in data analysis.
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Using machine learning techniques for data analysis.
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Applying cloud solutions for processing and analyzing large datasets.
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Enhancing visualization skills using advanced tools.
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Analyzing real-world case studies showcasing the impact of modern techniques across various industries.
Unit 10:
Preparing for Data Analyst Certification:
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Overview of the Certification Exam Structure.
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Key Topics and Areas of Focus for the Exam.
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Study Techniques and Exam Strategies.
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Sample Questions and their Potential Answers.
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Developing strategies to pass the certification exam.
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Learning from the experiences of certified professionals.