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:

• Apply advanced data analysis techniques to interpret and extract insights from complex datasets.

• Create interactive and visually appealing reports and dashboards using Power BI.

• Develop sophisticated data models to support analysis and reporting.

• Apply principles of data governance to ensure data quality, security, and compliance.

• Prepare for and achieve certification as a professional data analyst.

Target Audience:

• Data Analysts.

• Business Intelligence Professionals.

• Data Scientists.

• IT Specialists.

• Professionals Seeking Data Analysis Skills.

Program Outline:

Unit 1:

Introduction to Data Analysis:

• Overview of data analysis and its role in business decision-making.

• Identifying different types of data and their sources.

• Techniques for collecting and preparing data for analysis.

• Conducting Exploratory Data Analysis (EDA) to summarize and visualize data.

• Analyzing real-world examples of successful data analysis projects.

Unit 2:

Fundamentals of Power BI:

• Overview of Power BI and its components.

• Installing and setting up Power BI Desktop.

• Importing data from various sources into Power BI.

• Using Power Query to clean and transform data.

• Creating basic charts and graphs in Power BI.

Unit 3:

Data Preparation and Transformation:

• Handling missing data, outliers, and inconsistencies.

• Advanced data transformation techniques using Power Query.

• Merging and appending data from multiple sources.

• Introduction to DAX and its application in data modeling.

• Real-world examples of effective data preparation.

Unit 4:

Advanced Data Analysis Techniques:

• Applying statistical methods to analyze data.

• Building and evaluating predictive models using historical data.

• Analyzing time-series data to identify trends and patterns.

• Understanding and applying regression techniques for predictive modeling.

• Exploring advanced data analysis projects in various industries.

Unit 5:

Data Modeling in Power BI:

• Understanding data models and their importance.

• Establishing relationships in Power BI models.

• Implementing hierarchies and drill-downs for detailed analysis.

• Using DAX to create calculated columns and measures.

• Analyzing successful data models in business applications.

Unit 6:

Advanced Power BI Visualization:

• Adding and customizing visuals in Power BI.

• Designing interactive dashboards that enhance user experience.

• Sharing and collaborating on Power BI reports and dashboards.

• Integrating Power BI reports into other applications.

• Reviewing advanced visualization techniques in real-world scenarios.

Unit 7:

Data Governance and Security:

• Understanding data governance and its importance.

• Ensuring the accuracy, completeness, and reliability of data.

• Implementing data security measures to protect sensitive information.

• Understanding and adhering to data privacy regulations.

• Exploring examples of effective data governance strategies.

Unit 8:

Reporting and Communication of Results:

• Designing reports that clearly communicate data insights.

• Using data to tell compelling stories and drive decision-making.

• Ensuring clarity, accuracy, and accessibility in report design.

• Using Power BI to distribute reports within an organization.

• Reviewing successful data reporting and communication strategies.

Unit 9:

Exploring and Applying Advanced Data Analysis Tools:

• Exploring the latest tools and techniques in data analysis.

• Using machine learning techniques for data analysis.

• Applying cloud solutions for processing and analyzing large datasets.

• Enhancing visualization skills using advanced tools.

• Analyzing real-world case studies showcasing the impact of modern techniques across various industries.

Unit 10:

Preparing for Data Analyst Certification:

• Overview of the Certification Exam Structure.

• Key Topics and Areas of Focus for the Exam.

• Study Techniques and Exam Strategies.

• Sample Questions and their Potential Answers.

• Developing strategies to pass the certification exam.

• Learning from the experiences of certified professionals.

Note: This program is designed to prepare participants for the certification exam only.