Certified Data Analyst Professional - Tableau Exam Analytics Institute

Overview

Certified Data Analyst Professional - Tableau

Duration 1 Hour

Fee $39.99 ~~$60.99~~

Exam Guidelines: View Buy Now

Exam Guidelines and Procedures

Thank you for choosing Analytics Institute for your professional certification exam. To ensure a fair and secure examination process, we have implemented the following guidelines and procedures. Please carefully review the information below before taking your exam.

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5. Exam Timing and Question Marking: All exams are timed, and the duration will be clearly specified before you begin. Please manage your time effectively to complete all the questions within the allotted time. You will have the option to mark questions for later review if needed.

6. Exam Result and Certification: Upon completing the exam, your results will be available immediately. If you pass the exam, you will be able to generate a digital certificate, which can be downloaded and shared. The certificate will be a testament to your successful completion of the certification and can be used to showcase your expertise. Additionally, you will have the privilege to use our official logo to demonstrate your achievement.

Please note that these guidelines and procedures are in place to ensure a fair and reliable assessment process. We take exam integrity seriously and strive to maintain the highest standards. By adhering to these guidelines, you contribute to the credibility and value of your certification.

If you have any questions or require further assistance, please don't hesitate to contact our support team. Best of luck with your exam, and we wish you success in your professional journey!

Description:

Certified Data Analyst Professional Certification - Tableau, R, Python, SQL, Excel and Core Skills

The Certified Data Analyst Professional (CDAP) certification offered by Analytics Institute is a comprehensive program designed to validate the skills and knowledge required to excel in the field of data analysis. This certification equips professionals with the expertise to collect, analyze, and interpret complex data sets to uncover valuable insights and drive data-informed decision-making within organizations.

Benefits of Certified Data Analyst Professional Certification:

Advanced Data Analysis Skills: The CDAP certification program is designed to enhance your data analysis skills, enabling you to confidently navigate through vast amounts of data and derive meaningful insights. You will gain expertise in various analytical techniques and tools, empowering you to make data-driven recommendations and solve complex business problems.
Industry Recognition: By earning the CDAP certification, you establish yourself as a highly skilled and knowledgeable data analyst. This industry recognition enhances your professional credibility and distinguishes you as a sought-after expert in the field, increasing your career prospects and earning potential.
Efficient Decision-Making: As a certified data analyst professional, you develop the ability to make informed decisions based on data-driven insights. You learn how to identify trends, patterns, and correlations within data, enabling you to provide valuable recommendations that drive organizational success.

Topics Covered in the Certified Data Analyst Professional Exam: The CDAP certification exam covers a wide range of topics related to data analysis, ensuring a comprehensive understanding of key concepts and techniques. The exam tests your knowledge and proficiency in the following areas:

Prepare to demonstrate your expertise in fundamental data analysis and database concepts with this certification. The exam covers a range of topics including data analysis methodologies, database fundamentals, and proficiency in Excel, SQL, R, Python and Tableau.

Format: Multiple Choice
Duration: 60 minutes
Number of Questions: 55
Passing Score: 80%

Exam Topics

1. Data Analysis Fundamentals

Data Analysis Process and Methodology
Types of Data Analysis: Descriptive, Diagnostic, Predictive, Prescriptive
Data Visualization Techniques
Role and Responsibilities of a Data Analyst
Key Skills and Tools for Data Analysts

2. Database Fundamentals

Database Concepts
Database Architecture
Database Security
Data Cleaning and Preparation
Data Collection Methods
Data Modeling
Data Integrity
Database design patterns

3. Excel for Data Analysis

Basic Excel functions
Data validation and data protection
Charts and graph creation
Conditional formatting
Pivot Tables and Pivot Charts
Cell formatting and styles
Data sorting and filtering
Data analysis and visualization
Text functions
Data de-duplication
Grouping and outlining data
Freeze panes and worksheet protection
Keyboard shortcuts
Data trends and time analysis

4. SQL for Data Analysis

Normalization and De-normalization
SQL Keywords and Basic Operations
SQL Clauses
SQL Operators
Aggregate Functions
Joins
Indexes
Database Constraints
Transactions
Temporary Tables
Views
Subqueries
SQL Data Types
SQL Functions

5. Tableau for Data Analysis

Data Connection and Integration
Data Types and Structures
Data Blending and Joins
Data Visualization Techniques
Dashboard Creation and Interactivity
Data Analysis, Calculation and Functions
Filtering and Sorting Data
Advanced Features and Tools - Parameters, Handling nulls, data interpretation, stories, custom SQL, and extracts
Publishing and Sharing

6. Data Warehousing Concepts

Purpose and Benefits to Data Warehousing
ETL (Extract, Transform, Load) Processes
Data Warehouse Architecture- Star Schema, Snowflake Schema
Data Modeling for Data Warehouses - Dimensional Modeling, Fact and Dimension Tables
Data Governance and Privacy

7. R Language

Data Reading and Writing: Reading CSV Files, Data Export
Data Manipulation and Transformation: dplyr Package, Filtering and Aggregation, Data Transformation, Data Reshaping, Joining and Merging Data Frames, Handling Large Datasets
Data Visualization: ggplot2 Package, Data Visualization Techniques
Statistical Analysis and Model Building: Statistical Analysis, Model Building
Data Cleaning and Handling: Data Cleaning, String Manipulation, Working with Dates and Times
Functions and Programming: apply() Function, Function Writing
Advanced Topics: Parallel Computing, R Markdown
Specialized Data Techniques: Time Series Analysis

8. Python

Data Manipulation and Analysis: Pandas Library, Reading CSV Files, DataFrame Operations, Data Cleaning and Transformation, Advanced DataFrame Merging, Data Aggregation and Grouping, Handling Missing Data, Data Visualization with Pandas, Time Series Analysis
Python Programming Concepts: Lambda Functions, String Methods, Class Initialization, Exception Handling, Date and Time Handling, Python Data Structures, Object-Oriented Programming in Python, Decorators and Higher-Order Functions, Regular Expressions
File Operations and Performance: File Operations, File I/O Operations, Performance Optimization
Testing and Libraries: Unit Testing in Python, Python Libraries for Data Analysis
Advanced Topics: DataFrame Indexing and Selection

By successfully passing the CDAP certification exam, you demonstrate your proficiency in these areas, positioning yourself as a skilled data analyst capable of extracting actionable insights and driving data-centric decision-making within organizations.

Note: The specific topics mentioned above are for illustrative purposes. The actual topics covered in the Certified Data Analyst Professional exam may vary based on the curriculum and focus of your analytics institute.

Passing this exam is required to earn the certification.