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Information Technology
CompTIA Data+ (DA0-001)
What You'll Learn
CompTIA Data+ validates that you have the skills required to facilitate data-driven business decisions, including:
Mining data
Manipulating data
Visualizing and reporting data
Applying basic statistical methods
Analyzing complex datasets while adhering to governance and quality standards throughout the entire data life cycle
Description
This course teaches you the knowledge and skills required to transform business requirements in support of data-driven decisions by mining data, manipulating data, applying basic statistical methods, and analyzing complex data sets while adhering to governance and quality standards throughout the entire data lifecycle. In addition, this course will help prepare candidates to take the CompTIA Data+ certification exam.
Who Should Attend
Data+ is an ideal certification for not only data-specific careers, but other career paths that can benefit from analytics processes and data analytics knowledge, such as marketing specialists, financial analysts, human resource analysts or clinical health care analysts. This course is suited for roles such as:
Data Analyst
Business Intelligence Analyst
Reporting Analyst
Marketing Analyst
Clinical Analyst
Business Data Analyst
Operations Analyst
Course Overview
This course teaches you the knowledge and skills required to transform business requirements in support of data-driven decisions by mining data, manipulating data, applying basic statistical methods, and analyzing complex data sets while adhering to governance and quality standards throughout the entire data lifecycle. In addition, this course will help prepare candidates to take the CompTIA Data+ certification exam.
Course Prerequisites
No results found.
Course Agenda
18 Title
Course Agenda
1
Identifying Basic Concepts of Data Schemas
Identify Relational and NonRelational Databases
Understand the Way We Use Tables ,Primary Keys, and Normalization
Understand the Way We Use Tables ,Primary Keys, and Normalization
2
Understanding Different Data Systems
Describe Types of Data Processing and Storage Systems
Explain How Data Changes
Explain How Data Changes
3
Understanding Types and Characteristics of Data
Understand Types of Data
Break Down the Field Data Types
Break Down the Field Data Types
4
Comparing and Contrasting Different Data Structures, Formats, and Markup Languages
Differentiate between Structured Data and Unstructured Data
Recognize Different File Formats
Understand the Different Code Languages Used for Data
Recognize Different File Formats
Understand the Different Code Languages Used for Data
5
Explaining Data Integration and Collection Methods
Understand the Processes of Extracting, Transforming, and Loading Data
Explain API/Web Scraping and Other Collection Methods
Collect and Use Public and Publicly Available Data
Use and Collect Survey Data
Explain API/Web Scraping and Other Collection Methods
Collect and Use Public and Publicly Available Data
Use and Collect Survey Data
6
Identifying Common Reasons for Cleansing and Profiling Data
Learn to Profile Data
Address Redundant, Duplicated, and Unnecessary Data
Work with Missing Values
Address Invalid Data
Convert Data to Meet Specifications
Address Redundant, Duplicated, and Unnecessary Data
Work with Missing Values
Address Invalid Data
Convert Data to Meet Specifications
7
Executing Different Data Manipulation Techniques
Manipulate Field Data and Create Variables
Transpose and Append Data
Query Data
Transpose and Append Data
Query Data
8
Explaining Common Techniques for Data Manipulation and Optimization
Use Functions to Manipulate Data
Use Common Techniques for Query Optimization
Use Common Techniques for Query Optimization
9
Applying Descriptive Statistical Methods
Use Measures of Central Tendency
Use Measures of Dispersion
Use Frequency and Percentages
Use Measures of Dispersion
Use Frequency and Percentages
10
Describing Key Analysis Techniques
Get Started with Analysis
Recognize Types of Analysis
Recognize Types of Analysis
11
Understanding the Use of Different Statistical Methods
Understand the Importance of Statistical Tests
Break Down the Hypothesis Test
Understand Tests and Methods to Determine Relationships Between Variables
Break Down the Hypothesis Test
Understand Tests and Methods to Determine Relationships Between Variables
12
Using the Appropriate Type of Visualization
Use Basic Visuals
Build Advanced Visuals
Build Maps with Geographical Data
Use Visuals to Tell a Story
Build Advanced Visuals
Build Maps with Geographical Data
Use Visuals to Tell a Story
13
Expressing Business Requirements in a Report Format
Consider Audience Needs When Developing a Report
Describe Data Source Considerations For Reporting
Describe Considerations for Delivering Reports and Dashboards
Develop Reports or Dashboards
Understand Ways to Sort and Filter Data
Describe Data Source Considerations For Reporting
Describe Considerations for Delivering Reports and Dashboards
Develop Reports or Dashboards
Understand Ways to Sort and Filter Data
14
Designing Components for Reports and Dashboards
Design Elements for Reports and Dashboards
Utilize Standard Elements
Creating a Narrative and Other Written Elements
Understand Deployment Considerations
Utilize Standard Elements
Creating a Narrative and Other Written Elements
Understand Deployment Considerations
15
Distinguishing Different Report Types
Understand How Updates and Timing Affect Reporting
Differentiate Between Types of Reports
Differentiate Between Types of Reports
16
Summarizing the Importance of Data Governance
Define Data Governance
Understand Access Requirements and Policies
Understand Security Requirements
Understand Entity Relationship Requirements
Understand Access Requirements and Policies
Understand Security Requirements
Understand Entity Relationship Requirements
17
Applying Quality Control to Data
Describe Characteristics, Rules, and Metrics of Data Quality
Identify Reasons to Quality Check Data and Methods of Data Validation
Identify Reasons to Quality Check Data and Methods of Data Validation
18
Explaining Master Data Management Concepts
Explain the Basics of Master Data Management
Describe Master Data Management Processes
Describe Master Data Management Processes