Course Outline
1 - Identifying Basic Concepts of Data Schemas
- Identify Relational and NonRelational Databases
- 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
3 - Understanding Types and Characteristics of Data
- Understand Types of Data
- 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
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
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
7 - Executing Different Data Manipulation Techniques
- Manipulate Field Data and Create Variables
- 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
9 - Applying Descriptive Statistical Methods
- Use Measures of Central Tendency
- Use Measures of Dispersion
- Use Frequency and Percentages
10 - Describing Key Analysis Techniques
- Get Started with 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
12 - Using the Appropriate Type of Visualization
- Use Basic Visuals
- 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
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
15 - Distinguishing Different Report Types
- Understand How Updates and Timing Affect Reporting
- 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
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
18 - Explaining Master Data Management Concepts
- Explain the Basics of Master Data Management
- Describe Master Data Management Processes
Target Audience
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