Data Analyst (1D0-622)
1 Introduction to Data Analysis
1-1 Definition of Data Analysis
1-2 Importance of Data Analysis in Business
1-3 Types of Data Analysis
1-4 Data Analysis Process
2 Data Collection
2-1 Sources of Data
2-2 Primary vs Secondary Data
2-3 Data Collection Methods
2-4 Data Quality and Bias
3 Data Cleaning and Preprocessing
3-1 Data Cleaning Techniques
3-2 Handling Missing Data
3-3 Data Transformation
3-4 Data Normalization
3-5 Data Integration
4 Exploratory Data Analysis (EDA)
4-1 Descriptive Statistics
4-2 Data Visualization Techniques
4-3 Correlation Analysis
4-4 Outlier Detection
5 Data Modeling
5-1 Introduction to Data Modeling
5-2 Types of Data Models
5-3 Model Evaluation Techniques
5-4 Model Validation
6 Predictive Analytics
6-1 Introduction to Predictive Analytics
6-2 Types of Predictive Models
6-3 Regression Analysis
6-4 Time Series Analysis
6-5 Classification Techniques
7 Data Visualization
7-1 Importance of Data Visualization
7-2 Types of Charts and Graphs
7-3 Tools for Data Visualization
7-4 Dashboard Creation
8 Data Governance and Ethics
8-1 Data Governance Principles
8-2 Data Privacy and Security
8-3 Ethical Considerations in Data Analysis
8-4 Compliance and Regulations
9 Case Studies and Real-World Applications
9-1 Case Study Analysis
9-2 Real-World Data Analysis Projects
9-3 Industry-Specific Applications
10 Certification Exam Preparation
10-1 Exam Overview
10-2 Exam Format and Structure
10-3 Study Tips and Resources
10-4 Practice Questions and Mock Exams
Sources of Data

Sources of Data

Understanding the sources of data is crucial for any data analyst. Data can originate from various sources, each with its own characteristics and implications for analysis. Here are the primary sources of data:

1. Internal Data

Internal Data refers to information that is generated and stored within an organization. This data is typically easier to access and analyze since it is already within the organization's systems.

Examples of internal data include:

2. External Data

External Data comes from sources outside the organization. This data can provide valuable insights but may require more effort to collect and integrate into the analysis.

Examples of external data include:

3. Primary Data

Primary Data is data that is collected directly by the organization for a specific purpose. This data is often more relevant and tailored to the organization's needs.

Examples of primary data include:

4. Secondary Data

Secondary Data is data that has already been collected by someone else and is available for use. This data can be a cost-effective way to gather information but may require careful evaluation for relevance and accuracy.

Examples of secondary data include:

By understanding these sources of data, a data analyst can effectively gather and utilize information to support informed decision-making and strategic planning.