Talend Data Quality

1. Data Profiling: Analyzes data to understand its quality and completeness.

2. Data Cleansing: Identifies and corrects errors, duplicates, and inconsistencies.

3. Data Standardization: Ensures consistency by standardizing formats and values.

4. Data Enrichment: Enhances data quality with additional information from external sources.

Before learning Talend Data Quality, it's beneficial to have the following skills:

1. Data Management: Understanding of basic data management principles and concepts.

2. Data Integration: Familiarity with data integration tools and processes for moving and transforming data.

3. Data Analysis: Ability to analyze and interpret data to identify patterns, trends, and anomalies.

4. Database Knowledge: Basic knowledge of databases and SQL for querying and manipulating data.

By learning Talend Data Quality, you gain skills in:

1. Data Profiling: Ability to analyze data to understand its quality, completeness, and structure.

2. Data Cleansing: Proficiency in identifying and correcting errors, duplicates, and inconsistencies in data.

3. Data Standardization: Skills to standardize data formats, values, and representations for consistency.

4. Data Enrichment: Capability to enhance data quality by enriching it with additional information from external sources.