Core features - 6.1

Talend Real-time Big Data Platform Studio User Guide

Talend Real-Time Big Data Platform
Data Quality and Preparation
Design and Development
Talend Studio

This section describes basic features of Talend data profiling solution.

Metadata repository

Using Talend data quality, you can connect to data sources to analyze their structure (catalogs, schemas and tables), and stores the description of their metadata in its metadata repository. You can then use this metadata to set up metrics and indicators.

For more information, see Before you begin profiling data.

One specific feature of interest as well is a report database where you can keep a history of created reports and share results among team members. For more information, see Setting up a distant database.

Patterns and indicators

Patterns are sets of strings against which you can define the content, structure and quality of high complex data. The Profiling perspective of the studio lists two types of patterns: regular expressions, which are predefined regular patterns, and SQL patterns which are the patterns you add using LIKE clauses.

For more information about patterns, see Patterns.

Indicators are the results achieved through the implementation of different patterns. They can represent the results of data matching and different other data-related operations. The Profiling perspective of the studio lists two types of indicators: system indicators, a list of predefined indicators, and user-defined indicators, a list of those defined by the user.

For more information about indicators, see Indicators.