Working principles of data quality - 6.2

Talend Real-time Big Data Platform Studio User Guide

English (United States)
Talend Real-Time Big Data Platform
Talend Studio
Data Quality and Preparation
Design and Development

From the Profiling perspective of the studio, you can examine the data available in different data sources and collect statistics and information about this data.

A typical sequence of profiling data using the studio involves the following steps:

  1. Connecting to a data source including databases and delimited files in order to be able to access the tables and columns on which you want to define and execute analyses. For more information, see Setting up connections to data sources.

  2. Defining any of the available data quality analyses including database content analysis, column analysis, table analysis, redundancy analysis, correlation analysis, etc. These analyses will carry out data profiling processes that will define the content, structure and quality of highly complex data structures. The analysis results will be displayed graphically next to each of the analysis editors, or in more detail in the Analysis Results view.


    While you can use all analyses types to profile data in databases, you can only use Column Analysis and Column Set Analysis to profile data in delimited files.

  3. Generating reports from different analyses and historize them in a distant database. These reports allow to compare current and historical statistics to determine the improvement or degradation of data. For more information, see Reports.

  4. Access different analytical tools that will allow you to explore and monitor the reports generated in the studio . For more information about the Portal, see the Talend Data Quality Portal User and Administrator Guide. For more information about installing the Portal, see the Talend Installation Guide.

Your studio provides you with lock modes that allow you, if you are the first user to open an item, to lock that item and thus have the "read and write" rights. All other users who try to open the same item simultaneously will have a read-only access. For more information, see Working collaboratively on data quality items.