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Talend Data Catalog
Certified Implementer Exam

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Talend certification exams measure your skills to ensure that you have the knowledge to successfully implement quality projects. Preparation is critical to passing.

This certification exam covers the Talend Data Catalog features. Test coverage also includes the Talend Data Catalog application, the configuration of the application and associated database servers, as well as Talend Data Catalog REST API management.

Certification exam details

Exam content is updated periodically. The number and difficulty of questions may change. The passing score is adjusted to maintain a consistent standard.

Duration: 90 minutes
Number of questions: 54
Passing score: 65%

Recommended experience

  • At least six months of experience using Talend products
  • Knowledge and experience with Talend data cataloging, Business Intelligence(BI) systems metadata management, and model management
  • Knowledge of data transformation processes using BI tools, ETL tools, data stores, data marts, data warehouses, and data models
  • Familiarity with the Talend Data Catalog user interface
  • Knowledge of Talend Data Catalog REST API management

Preparation

To prepare for this certification exam, Talend recommends:

Badge

After passing this certification exam, you are awarded the Talend Data Catalog Certified Implementer badge. To learn more about the criteria to earn this badge, refer to the Talend Academy Badging program page.

Certification exam topics

Overview of Talend Data Catalog

  • Define Data Catalog
  • Define the Business Intelligence (BI) systems
  • Explain the data transformation processes (BI tools, ETL tools, on-premises databases, data stores, data marts, data warehouses, and data models)
  • Explain the architecture of Talend Data Catalog (configuration and diagram, including Remote Metadata Harvesting Agents)
  • Differentiate between data cataloging and metadata management

Harvesting metadata (configuring data models, bridges, profiling, data masking, automating, and versioning)

  • Differentiate between full and incremental harvesting
  • Use a bridge to collect metadata from a data source (data store, Data Integration (DI) tool, BI tool, or business application)
  • Harvest metadata (flat files, database schemas, DI Jobs, Tableau reports, and Qlik)
  • Perform data profiling, classification, labeling, and sampling, including incremental data profiling
  • Manage a metadata repository
  • Automate harvesting and versioning control

Model management (concepts, terms, definitions, custom attributes, and semantic types)

  • Build a business glossary, including bootstrapping a glossary
  • Import and export objects, terminologies, definitions, and relationships
  • Map a business glossary to another model
  • Build and populate a custom model, including importing and exporting metadata
  • Manage relationships in the catalog

Mapping tracing, and analyzing data flow

  • Differentiate between the types of data mappings, including import, export, and forward engineering
  • Manage data mapping for data flow and impact analysis

Managing metamodel and data modeling

  • Describe metamodeling concepts
  • Manage metamodels, including importing and exporting
  • Describe data modeling, including naming standards and versioning
  • Work with data models

Managing data classes

  • Manage data classes, including importing and exporting
  • Describe data classification groups and classification process management

Managing user roles and tasks

  • Define object and global roles, users, groups, role-based access, and security privileges
  • Execute administration tasks (audit, operation logs, system logs, test performance, and user directories)
  • Manage configurations (build, back up, and publish)
  • Manage license updates and cumulative patches
  • Design and manage default dashboards, including customizing widgets

Stitching metadata and reports

  • Stitch objects together in a configuration to define the data flow
  • Build a configuration to connect models
  • Document metadata objects using labels, comments, attachments, and custom attributes
  • Maintain data connections and metadata stitching
  • Define Stitching Reports

Defining semantic lineage

  • Manage semantic mapping for semantic lineage and definition
  • Generate lineage reports
  • Use term documentation, inferred documentation, and mapping

Working collaboratively using social catalog and glossary workflow

  • Orchestrate data curation using social catalog (certifications, endorsements, warnings, watching, and notifications)
  • Manage workflow, including workflow tasks and publications
  • Perform advanced searches using specific parameters
  • Utilize worksheets (create, share, and manage default worksheets)

Accessing Talend Data Catalog REST API

  • Use REST API to run requests on the repository, glossaries, and users
  • Import and export data using the REST API

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