Concepts

This page describes core concepts within Dataworkz platform

• Datasource

  • A data source represents a repository of data that can be categorized as

    • Cloud Object Stores - AWS S3, Azure BLOB Storage, or Google Cloud Storage

    • Relational database - Oracle, MySQL, MSSQL, and more.

    • SaaS Applications - Salesforce, Marketo, Outreach, Pendo to name a few.

    • NoSQL Database - Aerospike, Couchbase, MongoDB

• Workspace

  • A workspace is a logical construct that groups together related collections and datasets. It can be used to organize different datasets and collections of datasets as logically separate units.

• Collection

  • A collection is a grouping of multiple datasets - the format of datasets contained in a collection can vary.

• Datasets

  • Datasets provide the foundation for various data-related tasks which are displayed in a tabular format in Dataworkz. The underlying data might be stored in a relational database, Hive table, cloud data warehouse, or NoSQL database. When you navigate to a dataset in Dataworkz, you’ll be presented with a visual profile of the data with summarized statistics.

• Transformations

  • A transformation is an operation that is performed on a field in a dataset. The transformation operations vary depending on the data type of the field.

• Lineage

• Catalog

• Data Discovery

  • This is the process of connecting with datasets stored in a lake, a cloud data warehouse, a relational/NoSQL database, or a SaaS application like Salesforce.