Understanding Deltaray's Data Model
Last updated August 14, 2024
Deltaray employs a flexible and powerful data model that streamlines your data transformation and analysis workflows. This model allows you to work with diverse data sources and easily manipulate your information.
Key Data Model Concepts
- Datasets: A dataset represents a collection of data organized in a tabular structure, similar to a spreadsheet. Each dataset contains rows representing individual records and columns representing attributes or fields.
- Fields: Each column in a dataset represents a field, which holds data of a specific type. Fields can be numerical, text, date, boolean (true/false), or others.
- Schema: The schema defines the structure of a dataset, including the field names, data types, and relationships between fields.
- Transformations: Deltaray offers a wide range of transformations to manipulate your data. These include operations like:
- Cleaning: Removing duplicate entries, handling missing values, and correcting inconsistencies.
- Enrichment: Adding new information to existing data, perhaps by joining data from other sources.
- Feature Engineering: Creating new derived fields or calculations useful for analysis.
- Relationships: Deltaray allows you to define relationships between datasets. For example, you can link a 'customers' dataset to an 'orders' dataset through a common 'customer ID' field. This empowers you to analyze data across multiple tables.
- Views: A view is a virtual representation of a dataset that allows you to:
- Filter: Select specific records based on criteria.
- Aggregate: Summarize data by grouping and analyzing summaries.
- Join: Combine data from multiple datasets based on common fields.
- Transform: Apply transformations to the data before analysis.
Deltaray provides a visual interface for working with your data model, allowing you to drag-and-drop fields, define relationships, and apply transformations with ease. This visual approach makes it intuitive to understand and navigate your data structures.
Was this article helpful?