Schema
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Schema

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Article Summary

A data schema in Dataddo Sources is essentially a collection of columns, each with a specific data type and label. This schema serves as the structure that organizes how data is stored and managed within each source.

Fixed Structure of Columns

Once a data schema is set during the source creation in Dataddo, it becomes immutable‚ÄĒmeaning the structure of columns cannot be changed. This design decision is intentional to prevent unwanted domino effects in downstream systems, such as data warehouses, that rely on the consistent structure of the source data.

Supported Data Types

To ensure maximum data type compatibility across a wide range of systems, Dataddo defines data types in a basic, yet highly compatible manner. The platform currently supports four primary data types.

Integer

Stores whole numbers, which can be positive, negative, or zero. Dataddo supports up to 64-bit integers to accommodate a wide range of numerical values and ensure maximum compatibility.

Float

Designed for storing double-precision floating-point numbers with up to 17 significant digits. These can be both positive and negative, and Dataddo supports up to 64-bit floats for maximum compatibility.

String

Utilized for text representation, as well as storing complex types like objects. This data type can comprise a set of characters containing spaces and numbers. Dataddo allows STRING values with up to 16MB capacity to ensure broad compatibility.

Date

Dataddo's DATE type supports datetime information with up to nanosecond precision for maximum compatibility.

Changing Data Types

WARNING!

Changing the data types in your source is not recommended. Proceed at your own risk.

If your source is already connected to a flow to a data warehouse, do not forget to change the data type in your data warehouse as well.

Changing the data types of your source columns in Dataddo is a sensitive operation that can potentially disrupt your data flows or result in data loss. When a data type change is initiated, Dataddo creates a new table in the corresponding database, which could lead to inconsistencies if not handled carefully.

Data Sources - change data type

Risks and Recommendations:

Data Type Mismatch

Always make sure to update the data types in both Dataddo and your destination database to maintain consistency. Failing to do this could result in errors or incomplete data transfers. If your database doesn't allow for editing data types, you'll need to create a new table or a new data flow in Dataddo.

Loss of Precision

Converting from a float to an integer type will round off the decimal places, changing your data values. For example, 5.4 will become 5.

Changing Column Labels

Edit the field names by clicking on the three dots next to your sources and selecting Edit. Navigate to the Data Types tab and rename your field. Please make sure you change the names in your database as well.

Data blending in app - FAQ change column name

FAQ

Can I add a new metric, dimension or attribute to existing source?

No, adding a new metric, dimension, or attribute directly through the source edit is not possible, because it would require changing the schema, which is not possible. You can use the clone function of the source and configure it with different metrics


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