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Symitar

Pipelined Data Sets > Symitar

[!WARNING] This section/project is actively under development. Content may be incomplete or subject to change.

Introduction

The goal of this pipeline is to make the Symitar dataset available in Google BigQuery where it can be queried directly in BigQuery Studio, or integrated into other data warehouses or data analytics platforms.

Scenarios

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Pipelines

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Schedule

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Dataset Types

Symitar pipeline datasets provide the following types of data:

  1. raw - Producer source system raw extract without transformations
  2. cdc - Change data capture indicates this table / view contains all instances of a specific thing and receives all changes to those things, INSERT, UPDATE, or DELETE

Dataset Table Partitioning for Query Performance

Data Hub dataset tables are partitioned by DAY Timestamps. The _raw tables use the extractdate column, and the _cdc tables use the sourceeventdate column, to improve query performance and lower cost of data reads. Recommended to include the timestamp in any where clause to reduce data reads and CPU costs of queries.

SELECT * FROM `<FI_project>.<FI_dataset>.<table>_raw`
WHERE TIMESTAMP_TRUNC(extractdate, DAY) = "2026-09-10"

SELECT * FROM `<FI_project>.<FI_dataset>.<table>_cdc`
WHERE TIMESTAMP_TRUNC(sourceeventdate, DAY) = "2026-09-10"

Topics in this section

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Last updated Tue Sep 15 2026