Working as an analytics engineer, I have developed a systematic method for technical data validation, which encompasses three steps: checking level of detail, columns and sources, and data type. I work with a datastack that includes #snowflake , #dbt , and #tableau , but the same principles can be applied to other tools as well.

Timestamps
0:00 Intro

LEVEL OF DETAIL
0:15 Validate the Level of Detail of a dataset
0:36 Summarize the Level of Detail needed in one sentence
1:17 How to check if rows are unique
1:36 What to do if aggregations are not at the lowest level of detail

COLUMNS AND SOURCES
2:07 Validate the Columns and Sourcesof a dataset

DATA TYPE
2:19 Validate the Data Type of columns in a dataset

свернуть