Magical plumbing for effective change dates
We discuss how to handle change data in a hands-off filedrop process. We use the ingestion timestamp as a simple proxy for the effective date of each record, allowing us to version each day’s data. For files with multiple change records, we scan all columns to identify and rank potential effective date columns. We then pass this information to an automated rule, ensuring it gets applied as we load the data. This process enables us to efficiently handle change data, track data flow, and manage multiple changes in an automated way.
Unveiling the Secrets of Data Quality Metrics for Data Magicians: Ensuring Data Warehouse Excellence
Data quality metrics are crucial indicators in a data warehouse that measure the accuracy, completeness, consistency, timeliness, and uniqueness of data. These metrics help organisations ensure their data is reliable and fit for use, thus driving effective decision-making and analytics
Amplifying Your Data’s Value with Business Context
The AgileData Context feature enhances data understanding, facilitates effective decision-making, and preserves corporate knowledge by adding essential business context to data. This feature streamlines communication, improves data governance, and ultimately, maximises the value of your data, making it a powerful asset for your business.
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