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Adding metric view demo notebook to retail c360 (#202)
* metric view demo notebooks added * metric view demo notebooks added * metric view demo notebooks added * metric view demo notebook added to c360 * metric view demo notebook added to c360 * metric view demo notebook added to c360 * metric view demo notebook added to c360 --------- Co-authored-by: mohanab-db <121183444+mohanab-db@users.noreply.github.com>
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demo-retail/lakehouse-retail-c360/01-Data-ingestion/01.3-DLT-churn-python.py

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# MAGIC
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# MAGIC Now that these tables are available in our Lakehouse, let's review how we can share them with the Data Scientists and Data Analysts teams.
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# MAGIC
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# MAGIC Jump to the [Governance with Unity Catalog notebook]($../00-churn-introduction-lakehouse) or [Go back to the introduction]($../00-churn-introduction-lakehouse)
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# MAGIC Jump to the [Governance with Unity Catalog notebook]($../02-Data-governance/02.1-UC-data-governance-security-churn) or [Go back to the introduction]($../00-churn-introduction-lakehouse)
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# COMMAND ----------
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demo-retail/lakehouse-retail-c360/02-Data-governance/02-UC-data-governance-security-churn.sql renamed to demo-retail/lakehouse-retail-c360/02-Data-governance/02.1-UC-data-governance-security-churn.sql

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-- COMMAND ----------
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-- MAGIC %md
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-- MAGIC # Next: Start building analysis with Databricks SQL
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-- MAGIC # Next: Start building semantic layer with Databricks SQL
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-- MAGIC
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-- MAGIC Now that these tables are available in our Lakehouse and secured, let's see how our Data Analyst team can start leveraging them to run BI workloads
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-- MAGIC Now that these tables are available in our Lakehouse and secured, let's see how we can define our business semantics using metric views.
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-- MAGIC
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-- MAGIC Jump to the [BI / Data warehousing notebook]($../03-BI-data-warehousing/03-BI-Datawarehousing) or [Go back to the introduction]($../00-churn-introduction-lakehouse)
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-- MAGIC Jump to the [UC / Metric views notebook]($02.2-UC-metric-views) or [Go back to the introduction]($../00-churn-introduction-lakehouse)

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