Refine the data¶

The purpose of a data warehouse is to archive data and refine it in order ease usage. Refining can be blending of multiple data sources, fixing some data source issues and/or apply some business rules.

Refining can also be modeling the data using a star schema to make it faster to manipulate and easier to understand.

For this tutorial, we will just define some tables that will be used for reporting later. SQL queries will therefore stay simple, basically some non-complex SQL queries.

All those tables will be stored in the module earthquake stored in the datawarehouse declared previously.

<module name="earthquake" datastore="dw">
  <!-- module tables goes here -->
</modules>

For instance, the daily_stats table aggregate earthquakes by day, over the last 30 days, and count the number of earthquake, find the maimal and average earthquake magnitude. I.e, the following query :

select cast("time" as date) as "date", count(*) as "earthquake_count", max("mag") as "max_magnitude",
  avg("mag") as "avg_magnitude"
from "archive_web"."earthquake"
group by cast("time" as date)
order by cast("time" as date) desc
limit 30

This query will be embedded in a :source element which has a type query.

You can find below the full specification of the module earthquake.

<!-- Model some (simple) stats tables for reporting -->
<module name="earthquake" datastore="dw">
  <table name="daily_stats">
    <source type="query">
      select cast("time" as date) as "date", count(*) as "earthquake_count", max("mag") as "max_magnitude",
        avg("mag") as "avg_magnitude"
      from "archive_web"."earthquake"
      group by cast("time" as date)
      order by cast("time" as date) desc
      limit 30
    </source>
  </table>

  <table name="weekly_stats">
    <source type="query">
      select to_char(cast("time" as date), 'IYYY-IW') as "date", count(*) as "earthquake_count", max("mag") as "max_magnitude",
        avg("mag") as "avg_magnitude"
      from "archive_web"."earthquake"
      group by to_char(cast("time" as date), 'IYYY-IW')
      order by to_char(cast("time" as date), 'IYYY-IW') desc
      limit 14
    </source>
  </table>

  <table name="last_big_ones">
    <source type="query">
      select "time", "mag", "latitude", "longitude", "place"
      from "archive_web"."earthquake"
      order by "mag" desc
      limit 7
    </source>
  </table>

  <table name="mag_vs_depth_corr" type="xlsx" location="earthquake.xlsx"
    sheet="DATA - mag vs depth" colStart="A" rowStart="2">
    <source type="query">
      select "mag", "depth"
      from "archive_web"."earthquake"
      order by "time" desc
      limit 60
    </source>
  </table>
</module>

Now that the data is prepared for reporting, we can get to the reporting phase.