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    <title>topic Re: Intraday Data for Reporting in Data Warehouse</title>
    <link>https://community.fabric.microsoft.com/t5/Data-Warehouse/Intraday-Data-for-Reporting/m-p/3999854#M1127</link>
    <description>&lt;P&gt;Hi&amp;nbsp;&lt;a href="javascript:void(0)" data-lia-user-mentions="" data-lia-user-uid="702891" data-lia-user-login="Digidank" class="lia-mention lia-mention-user"&gt;Digidank&lt;/a&gt;&amp;nbsp;,&lt;BR /&gt;&lt;BR /&gt;Glad to know that we have answered your query. Please continue using Fabric Community on your further queries.&lt;/P&gt;</description>
    <pubDate>Wed, 19 Jun 2024 09:23:41 GMT</pubDate>
    <dc:creator>Anonymous</dc:creator>
    <dc:date>2024-06-19T09:23:41Z</dc:date>
    <item>
      <title>Intraday Data for Reporting</title>
      <link>https://community.fabric.microsoft.com/t5/Data-Warehouse/Intraday-Data-for-Reporting/m-p/3996239#M1117</link>
      <description>&lt;P&gt;We have 2 sources of data for reporting.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;OL&gt;&lt;LI&gt;Nightly files for historical data&lt;/LI&gt;&lt;LI&gt;Intraday changes on transactional data&lt;/LI&gt;&lt;/OL&gt;&lt;P&gt;The nightly files are the result of the days data with some processing by the source system.&amp;nbsp; We have built out a warehouse of Dimensions and Facts from this using spark jobs for the ELT process.&amp;nbsp; Then transformed into Dimesnion/Facts in the Synapse Data Warehouse.&amp;nbsp; This all is working great.&amp;nbsp;&lt;/P&gt;&lt;P&gt;&lt;BR /&gt;We are not using our Fabric warehouse in production yet as I need to solve the intraday reporting problem first.&amp;nbsp; There is some data that comes in nightly files we process that does not come in the intraday data, but is needed to fully report the intraday data.&amp;nbsp; Currently, we are just writing everything to a regular Azure SQL database for both historical and intraday.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;My question is whether Data Warehouse is capable of keeping up with intraday changes?&amp;nbsp; Will writing those changes as they come in to Data Warehouse be feasible?&amp;nbsp; I presume it all just depends on the Capacity we choose, but wanted some input from y'all more knowledgable on it.&amp;nbsp;&lt;BR /&gt;&lt;BR /&gt;&lt;/P&gt;</description>
      <pubDate>Mon, 17 Jun 2024 13:42:43 GMT</pubDate>
      <guid>https://community.fabric.microsoft.com/t5/Data-Warehouse/Intraday-Data-for-Reporting/m-p/3996239#M1117</guid>
      <dc:creator>Digidank</dc:creator>
      <dc:date>2024-06-17T13:42:43Z</dc:date>
    </item>
    <item>
      <title>Re: Intraday Data for Reporting</title>
      <link>https://community.fabric.microsoft.com/t5/Data-Warehouse/Intraday-Data-for-Reporting/m-p/3997791#M1123</link>
      <description>&lt;P&gt;Hi&amp;nbsp;&lt;a href="javascript:void(0)" data-lia-user-mentions="" data-lia-user-uid="702891" data-lia-user-login="Digidank" class="lia-mention lia-mention-user"&gt;Digidank&lt;/a&gt;&amp;nbsp;,&lt;BR /&gt;&lt;BR /&gt;Thanks for using Fabric Community. &lt;BR /&gt;Synapse Data Warehouse (DW) can definitely handle your intraday data updates. It's designed for large-scale data ingestion and frequent updates, so capacity shouldn't be a major obstacle. Here's how we can tackle both nightly and intraday data:&lt;BR /&gt;&lt;BR /&gt;&lt;/P&gt;
&lt;P&gt;&lt;STRONG&gt;1. Nightly Data:&lt;/STRONG&gt;&lt;/P&gt;
&lt;P&gt;Keep using your existing Spark jobs to process and load nightly data files into Synapse DW. This is a familiar and efficient approach.&lt;BR /&gt;&lt;BR /&gt;&lt;/P&gt;
&lt;P&gt;&lt;STRONG&gt;2. Intraday Updates:&lt;/STRONG&gt;&lt;/P&gt;
&lt;P&gt;Break down your intraday data into smaller batches and ingest them into Synapse DW throughout the day. This provides near real-time updates for your reports.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;STRONG&gt;Important Note:&lt;/STRONG&gt;&lt;/P&gt;
&lt;P&gt;While Fabric notebooks are a valuable tool for data exploration and analysis, they currently cannot directly load data into the Data Warehouse. We recommend using Data Factory pipelines for this purpose.&lt;BR /&gt;&lt;BR /&gt;&lt;/P&gt;
&lt;P&gt;&lt;STRONG&gt;Additional Tips:&lt;/STRONG&gt;&lt;/P&gt;
&lt;P&gt;Partition your tables in Synapse DW to optimize query performance for both historical and intraday data.&lt;/P&gt;
&lt;P&gt;Consider using materialized views for frequently used aggregations on intraday data to further improve reporting speed.&lt;BR /&gt;&lt;BR /&gt;Docs to refer -&lt;BR /&gt;&lt;A href="https://learn.microsoft.com/en-us/fabric/data-warehouse/ingest-data" target="_blank"&gt;Ingesting data into the warehouse - Microsoft Fabric | Microsoft Learn&lt;/A&gt;&lt;BR /&gt;&lt;BR /&gt;Hope this is helpful. Please do let me know incase of further queries.&lt;/P&gt;</description>
      <pubDate>Tue, 18 Jun 2024 08:22:45 GMT</pubDate>
      <guid>https://community.fabric.microsoft.com/t5/Data-Warehouse/Intraday-Data-for-Reporting/m-p/3997791#M1123</guid>
      <dc:creator>Anonymous</dc:creator>
      <dc:date>2024-06-18T08:22:45Z</dc:date>
    </item>
    <item>
      <title>Re: Intraday Data for Reporting</title>
      <link>https://community.fabric.microsoft.com/t5/Data-Warehouse/Intraday-Data-for-Reporting/m-p/3998402#M1125</link>
      <description>Perfect! Thanks, that was the answer i was hoping to hear. I have already started work on the intraday and have a few things updating quickly.</description>
      <pubDate>Tue, 18 Jun 2024 14:03:33 GMT</pubDate>
      <guid>https://community.fabric.microsoft.com/t5/Data-Warehouse/Intraday-Data-for-Reporting/m-p/3998402#M1125</guid>
      <dc:creator>Digidank</dc:creator>
      <dc:date>2024-06-18T14:03:33Z</dc:date>
    </item>
    <item>
      <title>Re: Intraday Data for Reporting</title>
      <link>https://community.fabric.microsoft.com/t5/Data-Warehouse/Intraday-Data-for-Reporting/m-p/3999854#M1127</link>
      <description>&lt;P&gt;Hi&amp;nbsp;&lt;a href="javascript:void(0)" data-lia-user-mentions="" data-lia-user-uid="702891" data-lia-user-login="Digidank" class="lia-mention lia-mention-user"&gt;Digidank&lt;/a&gt;&amp;nbsp;,&lt;BR /&gt;&lt;BR /&gt;Glad to know that we have answered your query. Please continue using Fabric Community on your further queries.&lt;/P&gt;</description>
      <pubDate>Wed, 19 Jun 2024 09:23:41 GMT</pubDate>
      <guid>https://community.fabric.microsoft.com/t5/Data-Warehouse/Intraday-Data-for-Reporting/m-p/3999854#M1127</guid>
      <dc:creator>Anonymous</dc:creator>
      <dc:date>2024-06-19T09:23:41Z</dc:date>
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