<?xml version="1.0" encoding="UTF-8"?>
<rss xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:taxo="http://purl.org/rss/1.0/modules/taxonomy/" version="2.0">
  <channel>
    <title>topic What problems does the “modern data stack” actually solve that have not been solved already? in Catalog and Lineage</title>
    <link>https://community.qlik.com/t5/Catalog-and-Lineage/What-problems-does-the-modern-data-stack-actually-solve-that/m-p/2066291#M961</link>
    <description>&lt;P&gt;Help an old guy out here! I have been working in the data warehousing / business intelligence field for the last 25 years. I have probably been exposed to every traditional technology under the sun. I am honestly having a really hard time understanding what the big deal is with the whole data lake / Serverless X / spark / airflow / metric store / etc. It seems to me that these technologies are geared towards use cases that either involve data volumes that most companies will never reach or reinvent stuff that already exists (how is a metric store any different than an OLAP cube with calculations?) What is it that’s so great that’s not solved by a file system, traditional ETL and a RDBMS?&lt;/P&gt;</description>
    <pubDate>Mon, 01 May 2023 10:33:13 GMT</pubDate>
    <dc:creator>rekhaben92</dc:creator>
    <dc:date>2023-05-01T10:33:13Z</dc:date>
    <item>
      <title>What problems does the “modern data stack” actually solve that have not been solved already?</title>
      <link>https://community.qlik.com/t5/Catalog-and-Lineage/What-problems-does-the-modern-data-stack-actually-solve-that/m-p/2066291#M961</link>
      <description>&lt;P&gt;Help an old guy out here! I have been working in the data warehousing / business intelligence field for the last 25 years. I have probably been exposed to every traditional technology under the sun. I am honestly having a really hard time understanding what the big deal is with the whole data lake / Serverless X / spark / airflow / metric store / etc. It seems to me that these technologies are geared towards use cases that either involve data volumes that most companies will never reach or reinvent stuff that already exists (how is a metric store any different than an OLAP cube with calculations?) What is it that’s so great that’s not solved by a file system, traditional ETL and a RDBMS?&lt;/P&gt;</description>
      <pubDate>Mon, 01 May 2023 10:33:13 GMT</pubDate>
      <guid>https://community.qlik.com/t5/Catalog-and-Lineage/What-problems-does-the-modern-data-stack-actually-solve-that/m-p/2066291#M961</guid>
      <dc:creator>rekhaben92</dc:creator>
      <dc:date>2023-05-01T10:33:13Z</dc:date>
    </item>
  </channel>
</rss>

