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    <title>topic Re: BIg Data  and traditional databases - meaning(s) of schema in SAS Academy for Data Science</title>
    <link>https://communities.sas.com/t5/SAS-Academy-for-Data-Science/BIg-Data-and-traditional-databases-meaning-s-of-schema/m-p/578704#M400</link>
    <description>&lt;P&gt;Hi: Here's the response from the course instructors:&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;The intent of the item on the slide is that data can be ingested into Hadoop as-is, without a predefined schema, such as a STAR or SNOWFLAKE schema, found in traditional relational databases.&amp;nbsp; &amp;nbsp;Hadoop is schema on READ .. whereas traditional databases are schema on WRITE.&amp;nbsp;&amp;nbsp;&amp;nbsp; Schemas are good .. but have restrictions when trying to work with big data, which 90% of is considered unstructured, like IoT (internet of Things) or Social media data.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;In traditional databases with schemas, &amp;nbsp;to add data into an existing schema, the RDBMS Data Base Administrator (DBA) and IT department had to analyze the data and determine where best to connect the data.&amp;nbsp; This delay, from working with previous customers, could take weeks or months.&amp;nbsp; The rigid process definitely incurs a certain amount of latency in Service Level Agreements.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;With Hadoop, you can add any data and define the table schema to read the data later.&amp;nbsp; In fact, you can have several table schemas ( columns,data types, sizes) to read the same data. The schema is determined by the intended use case.&amp;nbsp; With that said, Hadoop is very flexible in data access and storage formats.&amp;nbsp; This flexibility provides a data lake with tremendous capabilities.&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Hope this helps clarify your questions,&lt;/P&gt;
&lt;P&gt;Cynthia&lt;/P&gt;</description>
    <pubDate>Fri, 02 Aug 2019 14:32:57 GMT</pubDate>
    <dc:creator>Cynthia_sas</dc:creator>
    <dc:date>2019-08-02T14:32:57Z</dc:date>
    <item>
      <title>BIg Data  and traditional databases - meaning(s) of schema</title>
      <link>https://communities.sas.com/t5/SAS-Academy-for-Data-Science/BIg-Data-and-traditional-databases-meaning-s-of-schema/m-p/578645#M399</link>
      <description>&lt;P&gt;Hello,&lt;/P&gt;&lt;P&gt;I am not sure about the meaning of schema in the context of Hadoop. The word schema has a well-defined meaning in a traditional DBMS&amp;nbsp; ( Oracle, SQL Server etc. ). PLease see attachment - in this course it seems that schema leads to rigidity which is bad.&amp;nbsp; My question is " How can we remove the rigidity but still preserve some form of hierarchy and control ?&amp;nbsp; Is this not necessary ?"&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Thanks.&lt;/P&gt;&lt;P&gt;Odesh.&lt;/P&gt;</description>
      <pubDate>Fri, 02 Aug 2019 09:20:40 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Academy-for-Data-Science/BIg-Data-and-traditional-databases-meaning-s-of-schema/m-p/578645#M399</guid>
      <dc:creator>odesh</dc:creator>
      <dc:date>2019-08-02T09:20:40Z</dc:date>
    </item>
    <item>
      <title>Re: BIg Data  and traditional databases - meaning(s) of schema</title>
      <link>https://communities.sas.com/t5/SAS-Academy-for-Data-Science/BIg-Data-and-traditional-databases-meaning-s-of-schema/m-p/578704#M400</link>
      <description>&lt;P&gt;Hi: Here's the response from the course instructors:&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;The intent of the item on the slide is that data can be ingested into Hadoop as-is, without a predefined schema, such as a STAR or SNOWFLAKE schema, found in traditional relational databases.&amp;nbsp; &amp;nbsp;Hadoop is schema on READ .. whereas traditional databases are schema on WRITE.&amp;nbsp;&amp;nbsp;&amp;nbsp; Schemas are good .. but have restrictions when trying to work with big data, which 90% of is considered unstructured, like IoT (internet of Things) or Social media data.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;In traditional databases with schemas, &amp;nbsp;to add data into an existing schema, the RDBMS Data Base Administrator (DBA) and IT department had to analyze the data and determine where best to connect the data.&amp;nbsp; This delay, from working with previous customers, could take weeks or months.&amp;nbsp; The rigid process definitely incurs a certain amount of latency in Service Level Agreements.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;With Hadoop, you can add any data and define the table schema to read the data later.&amp;nbsp; In fact, you can have several table schemas ( columns,data types, sizes) to read the same data. The schema is determined by the intended use case.&amp;nbsp; With that said, Hadoop is very flexible in data access and storage formats.&amp;nbsp; This flexibility provides a data lake with tremendous capabilities.&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Hope this helps clarify your questions,&lt;/P&gt;
&lt;P&gt;Cynthia&lt;/P&gt;</description>
      <pubDate>Fri, 02 Aug 2019 14:32:57 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Academy-for-Data-Science/BIg-Data-and-traditional-databases-meaning-s-of-schema/m-p/578704#M400</guid>
      <dc:creator>Cynthia_sas</dc:creator>
      <dc:date>2019-08-02T14:32:57Z</dc:date>
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