<?xml version="1.0" encoding="utf-8"?>
<export-example>
  <doc>
    <id>1082</id>
    <completedYear>2023</completedYear>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>9 (ungezählt)</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>other</type>
    <publisherName>Medium</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>2023-05-23</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">From Data Engineering to Prompt Engineering</title>
    <abstract language="eng">Data engineering makes up a large part of the data science process. In CRISP-DM this process stage is called "data preparation". It comprises tasks such as data ingestion, data transformation and data quality assurance. In our article we solve typical data engineering tasks using ChatGPT and Python. By doing so, we explore the link between data engineering and the new discipline of prompt engineering.</abstract>
    <parentTitle language="eng">Towards Data Science</parentTitle>
    <subTitle language="eng">Solving data preparation tasks with ChatGPT</subTitle>
    <identifier type="url">https://medium.com/towards-data-science/from-data-engineering-to-prompt-engineering-5debd1c636e0</identifier>
    <identifier type="urn">urn:nbn:de:bvb:92-opus4-10829</identifier>
    <enrichment key="opus.source">publish</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Christian Koch</author>
    <author>Markus Stadi</author>
    <author>Lukas Berle</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Prompt Engineering</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Data Engineering</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>ChatGPT</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Large Language Model</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Python</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Künstliche Intelligenz</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Natürlichsprachiges System</value>
    </subject>
    <collection role="ddc" number="0">Informatik, Informationswissenschaft, allgemeine Werke</collection>
    <collection role="institutes" number="">Fakultät Betriebswirtschaft</collection>
    <thesisPublisher>Technische Hochschule Nürnberg Georg Simon Ohm</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-ohm/files/1082/data_engineering_to_prompt_engineering.pdf</file>
  </doc>
</export-example>
