06304967.htm

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<title>Universitt Liechtenstein / C19 Data Management (CPE) (WS 21/22)</title>
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		    5209651
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                  <td valign="top"><h2 style="margin: 0px; padding: 0px;">C19 Data Management (CPE)<!----></h2></td>
				  
                  <td valign="top" nowrap><!---->1<!----><!----></td>
				  
                  <td valign="top" nowrap>WS 21/22</td>
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Modul<!----></td>
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Pflichtmodul<!----></td>
                  <td valign="top" nowrap><!---->30.0 L<!----><!----> / 22.5 h<!----></td>
                  <td valign="top" nowrap><!---->67.5 h<!----></td>
                  <td valign="top" nowrap><!---->3.00<!----></td>
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        <!----><h2>Lehrveranstaltungen</h2><!----><A HREF="../00022200/06306467.htm">Data Management 9652 1 WS 21/22, Vorlesung</A><br/><!---->

        <!----><h2>Modulleitung</h2><!----><!----><!---->Laskov, Pavel<br><!----><!----><!----><!----><!----><!----><!---->
       	<!----><h2>Studienplan</h2><!---->MSc EM 20<br><!---->MSc FI 20<br><!---->MSc WI 19<br><!---->
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        <!----><h2>Lehrinhalte</h2>
        <i>Data Management</i> covers the modern data-management cycle, from the collection of data from diverse sources to the preparation of data for data-driven applications. Students learn how to handle various data formats, how to assess and improve data quality, and how to store and process data using SQL, NoSQL, and Hadoop technologies. The course covers eight primary topics:<br/><br/><ul style='margin-top:0px; margin-bottom:0px'><li>Modern data-management requirements</li><li>Database system architecture</li><li>Diagnosing and handling data quality problems</li><li>Relational databases (SQL)</li><li>Hands-on labs with MySQL</li><li>Concurrency control techniques</li><li>NoSQL databases (e.g., MongoDB)</li><li>Apache Hadoop (HDFS, MapReduce)</li></ul><p/><!---->
    
        <!----><h2>Lernergebnisse</h2>
        After successful completion of the course, students will:<br/><br/><ul style='margin-top:0px; margin-bottom:0px'><li>understand the basic concepts and methods of modern data management</li><li>be able to collect and prepare data for data-driven applications</li><li>be able to select and apply appropriate technologies for building data-driven applications</li></ul><p/><!---->
     
        <!----><h2>Lehrmethode</h2>
        <ul style='margin-top:0px; margin-bottom:0px'><li>The module involves interactive lectures with exercises to integrate theoretical knowledge with practical design and analysis skills.</li><li>The e-learning platform Moodle is used throughout the course to disseminate course material and for information and discussion.</li></ul><p/><!---->
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         <!----><h2>Lehrmittel</h2>
        Compulsory reading:<br/><br/><ul style='margin-top:0px; margin-bottom:0px'><li>Elmasri, R., & Navathe, S.B. (2016). Fundamentals of Database Systems, 7th edition. New York: Pearson Education</li><li>Harrison, G. (2015). Next Generation Databases  NoSQL, NewSQL, and Big Data. California: Apress Media.</li></ul><p/><!---->
    
        <!----><h2>Prfungsmethode</h2>
        Written exam (60min)<p/><!---->
    
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        <p><small>&nbsp;<br>&Auml;nderungen vorbehalten</small></p>
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