CP 612

Data Management & Analysis

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This course provides students with a broad overview of the concepts, techniques and tools of modern data management and analysis. It compares traditional relational databases with an alternative model (a NoSQL database), and explains how to choose the most appropriate means of storing and managing data, depending on the size and structure of a particular dataset and its intended use. Students are guided through the basics of using Hadoop with MapReduce and Spark. In data analysis, both theoretical concepts and algorithms in Association Mining, Classification, Clustering, etc., and a range of advanced applications, including Link Analysis, Recommender Systems, Computational Advertising, etc., are introduced.

This course provides students with a broad overview of the concepts, techniques and tools of modern data management and analysis. It compares traditional relational databases with an alternative model (a NoSQL database), and explains how to choose the most appropriate means of storing and managing data, depending on the size and structure of a particular dataset and its intended use. Students are guided through the basics of using Hadoop with MapReduce and Spark. In data analysis, both theoretical concepts and algorithms in Association Mining, Classification, Clustering, etc., and a range of advanced applications, including Link Analysis, Recommender Systems, Computational Advertising, etc., are introduced.

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This course provides students with a broad overview of the concepts, techniques and tools of modern data management and analysis. It compares traditional relational databases with an alternative model (a NoSQL database), and explains how to choose the most appropriate means of storing and managing data, depending on the size and structure of a particular dataset and its intended use. Students are guided through the basics of using Hadoop with MapReduce and Spark. In data analysis, both theoretical concepts and algorithms in Association Mining, Classification, Clustering, etc., and a range of advanced applications, including Link Analysis, Recommender Systems, Computational Advertising, etc., are introduced.

CP 612

Data Management & Analysis

0%Liked

Easy

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This course provides students with a broad overview of the concepts, techniques and tools of modern data management and analysis. It compares traditional relational databases with an alternative model (a NoSQL database), and explains how to choose the most appropriate means of storing and managing data, depending on the size and structure of a particular dataset and its intended use. Students are guided through the basics of using Hadoop with MapReduce and Spark. In data analysis, both theoretical concepts and algorithms in Association Mining, Classification, Clustering, etc., and a range of advanced applications, including Link Analysis, Recommender Systems, Computational Advertising, etc., are introduced.

This course provides students with a broad overview of the concepts, techniques and tools of modern data management and analysis. It compares traditional relational databases with an alternative model (a NoSQL database), and explains how to choose the most appropriate means of storing and managing data, depending on the size and structure of a particular dataset and its intended use. Students are guided through the basics of using Hadoop with MapReduce and Spark. In data analysis, both theoretical concepts and algorithms in Association Mining, Classification, Clustering, etc., and a range of advanced applications, including Link Analysis, Recommender Systems, Computational Advertising, etc., are introduced.

0%Liked

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0 ratings

This course provides students with a broad overview of the concepts, techniques and tools of modern data management and analysis. It compares traditional relational databases with an alternative model (a NoSQL database), and explains how to choose the most appropriate means of storing and managing data, depending on the size and structure of a particular dataset and its intended use. Students are guided through the basics of using Hadoop with MapReduce and Spark. In data analysis, both theoretical concepts and algorithms in Association Mining, Classification, Clustering, etc., and a range of advanced applications, including Link Analysis, Recommender Systems, Computational Advertising, etc., are introduced.