Description |
1 online resource (414 pages) |
Series |
Chapman & Hall/CRC Big Data Series |
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Chapman & Hall/CRC big data series.
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Contents |
Cover -- Half Title -- Title Page -- Copyright Page -- Table of Contents -- Preface -- About the Editors -- Contributors -- Chapter 1: Challenges in Big Data -- Introduction -- Background -- Goals and Challenges of Analyzing Big Data -- Paradigm Shifts -- Organization of This Paper -- Algorithms for Big Data Analytics -- k-Means -- Classification Algorithms: k-NN -- Application of Big Data: A Case Study -- Economics and Finance -- Other Applications -- Salient Features of Big Data -- Heterogeneity -- Noise Accumulation |
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Spurious Correlation Coincidental Endogeneity -- Impact on Statistical Thinking -- Independence Screening -- Dealing with Incidental Endogeneity -- Impact on Computing Infrastructure -- Literature Review -- MapReduce -- Cloud Computing -- Impact on Computational Methods -- First-Order Methods for Non-Smooth Optimization -- Dimension Reduction and Random Projection -- Future Perspectives and Conclusion -- Existing Methods -- Proposed Methods -- Probabilistic Graphical Modeling -- Mining Twitter Data: From Content to Connections |
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Late Work: Location-Specific Tweet Detection and Topic Summarization in Twitter Tending to Big Data Challenges in Genome Sequencing and RNA Interaction Prediction -- Single-Cell Genome Sequencing -- RNA Structure and RNAâ#x80;#x93;RNA Association Expectation -- Identifying Qualitative Changes in Living Systems -- Acknowledgments -- References -- Additional References for Researchers and  Advanced Readers for Further Reading -- Key Terminology and Definitions -- Chapter 2: Challenges in Big Data Analytics -- Introduction -- Data Challenges -- Storing the Data |
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Velocity of the Data Data Variety -- Computational Power -- Understanding the Data -- Data Quality -- Data Visualization -- Management Challenges -- Leadership -- Talent Management -- Technology -- Decision Making -- Company Culture -- Process Challenges -- Introduction to Hadoop -- Why Not a Data Warehouse for Big Data? -- What Is Hadoop? -- How Does Hadoop Tackle Big Data Challenges? -- Storage Problem -- Various Data Formats -- Processing the Sheer Volume of Data -- Cost Issues -- Capturing the Data |
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Durability Problem Scalability Issues -- Issues in Analyzing Big Data -- HDFS -- Architecture -- MapReduce -- Hadoop: Pros and Cons -- Other Big Data-Related Projects -- Data Formats -- Apache Avro -- Apache Parquet -- Data Ingestion -- Apache Flume -- Apache Sqoop -- Data Processing -- Apache Pig -- Apache Hive -- Apache Crunch -- Apache Spark -- Storage -- HBase -- Coordination -- ZooKeeper -- References -- Chapter 3: Big Data Reference Model -- Introduction into Big Data Management Reference Model |
Notes |
""Information Visualization Based on the IVIS4BigData Reference Model "" |
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Print version record |
Subject |
Big data.
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Big data
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Form |
Electronic book
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Author |
Deka, Ganesh Chandra
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ISBN |
9781351180320 |
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1351180320 |
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