Big Data simplified
Material type: TextPublication details: Chennai Pearson 2019Description: 329pISBN: 9789353435110Subject(s): Data analysis Data management -Computer data Big data technologyDDC classification: 005.74 Summary: Big Data Simplified blends technology with strategy and delves into applications of Big Data in specialized areas, such as recommendation engines, data science and Internet of Things (IoT) and enables a practitioner to make the right technology choice. The steps to strategize a big data implementation are also discussed in detail. This book presents a holistic approach to the topic, covering a wide landscape of Big Data technologies like Hadoop 2.0 and package implementations, such as Cloudera. In-depth discussion of associated technologies, such as MapReduce, Hive, Pig, Oozie, Apache Zookeeper, Flume, Kafka, Spark, Python and NoSQL databases like Cassandra, MongoDB, graphs, etc., is also included.Item type | Current library | Call number | Status | Date due | Barcode |
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BK | Stack | 005.74 SOU/B (Browse shelf (Opens below)) | Available | 51467 |
Browsing Kannur University Central Library shelves, Shelving location: Stack Close shelf browser (Hides shelf browser)
005.74 SIL/D Database system concepts | 005.74 SIL/D Database system concepts / | 005.74 SOL Hands-on smart contract development with solidity and ethereum From fundamentals ro deployment | 005.74 SOU/B Big Data simplified | 005.74 TAN/I Introduction to database system | 005.74 ULL/F First course in database systems | 005.74 WAT/D Data management : databases and organizations |
Big Data Simplified blends technology with strategy and delves into applications of Big Data in specialized areas, such as recommendation engines, data science and Internet of Things (IoT) and enables a practitioner to make the right technology choice. The steps to strategize a big data implementation are also discussed in detail. This book presents a holistic approach to the topic, covering a wide landscape of Big Data technologies like Hadoop 2.0 and package implementations, such as Cloudera. In-depth discussion of associated technologies, such as MapReduce, Hive, Pig, Oozie, Apache Zookeeper, Flume, Kafka, Spark, Python and NoSQL databases like Cassandra, MongoDB, graphs, etc., is also included.
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