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Big Data Analytics with Hadoop: Tools, Techniques, and Best Practices
| AUTHOR | Carter, Thompson |
| PUBLISHER | Independently Published (12/15/2024) |
| PRODUCT TYPE | Paperback (Paperback) |
Description
In today's data-driven world, the ability to harness massive datasets isn't just an advantage-it's a necessity for survival. This comprehensive guide demystifies Big Data analytics using Hadoop, transforming complex concepts into practical, actionable insights that will revolutionize how you handle data at scale. Whether you're a data scientist seeking to enhance your analytical capabilities, an IT professional aiming to modernize your infrastructure, or a business leader looking to drive data-informed decisions, this book delivers the exact blueprint you need to succeed in the Big Data era What Sets This Book Apart Practical Expertise
Master real-world applications through hands-on examples, from building recommendation engines to implementing predictive analytics. Complete Coverage
Learn everything from core Hadoop components to advanced topics like machine learning integration and real-time analytics. Future-Ready Skills
Gain expertise in cutting-edge technologies including Apache Spark, NoSQL databases, and cloud integration. Key Topics Covered
Master real-world applications through hands-on examples, from building recommendation engines to implementing predictive analytics. Complete Coverage
Learn everything from core Hadoop components to advanced topics like machine learning integration and real-time analytics. Future-Ready Skills
Gain expertise in cutting-edge technologies including Apache Spark, NoSQL databases, and cloud integration. Key Topics Covered
- Distributed computing fundamentals and HDFS architecture
- Real-time data processing with Apache Spark
- Machine learning implementation with Apache Mahout
- Cloud deployment strategies for AWS, Google Cloud, and Azure
- Security best practices and compliance frameworks
- Performance optimization techniques
- Integration with NoSQL databases and visualization tools
Show More
Product Format
Product Details
ISBN-13:
9798303712379
Binding:
Paperback or Softback (Trade Paperback (Us))
Content Language:
English
More Product Details
Page Count:
212
Carton Quantity:
36
Product Dimensions:
6.00 x 0.45 x 9.00 inches
Weight:
0.64 pound(s)
Country of Origin:
US
Subject Information
BISAC Categories
Computers | Database Administration & Management
Descriptions, Reviews, Etc.
publisher marketing
In today's data-driven world, the ability to harness massive datasets isn't just an advantage-it's a necessity for survival. This comprehensive guide demystifies Big Data analytics using Hadoop, transforming complex concepts into practical, actionable insights that will revolutionize how you handle data at scale. Whether you're a data scientist seeking to enhance your analytical capabilities, an IT professional aiming to modernize your infrastructure, or a business leader looking to drive data-informed decisions, this book delivers the exact blueprint you need to succeed in the Big Data era What Sets This Book Apart Practical Expertise
Master real-world applications through hands-on examples, from building recommendation engines to implementing predictive analytics. Complete Coverage
Learn everything from core Hadoop components to advanced topics like machine learning integration and real-time analytics. Future-Ready Skills
Gain expertise in cutting-edge technologies including Apache Spark, NoSQL databases, and cloud integration. Key Topics Covered
Master real-world applications through hands-on examples, from building recommendation engines to implementing predictive analytics. Complete Coverage
Learn everything from core Hadoop components to advanced topics like machine learning integration and real-time analytics. Future-Ready Skills
Gain expertise in cutting-edge technologies including Apache Spark, NoSQL databases, and cloud integration. Key Topics Covered
- Distributed computing fundamentals and HDFS architecture
- Real-time data processing with Apache Spark
- Machine learning implementation with Apache Mahout
- Cloud deployment strategies for AWS, Google Cloud, and Azure
- Security best practices and compliance frameworks
- Performance optimization techniques
- Integration with NoSQL databases and visualization tools
Show More