Big Data
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Overview:
Big Data refers to the processing and analysis of large and complex datasets that traditional data processing applications may struggle to handle.
Key Concepts:
Volume, velocity, variety, and veracity of data.
Skills Developed:
Managing, processing, and deriving insights from massive datasets.
Hadoop Ecosystem
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Introduction:
The Hadoop Ecosystem is a set of open-source software tools for distributed storage and processing of large datasets.
Key Components:
Hadoop Distributed File System (HDFS), MapReduce, Hive, HBase, Pig, and more.
Skills Developed:
Working with various tools in the Hadoop ecosystem to manage and process data.
Spark and Scala
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Overview:
Apache Spark is an open-source, distributed computing system that provides fast and general-purpose cluster computing.
Key Concepts:
Resilient Distributed Datasets (RDD), Spark SQL, and Spark Streaming.
Skills Developed:
Using Spark with Scala for efficient data processing and analysis.
NoSQL Databases
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Introduction:
NoSQL Databases are a type of database that provides a mechanism for storage and retrieval of data that is modeled in means other than the tabular relations used in relational databases.
Key Types:
Document-oriented (MongoDB), key-value stores (Redis), column-family stores (Cassandra), and graph databases (Neo4j).
Skills Developed:
Working with various NoSQL databases based on specific use cases.
Data Mining
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Overview:
Data Mining involves discovering patterns, trends, and insights from large datasets to support decision-making.
Key Techniques:
Association rule mining, clustering, and classification.
Skills Developed:
Applying data mining techniques to extract valuable knowledge from data.
Real-time Big Data Processing
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Introduction:
Real-time Big Data Processing focuses on processing and analyzing data as it is generated, enabling instant insights and actions.
Key Concepts:
Stream processing, Apache Kafka, and real-time analytics.
Skills Developed:
Implementing solutions for processing and analyzing data in real-time.
Big Data Analytics in the Cloud
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Overview:
Big Data Analytics in the Cloud leverages cloud computing platforms to perform large-scale data processing and analytics.
Key Platforms:
AWS, Azure, Google Cloud Platform (GCP), and others.
Skills Developed:
Utilizing cloud-based services for scalable and cost-effective big data analytics.
