Essentials to Data Analytics the Big Data Hadoop (1)

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• Essentials to Data Analytics the Big Data Hadoop
• We live in a world that is driven by data. How an
  organization defines its data strategy and
  approach to it makes a great deal of difference
  to be able to compete in future.
• Big Data describes the amount of data that is too
  large and complex to be handled with traditional
  software tools. It relates to data creation,
  storage, retrieval and analysis that is unique in
  terms of volume, velocity and variety. Madrid
  Software Trainings in association with industry
  experts provides complete practical Big Data
  Hadoop Training in Delhi.
• Volume The scale of the information processed
  helps define big data systems. Because the work
  requirements exceed the capabilities of a single
  computer, this becomes a challenge of pooling,
  allocating, and coordinating resources from
  groups of computers.
• Velocity It is the speed that information moves
  through the system. Data is frequently flowing
  into the system from multiple sources and is
  often expected to be processed in time to gain
  understanding and update the current vision of
  the system.
• Variety Data can be ingested from internal
  systems like application and server logs, from
  social media feeds and other external APIs, from
  physical device sensors, and from other
  providers. Big data seeks to handle potentially
  useful data regardless of where it's coming from
  by conjoining all information into a single
  system.
• Activities Involved in Big Data Processing
• Ingesting data into the system
• Obtaining the data into storage
• Computing and analyzing data
• Foreseeing the results
• With Big Data databases, enterprises can save
  money, increase revenue and achieve other
  business goals
• Build new applications- Big Data allows a company
  to collect billions of real time data points on
  its resources or customers and then repackage
  the data to optimize customer experience or
  utilizing the resources.
• Lower the cost- Big Data technologies can replace
  the expensive systems with the standard
  solutions. Many Big Data technologies are open
  source and therefore can be implemented at a low
  cost.

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• Types of Big Data Technology
• Operational Technology- Operational system
  provides operational capabilities for real time
  workloads where data is primarily captured and
  stored. It includes customer, inventory and
  purchase data. This system supports high volume
  low latency access. One such example is NoSQL
  databases.
• Analytical Technology- Analytical systems provide
  analytical capabilities for complex analysis that
  may touch most or all of the data. Analytical
  Data is used to make business decisions.
• Organizations are increasingly turning to big
  data to discover new ways to improve
  decision-making, opportunities, and overall
  performance. For example, big data can be
  optimized to address the challenges that arise
  when information that is dispersed across several
  different systems that are not connected by a
  central system. By assembling data across
  systems, big data can help improve decision-
  making capability. It also can augment data
  warehouse solutions by serving as a buffer to
  process new data for inclusion in the data
  warehouse. Madrid Software Trainings is rated as
  the best Hadoop institute in Delhi.
• Big data can lead to improvements in overall
  operations by giving organizations greater
  visibility into operational issues. Operational
  insights might depend on machine data, which can
  include anything from computers to sensors or
  meters to GPS devices. Big data provides
  unprecedented insight on
• customers decision-making processes by allowing
  companies to track and analyze shopping patterns,
  recommendations, purchasing behavior and other
  drivers that are known to influence sales.
• Cyber security and fraud detection is another use
  of big data. With access to real-time data,
  businesses can enhance security and intelligence
  analysis platforms. They can also process, store
  and analyze a wider variety of data types to
  improve intelligence, security and law
  enforcement.
• When you are talking about Big Data, you cannot
  help include Hadoop an open source software
  platform managed by the Apache Software
  Foundation. It helps to store and manage vast
  amounts of data efficiently and cheaply.
• Hadoop has two main parts
• Data processing framework- this is the Java based
  system known as MapReduce
• Distributed file system for data storage
• Hadoop Training in Gurgaon
• A comprehensive Hadoop Big Data training course
  designed by industry experts provides an in-depth
  learning on big data and Hadoop Modules.
• What will you learn in the course?

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Master HDFS, MapReduce, Hive, Pig, Oozie, Sqoop,
Flume, Zookeeper, HBase

Learn Spark, Spark RDD, Graphx, MLlib writing
Spark applications

• Master Hadoop administration activities like
  cluster managing, monitoring, administration and
  troubleshooting
• Configuring ETL tools like Pentaho/Talend to work
  with MapReduce, Hive, Pig, etc
• Detailed understanding of Big Data analytics
• Hadoop testing applications using MR Unit and
  other automation tools
• Work with Avro data formats
• Practice real-life projects using Hadoop and
  Apache Spark
• Be equipped to clear Big Data Hadoop
  Certification.
• Before the Big Data training, you should be
  familiar with the basics of UNIX, SQL and Java.
  If you are brushed up with these skills, it will
  be convenient on your Hadoop learning. For more
  details please visit- https//www.madridsoftwaret
  rainings.com/hadoop.php