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Apache Hadoop: What is high performance big data analytics

hadoop big data

Start with What is high performance big data analytics?

high performance big data analytics

Big data means extremely big datasets that are hard to deal or tackle using traditional computing techniques. Big data is not merely a data, rather it has become a complete subject, which involves various tools, technqiues and frameworks.

How a Hadoop distribution can help you manage big data

A decade ago companies were struggling to manage their huge amount of data as they were using outdated data warehouse platform, which resulted in high product rates, wrong calculation etc.

Then came, Hadoop, a distributed processing framework designed to address the volume and complexity of big data environments involving a mix of structured, unstructured and semi-structured data.

Hadoop run in clusters of commodity servers. Following is a list where hadoop is used to store big data

  • Operational intelligence applications: The purpose of Operational intelligence (OI) is to monitor business activities and identify and detect situations relating to inefficiencies, opportunities, and threats and provide operational solutions. Now Hadoop captures streaming data from transactions and keep a eye on performance levels. The owners of companies are continuously looking for ways to maximize productivity and profitability. When hadoop is used to store big data, it creates a pattern in operations to find new optimization opportunities.
  • Web analytics: High performance big data analytics continuously keep a track of visitors, likes, comment on websites like facebook, twitter for understanding and optimizing web usage.

Basic Steps of the Web Analytics Process

  1. Collection of data.
  2. Processing of data into information.
  3. Developing KPI: This stage focuses on using the ratios (and counts) and infusing them with business strategies.
  4. Formulating online strategy.
  • Security and risk management: 

Risk-management-for-Hadoop

Traditional techniques in hadoop for Security and risk management

  1. Kerberos (just like used for Network security)
  2. Apache Knox that is used for perimeter security.
  3. ESS (Enterprise scale security).
  4. Argus (a product of Apache Foundation) that is use for monitoring and managing the framework.
  • Marketing optimization: Marketers have to continually deliver above-market growth and show measurable results. Following steps are taken care in marketing optimization:
  1. Mainframe Optimization: Offload data and batch processing to Hadoop to free up expensive MIPS cycles and modernize the enterprise data architecture.
  2. Data Warehouse Optimization.
  3. Big Data Exploration: Perform investigative analytics on large data volumes of unknown value.
  4. Data Refining.
  • Internet of Things applications: 
  1. Security and PrivacyThe platform ensure a secure operation and privacy for apps and websites.
  2. Business continuityThe platform ensure a secure Business continuity for apps and websites.
  • Massive data ingestion: For data collection, processing such as capturing satellite images etc we use high performance big data analytics

Advantages of adopting high performance big data analytics

  • High performance hadoop big data analytics ensures a low-cost, high-performance computing framework to keep an eye on your big data.
  • Ingestion and processing of large data sets, massive data volumes and streaming data.
  • A need to eliminate performance impediments: It eliminate all the problems like data accessibility, latency and availability issues or bandwidth limits.

How Big Data involves in the data produced by different devices?

Examples:

high performance big data analytics

In Aerospace Domain

In Helicopters, Aeroplanes, Fighter planes, Space shuttles, It captures voices of the flight crew, recordings of microphones and earphones, and the performance information.

In Facebook and Twitter

high performance big data analytics faceook

high performance big data analytics twitter

 

 

 

 

 

 

Facebook and Twitter hold information and the views posted by millions of people across the globe are recorded and captured.

In Search Engine like Google and Yahoo

high performance big data analytics yahoo

high performance big data analytics google

 

 

 

 

 

Search engines retrieve lots of data from different databases.

High performance big data analytics is divided into 3 types of data

  1. Relational data i.e a digital database.
  2. XML data i.e the data on the World Wide Web, intranets.
  3. Word, PDF, Text, Media data.

Benefits of high performance big data analytics

  1. Real-time live monitoring events that impact either business performance.
  2. Ability to find, acquire, extract, analyze, and visualize data with the tools SAP for Public Sector application.
  3. Identify Information and improve decision quality.
  4. Addresses speed and scalability, mobility and security, flexibility and stability.

Ref: Apache hadoop website