Big Data

Some Important Terms in Big Data Analytics You Need to Understand.

Big Data Analytics has many terms that are sometimes difficult to understand. I will attempt to give a simple explanation of the most important terms in Big Data Analytics. However, if you are new to this topic, then you might consider beginning here: What is Big Data Analytics and Why is it Important in Fintech? Here are some of the important terms to Big Data Analytics.

  1. Algorithm: A statistical process or a mathematical formula runs by software to analyse data. Usually, it consists of numerous calculation steps and used to automatically solve problems or process data.
  2. Amazon Web Services: These are cloud computing services given by Amazon to assist individuals and organizations conduct large-scale computing operations without investing their own data storage warehouses and data farms.
  3. Analytics: This is the process of gathering, processing, and analysing data to produce insights that inform decision making.
  4. Big Table: This proprietary data storage system of Google, which it uses to store, among other things, YouTube, Google Earth and Gmail services. It has been put in the public domain via Google App Engine.
  5. Biometrics: This is the use of analytics and technology to identify people’s physical traits such as iris recognition, face recognition, and fingerprint recognition.
  6. Cassandra: This is a popular open source database management system that is managed by The Apache Software Foundation. It is designed to handle a large amount of data across distributed servers.
  7. Cloud: This simply means data or software running on remote servers. Data kept “in the cloud” is accessible over the internet.
  8. Distributed File System: This is data storage system that is designed to keep large amounts of data across numerous storage devices, to decrease the complexity and cost of storing large volumes of data.
  9. Data Scientist: This is an expert who extracts value and insights data. Usually, this term is used to describe someone that has skills in mathematics, computer science, data visualization, statistics, and creativity.
  10. Gamification: This is usually a powerful method of incentivizing data collection.
  11. HANA: This is a high-performance Analytical Application that is designed for high volume data analytics and transactions.
  12. Hadoop: In Big Data, Hadoop is one of the most widely used software frameworks. It is a collection of programs that enable storage, retrieval, and analysis of data sets.
  13. Internet of Things: This term generally means that more and more items collect, transmit and analyse data to increase usefulness.
  14. MapReduce: This refers to the software process of breaking up an analysis into parts that can be shared across various computers in different locations.
  15. Natural Language Processing: This is software algorithms that are designed to enable computers to more correctly recognize everyday human speech, allowing people to interact more efficiently with them.
  16. Predictive Analytics: This is the process of using analytics future events and trends from data.
  17. RFID: RFID tags Data Capture technology and Automatic Identification to enable information to be transmitted to computer systems, enabling real-world items to be tracked online.

The above list might not be complete, so please let us know any term that you would like included .As always, I hope this post is useful, isn’t it?

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