Big Data Analytics has many terms that are occasionally difficult to comprehend. I’ll attempt to give a simple explanation of the main terms in Big Data Analytics. However, if you’re new to this subject, then you certainly might consider starting here: What’s Big Data Analytics and Why is it Important in Fintech? Below are some of the important terms to Big Data Analytics.
Algorithm: A statistical process or a mathematical formula runs by software to analyse data. Typically, it contains numerous computation measures and used to automatically solve problems or process data.
- Predictive Analytics: Here is the procedure for using analytics future events and trends from data.
- RFID: RFID labels Information Capture technology and Automatic Identification to enable information to be transmitted to computer systems, enabling real-world things to be tracked online.
- Amazon Web Services: All these are cloud computing services given by Amazon to help individuals and organizations conduct large-scale computing operations without investing their very own data storage warehouses and data farms.
- Analytics: This is the method of collecting, processing, and analysing data to produce insights that inform decision making.
- Enormous Table: This proprietary data storage system of Google, which it uses to save, among other things, YouTube, Google Earth and Gmail services. It’s been put in the public domain via Google App Engine.
- Biometrics: That is using analytics and technology to identify folks’s physical traits for example iris recognition, face recognition, and fingerprint recognition.
- Cassandra: It is a favorite open source database management system which is managed by The Apache Software Foundation. It really is created to handle lots of information across distributed servers.
- Cloud: This simply means data or applications running on remote servers. Data kept “in the cloud” is accessible over the internet.
- Distributed File System: This can be data storage system which is designed to keep considerable amounts of info across numerous storage devices, to reduce the complexity and cost of storing large volumes of data.
- Data Scientist: This can be an specialist who extracts value and insights info. Generally, this term is used to describe someone that’s abilities in mathematics, computer science, information visualization, statistics, and originality.
- Gamification: That is generally a robust method of incentivizing data collection.
- HANA: This is a high-performance Analytic Program which is created for high volume data analytics and trades.
- Hadoop: In Big Data, Hadoop is among the most widely used software frameworks. It’s a group of applications that empower storage, retrieval, and evaluation of data sets.
- Internet of Things: This term usually means that increasingly more things gather, transmit and analyse data to increase utility.
- MapReduce: This refers to the application process of breaking up an evaluation into parts which can be shared across various computers in numerous places.
- Natural Language Processing: This can be software algorithms which are built to enable computers to more accurately recognize everyday human speech, allowing visitors to interact more efficiently with them.
The above list may well not be complete, so please let’s know any term that you would like contained .