Big Data generally encompasses data sets characterized by high volume, velocity, and variety, making them unsuitable for traditional relational database management systems. To address these challenges, non-relational database technologies, collectively known as NoSQL databases, have emerged.
Predictive analytics uses the information generated in the data-mining phase to create
advanced predictive models with high degrees of accuracy.
Data analytics is a subset of BI functionality that provides advanced data analysis
tools to extract knowledge from business data.
Major components of Hadoop ecosystem.
3.Direct Query Applications
2.Data Ingestion Applications
1MapReduce Simplification Applications
primary characteristics of Big Data.3Vs
Volume—the quantity of data to be stored
Velocity—the speed at which data is entering the system
Variety—the variations in the structure of the data to be stored
Hadoop Framework
The Hadoop framework has quickly emerged as a standard for the physical storage
of Big Data. The primary components of the framework include the Hadoop Distributed
File System (HDFS) and MapReduce
No SQL
A new generation of
database management
systems that is not
based on the traditional
relational database
model.
No SQL is the unfortunate name given to a broad array of non relational database technologies
that have developed to address the challenges represented by Big Data
What is big Data?
Big Data generally refers to a set of data that displays the characteristics of volume, velocity,
and variety (the “3 Vs”) to an extent that makes the data unsuitable for management by
a relational database management system.