Introduction to Big Data
Big Data Analytics examines huge, disparate data sets (i.e. big data) to identify patterns, trends, correlations, and other information that lead to insights organizations can harness in support of better decision-making.
Big Data Analytics is the science and engineering of problem solving where the nature, size, and shape of the data makes it difficult, or even impossible, to use traditional analytics tools.
Let's learn the basics first.
What is Big Data?
Big Data TERM is used for Data sets that are unprocessed, too large & complex, and time consuming for traditional data-processing application software to handle.
The ROLE of Big Data is to help companies make more informed business decisions by enabling data scientists, predictive modelers, and other analytics professionals to analyze large data volumes.
A Big Data PLATFORM is an integrated platform/framework which comprises of hardware, software, applications and distributed data processes (Write once and Read intensive) designed together. Its FAST, FLEXIBLE, SCALABLE and COST EFFECTIVE.
Big Data – Key Characteristics
Large Data sets - Candidates for Big Data
Lots of structured and un-structured data is being generated from these sources.
Big Data Use Cases By Vertical Industry
In addition, advanced analytics and use cases in the field of Artificial Intelligence are very common.
In next lesson, we will look at 4V's of Big Data.