Getting Started with Big Data
Learn all about Big Data and open the doors to opportunity.
Wipe the slate clean and learn Big Data from scratch
What is Big Data?
Big Data History, Technologies, Use cases
Apache Flink- Big Data Processing Framework
Big Data Use Cases- Hadoop, Spark, Flink Case Studies
Careers and Job Roles in Big Data
Level up to more exciting and challenging chapters
Vulnerability- the 10th V of Big Data
Skills Required to Become a Data Scientist
Lambda Architecture for Big Data
Big Data And Cloud Computing
10 Best Big Data Analytics Tools
Check out more cool technologies
Exploring the Concept
Let’s take a look at some facts about Big Data and its philosophies.
Roger Magoulas, in 2005, coined the term ‘Big Data’ to refer to a large set of data that was then nearly impossible to manage and process with traditional business intelligence tools. 2005 also observed the conception of Hadoop, an open-source framework that could process both structured and unstructured data. This was built on top of Google’s MapReduce and crafted by Yahoo!. Today, the term Big Data pertains to the study and applications of data sets too complex for traditional data processing software to handle. This concept faces challenges in capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating, information privacy, and data source.
Volume, variety, velocity, and veracity are the 4 V’s of Big Data.
Roger Magoulas