Big Data refers to large datasets that could not be analysed by traditional database systems and processes like RDBMS and existing Data Warehousing systems. Big Data is generally characterized by Huge Volume, High Velocity and High Variety. Companies like Google, YouTube, Facebook, Amazon, Alibaba, Pandora, and Wikipedia are generating and collecting Petabytes of Big data every minute in multi-structured formats likes videos, audios, images, metadata, logs etc. The data generated can be used for Recommendations, formulating business and market strategies using Data Analysis and applying machine learning algorithms. It has been estimated that 2.5 Exabyte of Data is produced every day.
The Volume and variety of Big Data makes the task of Data Analysis using existing
traditional Data processing techniques extremely challenging. To solve this issue,
organizations are shifting towards using multiple servers and using parallel processing
to save time and memory. There are different technologies like Hadoop, Spark, HBASE
that have been developed and are rapidly evolving to deal with Big Data.
Hadoop makes it possible to run applications on systems with thousands of commodity hardware nodes, and to handle thousands of terabytes of data. Its distributed file system facilitates rapid data transfer rates among nodes and allows the system to continue operating in case of a node failure.
- Graduates, undergraduates eager to learn the latest Big Data technology can take this bigdata training.
- Programming Developers and System Administrators.
- Experienced working professionals , Project managers.
- Mainframe Professionals, Architects & Testing Professionals.
- Business Intelligence, Data warehousing and Analytics Professionals.
- Global Hadoop Market to Reach $84.6 Billion by 2021 – Allied Market Research
- Shortage of 1.4 -1.9 million Hadoop Data Analysts in US alone by 2018– Mckinsey
- Hadoop Administrator in the US can get a salary of $123,000 – indeed.com