How is Big Data stored and processed

How is Big Data stored and processed? (2018) In a traditional approach, usually the data that is being generated out of the organizations, the financial institutions such as banks or stock markets and the hospitals is given as an input to the ETL System. An ETL System, would then Extract this data, and Transform this data, that is, it would convert this data into proper format and finally load this data onto the database. Now the end users can generate reports and perform analytics, by querying this data. But as this data grows, it becomes a very challenging task to manage and process this data, using the traditional approach, this is one of the fundamental drawbacks of using the Traditional Approach. Now let us try to understand some of the major drawbacks of using the Traditional Approach. The 1st drawback is, it an expensive system, as it requires a lot of investment for implementing, or upgrading the system, therefore it is, out of the reach of small and mid-sized companies. The 2nd drawback is, scalability. As the data grows, expanding the system is a challenging task. And the 3rd drawback is, it is time consuming, it takes lot of time to process and extract, valuable information from the data. I hope you might have understood the Traditional Approach of Storing and Processing Big Data and its associated drawbacks. Please don't forget to subscribe to our channel. https://www.youtube.com/user/itskillsindemand Enroll into this course at a deep discounted price: https://goo.gl/HsbEC8 If you like this video, please like and share it. Visit http://www.itskillsindemand.com to access the complete course. Follow Us On Facebook: https://www.facebook.com/itskillsindemand Twitter: https://twitter.com/itskillsdemand Google+: https://plus.google.com/+Itskillsindemand-com YouTube: http://www.youtube.com/user/itskillsindemand