Big data has become a catchword to explain about a very large amount of structured or unstructured data. This data is too big to handle that it gets tricky to manage using only traditional database techniques & software. The Big Data Scientist is an employee responsible for managing & statistically evaluating large amounts of data. The essential task of a Big Data Scientist is to narrate the importance of massive data in an easier way. The terminology “Big Data” sometimes can be used to explain the tools & processes a company might need in order to process a massive volume of data. A lot of studies & researches also represents that 90% of the data today has been created in a couple of years, eventually making the need for developing & implementing Big Data Technologies.
Major Aspects of Big Data Technologies
A lot of technologies & frameworks have been developed to manage big data & amongst them the most popular ones are:
- Hadoop is the most famous Big Data tool. It has an open source platform including a framework which has the capacity to manage multiple data sources. This can be also implemented to ensure maintenance, handling mistakes& security of the Big Data. One of the vital applications of Hadoop is to process & manage a massive volume of data which is constantly evolving.
- The foundation framework for Hadoop is Map Reduce. This allows the managing of massive volumes of data in distributed environment.
- No SQL databases are entirely different from the old relational databases. No SQL doesn’t need any particular table schemas for data handling.
- Grid computing in Big Data Technologies is a special type of distributed computing where a connection is created between multiple computer sources. These generally operate in association to manage large chunks of data.
- The in-memory databases use the primary memory of the system for processing the data. They are also used in systems where response duration & data requests are higher than usual.
- Specialized databases manage & process data which provides particular information.
Essentials Skills Required to Pursue the Data Scientist Job
If you already have your eyes set on the attractive big data career, then take notice of these important tips which will help you to get on the path to big data career excellence:
- Build an area of technical analytic expertise including a solid foundation in statistics. Then learn advanced statistics, machine learning & other language processing. Once you’ve built expertise in any one of these areas, you’ll be ahead of others in pursuing big data career or data scientist job.
- Learn telling stories with data. This is very important if you are looking for a data scientist job. After learning basic statistics you should be able to express your dynamic analysis in layman language so that you can ensure everyone understands. You always need to explain your results properly in a straightforward way. Visualization can help in these instances.
- Build a strong portfolio with data science certification or big data certificationcan earn you brownie points in pursuing a big data career or data scientist jobs. Projects are the best way to learn & showcase the skills that you’ve got. You can consider enrolling in some data science competitions to build up your portfolio for data scientist job.
Learning these skills & developing msay take a lot of time & effort but in the end, it will all be worth it!