A comparision between Big Data, Data Science and Data Analytics.
In reallity all these skills are used in majority of the applications. They are not a single discipline but you will have to learn it together. However AI Orineted Data Science is key for future. Best will be to learn the AI usecases than just learning data analytics alone.
- Big Data Features:
- Applied where huge amount of data or possibility of growing data to that level:
- If you have at least a TB of data in your data store it is good to consider
- Do not care the format of the data, can be applied any where
- Move away from batch process but more incremental but scalable data processing.
- Velocity is not problem, we can scale adding more infrastructure, tool is compatible for it.
- Definitons are chaged, Big Data is a reality every where and every developer has to learn.
Data Science Features and Requirement:
What is really Data Science:
- There are some institutes which they teach data analytics and saying data science. Data science is applying data processing scientifically and systematically for solving cerntain problems. It is not exploring data, it is not visualising data. I wonder why people are so worried out visualisations Traditionally many decades developers were visualising data in chart form, tabular form, clustering, mining! It is not Data Science. It is a mix of Data Engineering and AI tools. You see a problem like reading Malayalam Text or reacting to customer interactions over web. Then you need a solution and traditional tools can't do it then Data science comes to picture. Stay way form those who are just teaching machine learning and statistics using Numpy, Pandas, Spark etc and saying it is data science. At Expertzlab you can really learn Data science to solve certain problems and enhanced soulutions. Learn Cyber Security, Virtual reality, Robotics process Management and execution. Watch this space we will add more info here to help you to orient your career.