Data is an information which give us a concrete and accurate insights. This is what the business needs to survive and surpass every struggle along the way. Without data, businesses may have the possibility to fail because it is exceedingly difficult to position any business in the market if its not backed up with data.
Data is everywhere. The amount data that are produce every second, every minute, every day is a mind-boggling. There might be more than 2.5 quintillion bytes of data are created each day. There are so much about the data that is not easy to handle, manipulate and understand.
Since data is found everywhere, the question that always linger in me is that where or is there any data repository? Where is this located? How to get the data that we are looking? How should we make use of the data? These are the questions that we need to think about.
These questions lead me to understand the concept of Data Science and Data Engineering. As data becomes more intrinsically key to business success, the implementation of a coherent data strategy becomes paramount. It is especially important for a business to have a good grasp of data. Businesses should understand the components of data and it is a requirements to have a sound data strategy management which can able to cover topics such as scalability, new and emerging technology, multichannel inter-connectivity, to avoid problem related to data silo situation and develop a data driven culture.
That is where Data Science and Data Engineering is coming from. To help business and enterprise understand the data to have a sense for them. This is the reason why Data Science is regarded as the sexiest job in the 20th Century.
Data Science is a collaboration of a theoretical and applied sciences in the field of Statistics, Computer Science, and Business. Thus, one should understand that it is not a one-man discipline. Data Science is a collaboration of professionals in the field of Statistics, Computer Science and Business; thus, you can never find someone who knows the different corners of Statistics, Computer Science and Business. They are not all knowing. Statistics alone is an extremely broad area and one cannot discover applied and theoretical statistics, one cannot discover and develop different algorithms or models. In addition, Computer Science is also a very extremely broad area to understand, as well as Business.
While there are some Statisticians who knew how to code, who knew how to use Python, R, or SAS but these are only few among the Computer Programming Languages and we are all aware that as we are embracing the technology, there are also discoveries of the different computer programming languages like Julia, etc. On the other hand, do not expect a Computer Scientist to fully understand the different algorithms, and models and even the basics of Statistics and different branches. To add, do not expect these people to understand the business itself. Business is also extremely broad area to explore.