Every moment we are getting huge amount of information to store, all are coming from different type of sources in different format, so we need a well define mechanism to analyse and organise them for quick access on demand to create better values in business operation. That's where Data Science comes into picture
So we need to learn some certain skill set that will help us to find a solution for that complex data problem. Data Science is all about that!
If you look at any large enterprise system, there are various types of data getting stored in different format like text, picture, voice, video etc. Some data are even different languages, and finding them quickly from data warehouses when required is really tough job.
Data Product is a ready to use component that receive a input and produce result based on that input value and nature. There are some certain prefix algorithm and logic are written, which decides that how data will be processed and result produced.
A classic example is Google Spam filter, think, how Google decides that a particular data is to be considered as spam.
Another good example can be any recommendation engine, just think based on your behaviours (what you click often, view often, duration etc.) the engine comes up with new set of new recommendation of similar or relevant products/ movies/ service etc.
Data Analytics are widely used to forecast different possibilities, the process involves digging deep and analysing information using different technologies and tools.
There are various types of Data Analytics Services, some are predefined, based on best practices for a specific business vertical, where Analytics development companies focuses on bringing up the best forecast that may help any business in that vertical to prepare best strategy, optimise their business and create best values with the data they have.
And some Data Analytics Services are built on demand, where the requirement specifications are based on various parameters, so they can’t depend on any standard or predefined services. Especially in field of health care, medicines, consumer goods for new market, many of them are research oriented, where client need to understand different type of possibilities, so they can explore better.
Analytics is all about Analyzing and Visualizing Data with BI like SSIS, Excel, Know more about Data Analytics, what all technologies you should learn and what would be the future demand, and how to start career in Data Analytics
Before we classify Data Science into different conceptual areas we should understand how big enterprise businesses are built up, how they execute operation on day to day basis, what are the inter dependency factors, how data collection is being done, and finally how those data are analysed and utilised for solving end customer problem, basically we should have some understanding of enterprise lifecycle.
Below are three different skill sets we need to have for implementing data science in any enterprise business.
Accelerate your skill in data science by learning starting from basics in Statistics, Data Management and Analytics to advanced topics like Big Data, Neural Networks, Machine Learning