Businesses operating in a highly complex and dynamic business environment are increasingly realising the importance of value in the data they gather for various purposes. As such they are employing an extensive variety of techniques to derive some valuable information and insight from that data. These ‘insights’ are the single most valuable things that are extracted from processing the data that is at an organisation’s disposal.
How data science, big data and data analytics work in the real world and how organizations make use of them can be best explained with the help of a real world example. A farmer say in Punjab grows maize in his agricultural lands. Now, what that farmer need to consider if he wishes to have a good crop. The farmer will be interested in seeds, fertilisers, pesticides, along with labour cost, transportation cost, watering cost, storage cost, etc. Weather is going to another of his major concerns. Ultimately the farmer will also look at the past trends and the prices the crops have been commanding in the market. You will see that the purpose of all this data is to provide insight which will help the farmer optimize his profit.
Big data are humongous amount of data that are beyond the processing capabilities of traditional system. In other words using of all data that are available to gain meaningful insights into a problem. The farmer instead of relying on one two factors like seeds, storage, fertilizers, etc can take into account all factors like water supply, historic supply and demand data, plant productivity, historic weather patterns, machinery cost, etc to increase his yield and profit.
Data science is a recent phenomenon that seeks to combine mathematics, statistics, programming and the ability to look into things in a different manner. Usually associated with Big Data, the primary job of data scientist is same as that of data analyst but at a significant higher level where the volume and velocity of data crosses a certain level.
Also Read:- How to Become a Data Scientist
Data analysis refers to the task of compilation and analysis of numerical information. Data analysts look at the numerical data the organization has collected, delve a bit deeper into it and then prepare reports so that people not well-versed with numerical or analytics aspects of things can understand it well and take decisions based on their understanding.
Arun prasath S
(India), Master Hadoop Administration
I went to Koenig Bangalore for my “Master Hadoop Administration“ course. Instructors at Koenig are very knowledgeable in the subject and they are able to explain it with real time example scenarios. They are able to complete all the topics on time. By the end of the class, I gained confidence in tackling production systems. I would recommend Koenig for anyone who would like to take Cloudera courses in Bangalore.