The difference between big data and its science may not be much. Even though, it has always instigated the minds of many and put them into a dilemma.
Data science which deals with large volumes of information is an evolutionary extension of statistics and also with the help of computer science technologies. For the expansion of artificial intelligence, Machine learning, the internet of things (IoT), data science has played a significant role. It is also available in standard database formats. Better insights about decision making and strategic management are also provided by Big Data. Big Data is classified into three and it contains structured, semi-structured, and unstructured.
Unstructured provides information that is not pre-defined. Social networks, emails, blogs, digital images, and contents are the ones included in the Unstructured classification of Big Data. In the Semi-structured form of Big Data, there is no separation of information in the database model and the amount of structure depends on the purpose. Examples of Semi-Structured forms of Big Data include XML files, JSON files, NoSQL databases, etc.
A structured form of Big Data follows a reconcilable order and can be easily accessed and used by a person or a computer program. Examples of the structured form of Big Data include names, addresses, etc. It is easy to understand structured information. To extract information using various statistical tools and technologies, the unstructured form requires customized modeling techniques.
Though machine learning is a subset of data science, data science and big data are not the same which leads to quite a bit of confusion between these two subjects. Big data analytics helps to harness information efficiency in organizations to understand the untapped market. Thus, enhance the competitiveness and efficiency of the organizations. Data science evaluates information in a precise manner by concentrating more on providing modeling techniques and methods.
Data science extracts actionable insights with the attempt to utilize the information. The information collected by the companies is raw and massive. Velocity, variety, and volume are the 3Vs guiding the use of big data. Data Science garner insights from large volumes of information using theoretical as well as practical means. Big data is a pool of unstructured information with no inherent value and unless analyzed with deductive and inductive reasoning. An enormous amount of information needs to be mined in big data analysis.
Big Data relates more with technology, computer tools, and software while data science focuses more on business decisions. There is more focus on big data rather than a science due to the current trend in the information segmentation industry.
