Data is the collection of facts and bits of information. In the real world, the data is either structured or unstructured. Structured data is highly-organized and formatted in a way so it's easily searchable in relational databases. Unstructured data has no pre-defined format or organization, making it much more difficult to collect, process, and analyze. An article by Forbes states that data is growing faster than ever before. By the year 2020, about 1.7 megabytes of new information will be created every second for every human being on the planet.
Data Science and Big Data are the two terms commonly referenced in all literature. In order to meet the growing need for Big Data and Data Science talent, we witness the emergence of training programs across worldwide universities and training institutes.
Big data includes Unstructured data (news, articles, blogs, tweets, digital content audio, video, social networks, etc.), Semi-structured (XML files, system log files, text files, etc.) and Structured data. Big data approach cannot be handily accomplished utilizing traditional data analysis methods. Data science field is much needed, which comprises everything related to data cleaning, wrangling and analysis in dealing with big data. Data science is the field of study that combines domain expertise, programming skills, and knowledge of mathematics and statistics. Data science practitioners apply machine learning algorithms to numbers, text, images, video, audio, and more to produce artificial intelligence systems. Meanwhile, Data analytics is the science of examining raw data to reach certain conclusions. Data analytics' focus lies in inference, which derives findings based on what the researcher already knows.
Data Science Pillar
Data scientists come from various educational and work experience backgrounds, however, most should be strong in these fundamental areas, which are :
Business / Domain
Mathematics which includes statistics and probability
Computer science (e.g., software, data architecture and engineering)
Communication in both written and verbal
References
1. Data Science vs. Big Data vs. Data Analytics. Retrieved from https://www.simplilearn.com/data-science-vs-big-data-vs-data-analytics-article
2. Big Data: 20 Mind-Boggling Facts Everyone Must Read. Retrieved from https://www.forbes.com/sites/bernardmarr/2015/09/30/big-data-20-mind-boggling-facts-everyone-must-read/#34e1184a17b1
3. Data Types: Structured vs. Unstructured Data. Retrieved from https://www.bigdataframework.org/data-types-structured-vs-unstructured-data/