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Big Data vs. Data Science

Billy Yann
Deep learning and machine learning specialist, well-versed with experience in Cloud infrastructure, Block-chain technologies and Big Data solutions.
January 11, 2020


What is big data?

Data is everywhere and is considered the most important thing in the human world. With people using different kinds of data every minute, a large number gets generated that cannot be processed effectively. The size is so huge that, it cannot be stored in the memory of a single computer; so, it needs to be segregated effectively or utilize for something else that is significant. This forms the basis of big data. The right use of big data will be beneficial to so many businesses in various sectors.

The knowledge obtained from data mining is included under big data as the information is quite large or big, which cannot be contained in a single storage device (how vast the size of storage device maybe). For analysis of big data, tools from science need to be utilized quite extensively.

What is data science?

Data Science comprises of information, which is both structured and unstructured. This deals with the cleansing of data, preparation as well as its analysis. From capturing data in unique and ingenious ways and the ability to look at things differently, data science is a combination of mathematics, statistics, programming as well as problem-solving skills. It also includes preparing, aligning, and cleansing data. This forms the crux of data science.

The science that deals with the identification, representation, and extraction of information, which is meant for certain contexts from a vast pool of data help in the faster growth of business enterprises and organizations. Proper analysis along with the right usage of programming software can segregate the data into various small packets. This aids in converting unstructured information into pure, polished, and business-relevant data.

Some major differences to talk about when our major topic is Big Data vs. Data Science

• Big data is used by various organizations for improving the overall efficiency of their business services as this helps them to understand more about the untapped market. This has the advantage of enhancing competitiveness.

• Data science concentrates on evaluating big data in the right way through various models.

• As the amount of data collected by various firms and companies are large (big data), it becomes essential to use data science to extract the maximum out of this information.

• The various tools in data science utilize both practical as well as theoretical approaches for extracting information from the big data; thus playing a vital role in using the full potential of big data.

•Through data analysis, the 3Vs (Velocity, Variety, and Volume) of big data can be analyzed properly.

• Big data needs to be analyzed by data analytics for it to be significant or credible. This is done using proper inductive as well as deductive reasoning.

• Through proper analysis, information obtained via data mining can be utilized for improving various businesses, as aforementioned.

• It has been observed that data science properly uses various apt machine algorithms for designing as well as developing clear statistical models; a good way to extract vital and utilizable knowledge, from big data.

• While big data focuses on technology such as information mining, data analysis deals with all the tools to extract adequate knowledge.

Areas where big data is utilized

datascience

Big Data in Communication

Firms that deal with telecommunication has a vast amount of information (big data), which they gather from their consumers, both old and new. A proper analysis of this knowledge aids these firms to resolve various issues that crop up.

Big Data for retail

The data obtained from customers of retail industries are absolute gold mines for them. This can change the dynamics of their business through proper analysis of the content. For instance, the feedbacks and reviews obtained from customers can be utilized to develop customized products that will ultimately result in the growth of these retail businesses.

Big Data for financial services

Big data plays a major role in the running and security of firms and companies that deal with financial transactions. The organizations such as retail banks, insurance firms, venture capitalists, investment enterprises, private wealth management advisories, and credit card companies rely on big data for running their operation as smooth as possible. The major functions include operational, compliance, customer, as well as fraud analysis.

Big Data for Education

The data obtained from the educational sector is quite large, which needs a proper brush-up through the scientific tools of data analysis. Of late, big data expert trainers are in very high demand and individuals can make good earning through this sector. Big data professionals are needed by various companies, industries, and businesses as well.

Areas where data science is utilized

Advertisements in digital media

The algorithms used for data science by the specific tools have benefitted the marketing world in a big way. This has paved a revolution in the way digital bill-boards and display banners are used. The Click-through Rates (CTRs) is increased via the process of apt digital marketing techniques.

Searches in Internet

Data science forms the backbone of many search engine algorithms. It helps the search engine bots to crawl through the websites, based on the keywords provided.

Enhancing user experience

The tools of data science aids in enhancing the user-experience as internet searching become much easier and focused. For instance, a lot of companies recommend a lot of products and services while a potential customer casually browses through online sites. This is indeed influenced by a user's search history.

Speech or image recognition

The image and speech recognition tools used by the data analysis ensures an enhanced user experience. By offering a barcode scanning facility in the mobile phone, one can tag their friends, use Facebook and also use image searches on Google. This also utilizes a face recognition algorithm along with a speech recognition facility. A wonderful way to use big data in images or speech effectively.

Conclusion

Big data is a haven for information nowadays. However, data analysis tools need to be used for analyzing this large amount of information and knowledge at hand. The information helps businesses to optimize their processes. Big data hand-in-hand with data analysis can help any business evolve effectively. Data science can drive the technology of analyzing big data in the coming months and years.