How Big Data Revolutionizes Conventional Data Analytics

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Recently, big data has become a popular jargon amongst corporations. More and more companies are showing interest in big data in order to obtain competitive advantage in their respective industries. The existence of big data technologies increases the efficiency of an organization’s capabilities and values. No matter how popular big data may be, the term has yet to be understood by many. There are three distinctive features of big data compared to traditional data analytics.

The first feature of big data is the emphasis on flows as opposed to stocks. Unlike traditional data analytics that require large amounts of time for data processing, big data technologies allow organizations to continuously gather, analyze and interpret data. The traditional process of data extraction, preparation and analysis will take weeks to prepare and execute. Credit card companies are some of the many organizations that suffer from the inability to act fast. Big data technologies provide companies with a high level view of the business processes of the organization. In a short amount of time, big data technologies allow companies to look at the various aspects of available data as one big picture. This increases the organization’s ability to make better informed decisions based on many different sources of data in real-time.

The second feature is the reliance on data scientists, product and process developers compared to data analysts. Traditional data analysis mainly requires data analysts to analyze data. Big data technologies provide the necessary analytical functionalities and thus reducing the need for data analysts. With data now extracted, manipulated and structured in real time, data scientists play a more important role in interpreting big data. They are required to possess a mix of both management, and analytical skills in order to interpret the processed data and put it into practice. More organizations are starting their own talent development programs to cater the specific talent needs in managing big data technologies. Even though data analytics have been made faster and easier, the instant nature of big data requires swift decision and action.

Lastly, big data technologies emphasize more on core business, operational, and production functions compared to IT. The emergence of big data technologies has moved companies away from a tech-focused analytical approach to a more business-focused approach. Because data is constantly changing, the focus of big data is scalability and stability. This requires new analytical technologies to adapt faster and better to constant changes in data types. In order to provide flexibility, emergence of big data has allowed data delivery capabilities to move to the virtual cloud. Big data technologies are designed to focus on the ability to mine existing and new data sources in search of trends and patterns that can be used to better facilitate decision making processes. In essence, big data technologies emphasize more on insights, not automation.

These three distinct features are what set big data apart from traditional data analytics. The evolution of big data technologies are rapidly changing the way traditional data analytics is being conducted. The architecture facilitates fast and continuous sharing of information to allow rapid optimization of decisions and swift actions to be taken in order to gain a competitive advantage in any industry.


Yusri

Yusri Jamaluddin is the Co-Founder and Director of IRIS Institute. He is a Masters student in Business Analytics at Rensselaer Polytechnic Institute (RPI), New York. He is also a Scholar under the Master’s Scholars Research Program at RPI in which he works on translating a white paper on the impact of various cultures on global business strategies into articles for business practitioner outlets. He is the Co-Founder and Director of Human Capital for Future Business Leaders of America – Phi Beta Lambda RPI Chapter and is the current President of RPI Muslim Students Association. He previously worked at the Prime Minister’s office as an Analyst Intern where he gained insights and experience in policy analysis under the Government Transformation Program. He aims to pursue an academic career in public policy and is currently studying the impact of civil society institutions on governance and liberal democracy promotion in Muslim countries.

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