What is Big Data Analytics (BDA)?
The rapid development of data due to the large number of users who collect data and the influence of the industrial revolution 4.0 has also resulted in the growing role of Big Data. The data collected is based on factual data such as digital transactions, which are also growing rapidly, especially in our country, Indonesia.
The data that has been collected certainly meets at least eight characteristics of Big Data itself, such as volume, velocity, variety, variability, veracity, visualization, value, and validity. So, indirectly there is a butterfly effect; when one develops, it affects the development of other things. So, there needs to be a process so that data that has become Big Data or a large amount of data can be helpful because it is beneficial.
Big Data Analytics (BDA) is one thing that can provide a significant picture of the processing of this data. However, before that, you need to understand Analytics first. Note that the results from the analytics don’t usually cause much confusion as the context usually makes the meaning clearer. The starting point for understanding these analytics is how to explore, investigate, or understand objects down to their roots.
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This BDA differs from Business Intelligent (BI) and the Decision Support System (DSS). However, all three are related to one another. Business Intelligent (BI) can be seen as an umbrella term for all the applications that support Decision Support Systems (DSS) and how they are interpreted in industry and are expanding into the fields of health, education, tourism, and so on. BI evolved from DSS, and one could argue that analytics became from BI (at least in terms of terminology). Thus, analytics is an umbrella term for data analysis applications. So that we can conclude that BDA is an analytical tool and technique that will be very helpful in understanding big data as long as the algorithms that are part of this tool must be able to work with large amounts of data in real-time conditions and on different data.
This BDA usually requires an identification process, market segmentation, decision-making, performance development, building infrastructure, and transparency from new products to business model innovation. Because in this digital era, of course, greatly influences economic growth. Thus, the financial crisis that occurred can be helped. BDA certainly has a significant role as well as:
- Personalization
- Dynamic Pricing
- Customer Service
- Predictive Analytics
- Supply Chain Visibility
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Therefore, BDA is a science that is still developing. Many methods will be applied and combined to improve the accuracy or performance of existing analytical results. So that data processing will be more accessible, more effective, and more accurate.
