Big data refers to extremely large, and complex datasets generally from different sources. While Big data technologies refers to the software tools that are used to extract, process and analyze this data from an extremely complex and large data set for which traditionally used management tools are not sufficient.
There are 2 types of Big Data technologies-
Operational Big Data Technologies
Operational Big Data Technologies refers to the amount of data generated every day, such as online transactions, social media posts, or any other information from a specific firm that is analysed using big data technologies. It serves as raw data for big data analysis software. Information on MNC management, Amazon, Flipkart, Walmart, online ticketing for movies, aeroplanes, and railroads are just a few examples of Operational Big Data Technologies.
Analytical Big Data Technologies
Analytical Big Data Technologies is more sophisticated than Operational Big Data Technologies since it involves advanced adjustments to Big Data Technologies. This category comprises real-world Big Data analysis, which is critical for business choices. Stock marketing, weather forecasting, time series analysis, and medical records analysis are some examples of this type of analysis.
The 5 most popular Big Data technologies include-
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Hadoop Ecosystem
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Artificial Intelligence
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NoSQL Database
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R Programming
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Data Lakes
While the emerging Big Data technologies are-
1. TensorFlow
2. Beam
3. Docker
4. Airflow
5. Kubernetes
6. Blockchain
