Real Time Data Processing: Understanding Data Processing And Analytics

Introduction

Data is the new oil, and every business is becoming a data-driven business. The data science revolution has brought about many breakthroughs in different fields of study. Companies are constantly looking for ways to improve their performance by analyzing their huge data sets. This article discusses real time processing and the role it plays in the world of big data analytics.

Big Data

Big data is a collection of data that has grown beyond the ability of current software tools to capture, store, manage, and analyze. It can be structured or unstructured. Big data is usually stored in a NoSQL database (a type of database designed for storing large volumes of structured and semi-structured data) because it can hold more information than traditional relational databases.

Big data refers to large sets of information generated from many different sources – including social media posts, mobile phone GPS locations, sensors on machines in manufacturing plants and much more – that must be analyzed quickly in order to make decisions based on it.

Real Time Processing

Real time processing is the ability to analyze data in real time. This is different than real time analytics, which refers to the ability to use historical data for analysis.

Real time data processing is a subset of real-time processing and refers to the ability to perform complex calculations on incoming data as it arrives from various sources like IoT devices or web services.

Data Analytics

Data analytics is the ability to analyze data in real time. It’s a subset of big data, which itself is a subset of real time processing (RTSP).

Data analytics is useful for many things, including:

• Making predictions about future events based on historical data analysis and current conditions; for example, predicting when your supply chain will run out of inventory or whether customers will buy new products from you based on their previous purchases.
• Finding patterns in large sets of unstructured information that could help you improve business processes; for example, finding keywords used by potential clients online so that sales reps can target them with personalized offers more effectively than competitors do

Real time data processing is the ability to analyze data in real time.

Real time data processing is the ability to analyze data in real time. It’s used to detect fraud, predict customer behavior and market behavior.

Conclusion

Real time data processing is the ability to analyze data in real time. This means that you can use your analytics software to make decisions on how to act on information as it’s coming in, rather than after the fact when it might no longer be useful or relevant.