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Table of contents
1.
Introduction
2.
Principles for Data Streaming
3.
Applications
4.
Examples of Data Streaming
5.
FAQs
6.
Key Takeaways
Last Updated: Mar 27, 2024
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Data Streaming

Author Prachi Singh
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Introduction

Data Streaming is an analytic computing framework with its primary focus on speed. The main idea behind these administrators on the requirement of a continuous stream of often unstructured data to be processed. Therefore, data is continuously kept under transformation in memory before it is featured on a disk. This approach is similar to data management by leveraging Hadoop. The primary difference between leveraging Hadoop and Data streaming is the issue of velocity. In the Hadoop cluster, data processing takes place in consequent batches. Speed factor plays a less dominant role in Hadoop than data streaming.

Principles for Data Streaming

Some fundamental principles that define data streaming applications in a real-time environment are as follows. 

1. When it is necessary to determine a retail buying opportunity at the engagement point, either via social media or via permission-based messaging.

2. To collect information about the movement covering a secure site. 

3. To be able to react to an event that needs an immediate response, such as a service outage or a change in a patient’s medical condition.

 4. To calculate the real-time cost that is the variant of dependent variables such as usage and available resources.

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Applications

Streaming data is applicable when analytics need to be performed in real-time while the data is under motion. In fact, the analysis value degrades with time. For example, if the employee is unable to analyze and act at the moment, a sales opportunity might be in danger or a threat might go undetected.

Examples of Data Streaming

A telecommunications company in a highly performable market wants to declare that outages are carefully inspected so that detected drop-in service phases can be accelerated to the right group. Communication systems result in a generation of vast data sets that must be analyzed in real-time. A slight delay in error detection can seriously impact customer satisfaction.

A medical diagnostic group is expected to take massive volumes of data from brain scans and analyze the results in real-time environments to determine the location of the source problem and measures needed to help the patient. 


FAQs

1. What is Data Streaming?

   Data Streaming is an analytic computing framework that is focused on speed.

2. Define the application of Data Streaming.

    Streaming data is useful when analytics are needed in real-time while the information is in motion.

3. Define the purpose of data streaming in telecommunications.

    Communication systems deal with huge volumes of data that must be analyzed in real-time environments to take the appropriate action.

4. Define the purpose of data streaming in medical diagnostics.

    The data is used in real-time to provide early warnings of changes in a patient’s condition. In some situations, doctors are finding that they are able to take corrective action to help a patient almost 24–36 hours earlier than without the data-streaming technology.

5. Define the purpose of data streaming in a power plant. 

     A power plant needs to be a highly protected environment so that unauthorized persons do not interfere with the delivery of power to expected customers in the living world.

Key Takeaways

Congratulations on finishing the blog!! After reading this blog, you will grasp the concept of the Data Streaming.

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