Table of contents
1.
Introduction
2.
Complex Event Processing
3.
Need for Metadata in Streams
4.
Products for Streaming Data
4.1.
IBM Infosphere Streams
4.2.
Twitter’s Storm
4.3.
Yahoo’s S4
5.
FAQs
6.
Key Takeaways
Last Updated: Mar 27, 2024
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The Need for Metadata in Streams

Author Prachi Singh
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Introduction

Big data offers new and exciting approaches to providing a different level of insight and operational sophistication to data management. The most critical issues for organizations are that the amount of information is enormous and needs to be processed and managed at the right speed to impact outcomes. But most of this analysis is related to large-scale analysis and decision making. Analyzing the massive amount of data from multitudes of sources can help the organization understand the meaning of data, plan for the future, and anticipate market changes and unanticipated customer requirements.

Complex Event Processing

Streaming computing is designed to handle a continuous stream of many undesirable data. In contrast, Complex Event Processing (CEP) deals with a few variables that need to be mapped with a particular business process. In many situations, CEP is dependent on data streams. However, complex event processing is not required for streaming data. If data is at rest, it does not belong to the category of streaming data or CEP. 

Need for Metadata in Streams

Most data management professionals are familiar with managing metadata in structured database management environments. These data sources are strongly typed and designed to be operated with metadata. One might assume that metadata is non-existent in unstructured data, but that is not always true. Typically you find structure in any data. Take the example of video content. However, one might not be able to know precisely the content of a particular video since a lot of structure exists in the video-based data. But in Contrast, if you are looking at the unstructured text, you know that the words are written in the English language and that if you apply the right tools and algorithms, one can decrypt the text.

Because of the available implicit metadata from given unstructured data, it is possible to parse the information using XML. XML is a way of representing unstructured text files with meaningful tags.

Products for Streaming Data

Products for streaming data are IBM’s InfoSphere Streams, Twitter’s Storm, and Yahoo’s S4.

IBM Infosphere Streams

InfoSphere Streams enables discrete analysis of massive data volumes. It is intended to perform varied analytics of dissimilar data types, including text, images, GPS, financial, satellite, and sensors. Infosphere Streams can support all data types. 

Twitter’s Storm

Twitter’s Storm is an open-source real-time analytics engine developed by a company called BackType, acquired by Twitter in 2011 partially because Twitter uses Storm. It is available open-source and has gained a significant place among dominant companies. It applies to any programming language for real-time analytics, continuous computation, distributed remote procedure calls (RPCs), and integration.

Yahoo’s S4

The four S’s in S4 stand for Simple Scalable Streaming System. Yahoo developed Apache S4! as a general-purpose, distributed, scalable, partially fault-tolerant, pluggable platform that allows programmers to develop applications for processing continuous data streams quickly. The core platform is written in Java and was released by Yahoo! in 2010. It was turned over to Apache a year later under the Apache 2.0 license. Clients that send and receive events can be written in any programming language.

FAQs

1. Define the purpose of streaming computing.

Streaming computing is designed to handle a continuous stream of many undesirable data. 

2. What is the purpose of Complex Event Processing?

Complex Event Processing (CEP) deals with a few variables that need to be mapped with a particular business process.

3. What is the role of Big Data in real life?

Big data offers new and exciting approaches to providing a different level of insight and operational sophistication to data management.

4. Name different products for streaming data.

Products for streaming data are IBM’s InfoSphere Streams, Twitter’s Storm, and Yahoo’s S4.

5. What is the full form of four S  in Yahoo’s S4?

The four S’s in S4 stand for Simple Scalable Streaming System.

Key Takeaways

Congratulations on finishing the blog!! After reading this blog, you will grasp the concept of the need for metadata in streams.

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