Streaming Analytics

EmmaThompson By EmmaThompson, 31st May 2017 | Follow this author | RSS Feed | Short URL http://nut.bz/29v3grao/
Posted in Wikinut>Business>Analysis

Many businesses are often skeptical about switching to streaming. They often feel that it is not for their business but that is not the case; all business benefit from streaming, albeit in different proportions.

Streaming Analytics And Scope For Improvement

Many people think of stream analytics as very different from traditional analytics. As a matter of fact, streaming analytics complements traditional analytic by adding real-time insight to your decision making. Actually, the purpose of stream analytics and traditional analytics is the same: to find the problem in the system as early as possible and plug it as soon as possible.

The main difference between the two is speed and ease with which this can be done in streaming analytics in almost in an automated way. While data analysis in traditional analytics could take days and even months to reach the problem it can be done in real time in the streaming analytics.

The traditional approach was centered on batch processing where data is analyzed on the basis of a schedule and processed thereafter. This was a major drawback as many times when the data was collated, read and understood, the problem had already taken the toll on the system.

The Apache Spark streaming is a revolutionary approach as it can grab events (like a click of a mouse, sensor data etc.) analyze its significance and take appropriate action and even share it with other users in real time, the process which would have been tedious and time-consuming in the traditional analytics.

Many entrepreneurs are skeptical about the Apache Spark streaming and often ask the data scientists is it right for them? Would it help their business? The answer is affirmative. Indeed it would help all businesses that generate data. Many of them may not realize this but there is no business which doesn’t generate data, some do on a large scale while others may generate fewer amounts of data depending upon the need of the business and scale of sophistication of their operation. Indeed the advantages of switching to stream analytics would vary from business to business. One would do well to identify applications and equipment that generate data in one's company and ask an effort to make an evaluation report that would give the fair idea about the importance of stream analytics.

Next big question to answer before moving to Apache Spark analytics is which streams need to be prioritized and which one must be given importance over the others. Naturally, this would depend upon many factors such as costs involved, the activity involved, time saved and so on.

For example, a company producing hazardous chemicals would do well to prioritize the streams that would be linked to various sensors and measuring instruments rather than the human resource department. The reason is simple the production needs to be secured first as it is a matter of health and any mishap could lead to loss of lives and a huge loss to the reputation of the company.

The next big question to decide upon is would you go for open source streaming that is Apache spark streaming or the readymade paid versions. Apache spark streaming is always recommended as it is open source and gives the user free hand to use it. Of course, the coding would be required to make a predictive model which would need manpower and time but that is an investment worth making!

Tags

Apache Spark Analytics, Apache Spark Streaming

Meet the author

author avatar EmmaThompson
I'm Emma Thompson from US. Writing is my passion and my interest in researching and writing on technical topics such as Business, Technology, IT Services and more.

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