Big Data Hadoop : Companies are using Streaming Data for real time analytics

Big Data Hadoop : Companies are using Streaming Data for real time analytics

Streaming data a big word for all the organizations aiming for new projects. If you have the ability to develop programs and have analytic skill to process streaming data. You have it all what organizations are looking for. To everyone’s surprise, it is just one of the significant benefit.

Time when you get competitive edge?

To reach in a timely manner, we have a wide variety of specific use cases to demonstrate the time value of data and the merit of analysing it. To be quick in responding to an attack like fraud and cyber security let’s take an example in case your system detect an suspicious event during login on banking website you have the ability to block that. Big Data also improves the chances to shut down these types of theft before any loss. This will not only increase the customer satisfaction and confidence level however reduce financial loss.

Getting a real time or near real time insight from large scale data will add on in streaming architecture. For building these systems the most important aspect is having interest in fast stream processing systems like apache spark streaming. Technologies like this valuable but it’s just a part of what is needed.

To have an effective streaming system we need a tool capable of high throughput for multiple consumers re starting from a specific event persistence and most importantly efficient and reliable geo distributed replication.

“Use it and lose it” approach: Value beyond real time analytics.

 With the new effective messaging tool of streaming style, we are getting value beyond real time analytics. Telecommunication, Shipping and finance companies are giving lot of importance for proper handling of streaming data.

There are different needs for streaming data in telecommunication companies. The major is to analyse streaming event data communicated between cell towers and millions of cell phones or other network users who are quickly changing network usage patterns. The ability to handle millions of messages per second is high performance with geo distributed.

Effective ways are looked out to analyse the sensor data for equipment’s in transports also provide granular monitoring of logistical data on shipping containers. Shipping companies have interest in streaming data for different reasons. Location can be track by sensor on the containers any time. It helps in planning logistics and availability of capacity.The consumer can also use this data in tracking their goods.

Companies are using Big Data Hadoop for handling such vast amount of streaming data and thus creating lot of job opportunities for professionals in Big Data field.

Transportation companies are using this streaming data to reduce the fuel cost by adjusting routes according to route and environmental conditions.

 

 

 

 

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