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In the recent years – the term BigData has been gaining popularity. And there has been a paradigm shift in the volume of information and the ways in which it can be extracted from this data.
ElasticSearch, LogStash, Kibana (ELK) is one of the few new-age frameworks which is capable of handling Big Data demands and scale.
Over the years the ELK stack has become quite popular. And for a good reason. It is a very robust, mature and feature rich framework. ELK is used by large enterprises, government organizations and startups alike. The ELK stack has a very rich and active community behind it. They develop, share and support tons of source code, components, plugins and knowledge about these tools freely and openly.
In organizations large or small – there is tons of data produced by various applications running across the enterprise. The decision makers and other business stakeholders require timely access to information in a digestible format – so that they can run the organization in a meaningful and efficient way. Kibana provides such functionality out of the box. It integrates seamlessly with ElasticSearch and provides a very easy to use and visually appealing way to explore our data.
In this course, we will focus on this enterprise data visualization tool – Kibana which is one of the core components of the ELK stack. We will look at the overview and explore the technology that goes behind this tool.
Knowledge and experience about ELK and Kibana could be very valuable for your career. The latest stats and figures show some incredible numbers like jobs requiring these skill sets pay higher than most of the jobs posted on public job boards within the US and annual salaries for professionals could be as high as $100,000. That is the exact reason why you must enroll in this course and take your career to the next level.
As the title suggests – this course aims to provide you enough knowledge about ELK and Kibana so that you can build useful visualizations based on your data using these components together. But specifically: