Big Data Hadoop Certification Training
- 147k Enrolled Learners
- Live Class
Today, organizations have data streaming in from all directions. The biggest challenge here is to accept the unstructured data, process it and derive business value and competitive advantage from the large volume of data. Hadoop, the elephant in the enterprise, has emerged as the dominant platform for Big Data. The biggest business priority right now is to get more data, where Hadoop can play a major role in analysing them.
Hadoop has a special capability of capturing data and performing analysis on sentiment data. Now, what is this sentiment data? They are unstructured bits of data, like opinions, attitudes and emotions that we mostly see on blogs, social media platforms, online product reviews and customer support interactions. Sentiment data is very essential for organizations to analyze and understand how their target audience and people in general feel about their products, services, competitors and reputation in the market.
Let’s consider the launch of a product as an example. Hadoop allows organizations to load the sentiment data on to the platform, refine the data and visualize what the public is feeling and talking about the product in real time. This analysis gives organizations a heads-up about the changes that needs to be made to the distribution and promotion of the product.
A visitor has landed on your website, what next? The basic role of Hadoop is to store and process the massive volume of click stream data. Some of the click stream data that Hadoop can capture are:
It is basically the analysis of the user engagement and website performance. By implementing Hadoop, enterprises of all types can perform click stream analysis to optimize the user-path, carry out basket analysis, and predict what could be the next product to buy or allocate their web resources. Hadoop can hold years of data in multiple formats from many sources. Hadoop also uses Apache HIVE to interact and process million and billions of data rows.
Hadoop analyses server-log data and responds in no time to an enterprise’s security breach.
What are server-logs? Server-logs are computer generated logs that capture data on the operations of a network, especially for security and regulatory compliance. Log processing can be used to extract lot of information. Hadoop is a great fit to extract errors or count the occurrence of some event within a system, such as login failures.
The admin can load the server logs into Hadoop to identify the cause of the security breach and repair it. Server log enables organizations with insights from network usage, security threats and compliance, and Hadoop plays a central role in staging and analyzing this type of data.
We are a part of a fast growing technological world, where smart-phones play a major role. Retail, manufacturing, auto industry and other enterprises can now track their customers’ movement and predict customer purchases using geo-location data using smart phones and tablets. Hadoop clusters help in streamlining enormous amount of geo-location data for the organizations to figure out their trouble areas in the business.
Sensor data is among the fastest growing data types, where data collectors are infused on almost every single thing. These sensors monitor and track specific things like temperature, speed, location, price, quantity and so on. Hadoop tracks, captures, stores and analyses the sensor data to report operational insights and conditional changes of an organization.
With more and more data to be captured and analyzed in the years to come, Hadoop armed with above skills will continue to shine.