Our Big Data course content covers all the essential Big Data concepts from basic to advanced level. It is prepared by our industrial trainers which is suitable for all aspirants. This Big Data Course content is standardized and reviewed frequently.
ClickStream Data
ClickStream data could be generated from any activity performed by the user over a web application. What could be the user activity over any website? For example, I am logging into Amazon, what are the activities I could perform? In a pattern, I may navigate through some pages; spend some time over certain pages and click on certain things. All these activities, including reaching that particular page or application, clicking, navigating from one page to another and spending time make a set of data. All these will be logged by a web application. This data is known as ClickStream Data. It has a high business value, specific to e-commerce applications and for those who want to understand their users’ behavior.
More formally, ClickStream can be defined as data about the links that a user clicked, including the point of time when each one of them were clicked. E-commerce businesses mine and analyse ClickStream data on their own websites. Most of the E-commerce applications have their built-in system, which mines all this information.
ClickStream Analytics
Using the ClickStream data adds a lot of value to businesses, through which they can bring many customers or visitors. It helps them understand whether the application is right, and the application experience of users is good or bad, based on the navigation patterns that people take. They can also predict which page you are most likely to visit next and can-do Ad Targeting as well. With this, they can understand the needs of users and come up with better recommendations. Several other things are possible using the ClickStream Data.
Project Scope
In this project candidates are given with sample click stream data which is taken from a web application
in a text file along with problem statements.
- Users information in MySQL database.
- Click stream data in text file generated from Web application.
Each candidate has to come up with high level system architecture design based upon the Hadoop eco systems covered during the course. Each candidate has to table the High-level system architecture along with designed eco systems and pros and cons will be discussed with all the other candidates. Finally, will choose the best possible optimal system design approach for implementation.
Candidates are given instructions to create an oozie work flow with the respective Hadoop Eco systems finalized based on the discussion. Candidates has to submit the project for the given problem statement and this will be validated by the trainer individually before course completion.
ECO System involved in click stream analytics Project
HDFS, Sqoop, Pig, Hive, Oozie
