IT5612: Data Analytics and Cloud Computing Laboratory Syllabus for IT 6th Sem 2019 Regulation Anna University

Data Analytics and Cloud Computing Laboratory detailed syllabus for Information Technology (IT) for 2019 regulation curriculum has been taken from the Anna Universities official website and presented for the IT students. For course code, course name, number of credits for a course and other scheme related information, do visit full semester subjects post given below.

For Information Technology 6th Sem scheme and its subjects, do visit IT 6th Sem 2019 regulation scheme. The detailed syllabus of data analytics and cloud computing laboratory is as follows.

Course Objective:

• To provide hands-on experience to cloud and data analytics frameworks and tools.
• To use the Python packages for performing analytics.
• To learn using analytical tools for real world problems.
• To familiarize the usage of distributed frameworks for handling voluminous data.
• To write and deploy analytical algorithms as MapReduce tasks.

LIST OF EXERCISES:

Analytics Using Python:

1. Download, install and explore the features of NumPy, SciPy, Jupyter, Statsmodels and Pandas packages.
   1. Reading data from text file, Excel and the web.
   2. Exploring various commands for doing descriptive analytics on Iris data set.
2. Use the diabetes data set from UCI and Pima Indians Diabetes data set for performing the following:
   1. Univariate analysis: Frequency, Mean, Median, Mode, Variance, Standard Deviation, Skewness and Kurtosis.
   2. Bivariate analysis: Linear and logistic regression modeling
   3. Multiple Regression analysisAlso compare the results of the above analysis for the two data sets.
3. Apply Bayesian and SVM techniques on Iris and Diabetes data set.
4. Apply and explore various plotting functions on UCI data sets.Cloud Computing:
5. Installation of OpenStack.
6. Creation of VMs and installing applications and executing simple programs in OpenStack.
7. Simple applications for communication across VMs.Hadoop, MapReduce, HDFS, Hive:
8. Install and configure Hadoop in its two operating modes: Pseudo distributed and fully distributed.
9. Implement the following file management tasks in Hadoop: Adding files and directories, retrieving files and deleting files.
10. Create a retail data base with the following tables: Product, Customer, Manufacturer, Shipping and Time using MongoDB and perform data replication using sharding techniques.
11. Install HIVE and implement the above retail schema definition and perform CRUD operations.

Course Outcome:

On completion of the course, the students will be able to:

1. Install analytical tools and configure distributed file system.
2. Have skills in developing and executing analytical procedures in various distributed frameworks and databases.
3. Develop, implement and deploy simple applications on very large datasets.
4. Implement simple to complex data modeling in NoSQL databases.
5. Develop and deploy simple applications in OpenStack cloud.
6. Implement real world applications by using suitable analytical framework and tools.

For detailed syllabus of all other subjects of Information Technology, 2019 regulation curriculum do visit IT 6th Sem subject syllabuses for 2019 regulation.

For all Information Technology results, visit Anna University IT all semester results direct link.