SUGANYA JAYARAMANPANNEERSELVAM

To pursue a highly challenging career, where I can apply my existing knowledge and creativity, acquire new skills, and contribute effectively to the organization. Coordinated scheduler driven to optimize procedures and improve productivity. Knowledgeable about calendar management and documentation. Bringing several years of experience in administration and customer service.

• I have positive attitude towards things and take every negative happenings or criticism as a challenge
• I am adaptable & adjust according to my surroundings and neighbors
• I am very much attracted to practical knowledge rather than theoretical and am keen to improve myself

• English
• Tamil

Reading books Surfing

Product delivery and account payment between Merchant and Customer, The goal is to develop a framework for monitoring such service systems. To establish its feasibility, and evaluates it with scenarios and comparisons against existing proposals. It monitoring the software systems is closely tied to the monitoring of requirements and how they are realized in software. If observes and analyzes the behavior of another (target) system, that determining qualities of interest, such as satisfaction of the target system’s requirements., Windows XP, Asp.Net With C#, Sql Server 2005

• C++ Programming
• VBA
• HTML
• SQL
• Oracle
• Python
• Perl
• Java Script
• Cloud Services
• Databases
• Data Science

• Father's Name: Mr.P.J.Panneer selvam
• Mother's Name: Mrs.P.Devaki
• Date of Birth: 07/07/92
• Gender: Female
• Nationality: Indian
• Marital Status: Married

Project: Automating Data Processing Workflow with CA ESP Batch Scheduler

Objective: The project aims to automate a data processing workflow where multiple tasks (data extraction, transformation, loading, and reporting) need to be executed in sequence on different systems (mainframe and distributed). The CA ESP Batch Scheduler will ensure that these tasks are scheduled, monitored, and completed without manual intervention.

Step 1: Define Workflow Requirements

• Data Extraction: A job that pulls data from an operational database on a mainframe.
• Data Transformation: A set of tasks that clean, enrich, and transform the extracted data into a structured format, performed on a distributed server.
• Data Loading: A job that loads the transformed data into a data warehouse.
• Reporting: A final job that generates and sends reports to stakeholders, using the newly loaded data.

Step 2: Install CA ESP Batch Scheduler

Ensure that the CA ESP Batch Scheduler is installed on both the mainframe and distributed systems. Follow the product documentation for proper installation and configuration.

Step 3: Create and Configure Job Definitions

Each step in the workflow will have a corresponding job. Define jobs using CA ESP's scripting language or job definitions in the ESP user interface.

• Job 1: Data Extraction
• Job Type: Batch job on mainframe
• Execution Time: Scheduled daily at midnight
• Dependencies: None (first job in the workflow)
• Job 2: Data Transformation
• Job Type: Batch job on distributed server
• Execution Time: After successful completion of Job 1
• Dependencies: Job 1
• Job 3: Data Loading
• Job Type: Batch job on distributed server
• Execution Time: After successful completion of Job 2
• Dependencies: Job 2
• Job 4: Reporting
• Job Type: Batch job on distributed server
• Execution Time: After successful completion of Job 3
• Dependencies: Job 3

Step 4: Set Job Dependencies and Conditional Logic

Using CA ESP's job control language (JCL), set dependencies to ensure that jobs run in the correct order. Define failure conditions and alert mechanisms:

• Job Dependencies: Each job should be scheduled to start only after the successful completion of its predecessor.
• Job Failures: If a job fails, trigger an alert to the administrator and prevent subsequent jobs from running.
• Alerts and Notifications: Set up notifications to be sent via email or other communication channels in case of job failure or completion.

Step 5: Scheduling Jobs in CA ESP

Use CA ESP’s scheduling functionality to automate the execution of the jobs. Specify the frequency and time for each job to run:

• Data Extraction: Schedule this job to run at midnight every day.
• Data Transformation: This job will run at 2 AM, two hours after the Data Extraction job.
• Data Loading: This job will run at 5 AM, after Data Transformation is completed.
• Reporting: The reporting job will be scheduled for 6 AM, after data loading finishes.

Step 6: Test the Workflow

Before going live with the automated workflow, thoroughly test each step of the process:

• Test job execution individually to ensure each job works as expected.
• Test the entire workflow, verifying that jobs run in the correct order and dependencies are respected.
• Verify that error handling mechanisms (e.g., alert notifications, job retries) work as expected.

Step 7: Monitor Job Execution

After the jobs are scheduled, you will use CA ESP's monitoring features to track job execution:

• CA ESP Monitor: Provides a real-time view of the job statuses and allows you to quickly identify if any jobs fail.
• Reports and Logs: Use job logs to identify issues with job execution. Set up reports to summarize job completions and failures.

Step 8: Reporting and Analysis

Use CA ESP’s integration with reporting tools (or custom scripts) to generate end-of-day or weekly reports based on the job execution logs. These reports can include:

• Job Success/Failure Summary
• Job Runtime Metrics
• Error Logs (if any)

Step 9: Optimization and Refinement

• Optimize Job Performance: As the system scales, you might need to optimize jobs to ensure they complete faster (e.g., optimizing database queries or using parallel processing).
• Refine Scheduling: As new jobs or tasks are added to the workflow, modify the scheduling and dependencies as needed.
• Automation: Implement more automation for administrative tasks like system cleanup, log rotation, and backups.

Step 10: Final Deployment and Documentation

Once the workflow is tested, optimized, and refined, deploy it into the production environment. Document the following:

• Detailed descriptions of each job and its dependencies
• Monitoring procedures
• Troubleshooting steps
• Reporting templates

Project Benefits:

This project is just one example of how to leverage CA ESP Batch Scheduler for automation. Depending on the specifics of your business and IT infrastructure, the project could be customized to handle more complex or larger-scale operations.