This project will remove the legacy property management capabilities from LMS to pave the way for its ultimate retirement once sales capabilities have been decommissioned. The project will include the replacement of the legacy PMS supports for front desk operations (guest facing activities) and back office (e.g., Room Assignment, Housekeeping, Revenue Accounting, etc.). The new PMS will enable enhanced interactions between Cast and Guests by providing mobile technology to Front Office and Housekeeping Cast Members.

Responsibilities:

• Extracting the data from SFTP servers and publishing to Amazon S3 bucket using NiFi workflow.
• Converted the CSV data into Nested Json format using the Spark and Scala.
• Developed RDD’s, DF’s and Data sets for the required input data and performed the data transformations using Spark-Core.
• Loaded the data from servers directly into HDFS using Kafka.
• Handled Hive queries using Spark SQL that integrates with Spark environment.
• Scheduled the spark jobs using the cron scheduler

Disney Vacation Club (DVC) is migrating member data to a MariaDB system. IA will receive eventing messages and store them in the HDFS data lake. Data will then be exposed in familiar table structures via Hive for analytics to allow users to interact via HiveQL, a SQL-like language.

This project will remove the legacy property management capabilities from LMS to pave the way for its ultimate retirement once sales capabilities have been decommissioned. The project will include the replacement of the legacy PMS supports for front desk operations (guest facing activities) and back office (e.g., Room Assignment, Housekeeping, Revenue Accounting, etc.). The new PMS will enable enhanced interactions between Cast and Guests by providing mobile technology to Front Office and Housekeeping Cast Members.

STARS (Sales Trends Analytics Reporting System) Phase 2 is an extension of Phase 1 which was related to integrating the Room/lodging data for STARS. The scope of Phase 2 is anticipated to be integration of Package, phase 1 deferred and ticketing data into the STARS system.

Description:

Disney Vacation Club (DVC) is migrating member data to a MariaDB system. IA will receive eventing messages and store them in the HDFS data lake. Data will then be exposed in familiar table structures via Hive for analytics to allow users to interact via HiveQL, a SQL-like language.

Responsibilities:

• Developed the Kafka consumer job to read the JSON data from topic.
• Developed RDD’s, DF’s and Data sets for the required input data and performed the data transformations using Spark-Core.
• Loaded the data from servers directly into HDFS using Kafka.
• Build the data pipeline to store raw, data-asset and consumable areas.
• Developed the consumable are using Hive.
• Scheduled the spark jobs using the cron scheduler.
• Unit testing.

ARP will replace the package booking system (Accovia Logitours) which was implemented 20 years ago. This application is used by Disney Reservation Center at Disneyland Resort, Disneyland Paris, and Walt Disney World Resort as well as online Guests to book travel packages. Travel packages include Disney-provided components—such as rooms, dining plans, and theme park tickets—and externally procured components— such as air travel, rental cars, and ground transfers. This technology uplift will provide the necessary tools to continue supporting the evolving business. Additionally, this solution will establish the flexible package framework foundation of the larger strategic program vision known as Sales & Fulfillment. All future projects supporting this program will be initiated at the appropriate inflection points and be evaluated independently. Disney has chosen the application called TravelBox for this technology uplift.

Description:

Well Point, Inc. is one of the largest health benefits companies in the United States. Through its networks nationwide, the company delivers a number of leading health benefit solutions through a broad portfolio of integrated health care plans and related services, along with a wide range of specialty products such as life and disability insurance benefits, dental, vision, behavioral health benefit services, as well as long term care insurance and flexible spending accounts.

Edward as data warehouse extracts and stores data from across 13 different subject areas or domains across the enterprise. The different subject areas or domains are Members, Claims, Clinical, Rxclaims, RHI, Broker, Revenue, Capitation, Groupers, Provider. Apart from subject area the data comes from various source systems depending upon location, Business divisions, partners, vendors etc. Edward is the wellpoints single source of truth to support all business needs, all reports and downstream applications feeds data from here.

Responsibilities:

• Analysis of the specifications provided by the clients.
• Involved in writing/modifying scripts for loading data to target data warehouse for BTEQ, FastLoad and MultiLoad.
• SQL Assistant usage for data analysis and SQL queries.
• Worked with different Teradata objects like PI, SI and Derived Tables.
• Modifying the queries to use the Teradata features for performance improvement.
• Modified or created UNIX Scripts and Informatica workflows.
• Involved in developing and update existing scripts as per project requirements
• Prepared Unit Test cases to check that data entered has been uploaded correctly into the database.
• Modified or created WLM scheduled jobs, UNIX Scripts and Informatica workflows.Creating the Design Specification document as per the Requirements gathered

Well Point, Inc. is one of the largest health benefits companies in the United States. Through its networks nationwide, the company delivers a number of leading health benefit solutions through a broad portfolio of integrated health care plans and related services, along with a wide range of specialty products such as life and disability insurance benefits, dental, vision, behavioral health benefit services, as well as long term care insurance and flexible spending accounts. Edward as data warehouse extracts and stores data from across 13 different subject areas or domains across the enterprise. The different subject areas or domains are Members, Claims, Clinical, Rxclaims, RHI, Broker, Revenue, Capitation, Groupers, Provider. Apart from subject area the data comes from various source systems depending upon location, Business divisions, partners, vendors etc. Edward is the wellpoints single source of truth to support all business needs, all reports and downstream applications feeds data from here.

GSK project is a enhancement project for the existing EDW. Source data from Oracle, SQL Server, Db2 or Flat files flow into Teradata Database transition tables; Extracting data from different source systems, data transformation and loading to Teradata staging tables (ETL process) is implemented through Informatica workflows or Data from Flat files are loaded to staging tables through Teradata Utilities like Fast load and Multi-load.

Responsibilities:

• Write/Modify scripts using Teradata BTEQ, FastLoad, MultiLoad utilities to make load jobs.
• Involved in building tables, views and Indexes
• SQL Assistant usage for data analysis and SQL queries.
• Worked with different Teradata objects like PI, SI, Volatile Tables, GTT and Derived Tables.
• Modifying the queries to use the Teradata features for performance improvement.
• Modified or created IPM scheduled jobs, UNIX Scripts and Informatica workflows.
• Created Semantic Layer views.
• Prepared Unit Test cases to check that data entered has been uploaded correctly into the database.

GSK project is a enhancement project for the existing EDW. Source data from Oracle, SQL Server, Db2 or Flat files flow into Teradata Database transition tables; Extracting data from different source systems, data transformation and loading to Teradata staging tables (ETL process) is implemented through Informatica workflows or Data from Flat files are loaded to staging tables through Teradata Utilities like Fast load and Multi-load.

The purpose of the reconciliation project is to ensure that data in AOCM,CAP-CIS,IB and IKNOW are not only in synch but also exactly matched. There are two general types of data matching and comparison logic applicable for this system - key integrity check comparisons and direct attribute value comparison. Any field that is part of a primary key, can only be compared via a set comparison, as per customer exception report. Any non-key attribute, can be directly compared to its corresponding value in opposing system, based on a primary key match in both. These separate comparison types will be reported via two separate report types called the customer exception report and an attribute exception report.

Supervalu is a leader in the grocery retailing industry. We combine expertise in grocery retail and supply chain operations. Supervalu is grounded in a rich, 135-year history of food-industry innovation. As one of the nations most formidable grocery retailers, Supervalus nationwide network of approximately 2,500 retail stores embodies the full range of grocery retailing formats, blending price, service and selection to best address the communities that we serve. Approximately 2,200 successful retailers count on Supervalu for on-time deliveries, product availability and competitive rates. Marketing Analysts requires making quick decisions on current campaigns and pre/post campaigns in order to Supervalu success.

The EDW is being impacted by changes being made in the Billing system, Infranet. The Billing source files are being modified as part of enhancements being made for Project Phoenix. The requirement is to develop a new feed that will improve the current process, in terms of efficiency and simplicity, for the sourcing and loading of billing source data. This new process will be independent of other billing processes.