Aashish Prashant

Project Description

• The Enterprise Data Quality Framework (EDQ) is a fully metadata-driven, scalable solution designed to streamline and automate the application of data quality rules across diverse business domains. The framework enables both technical and business users to efficiently manage data quality using a centralized rule template repository, dynamic rule expansion, and a self-service UI layer.

Role & Responsibilities

1. Framework Implementation & Metadata Design

• Designed and delivered a metadata-driven Enterprise Data Quality (EDQ) Framework to enable scalable, reusable, and standardized rule execution across multiple domains and business units.
• Introduced a centralized Rule Template mechanism to define reusable logic (e.g., null checks, pattern checks, threshold validations), enabling dynamic rule expansion for multiple columns and datasets without code duplication.
• Built a flexible rule assignment model using metadata controls for full rule lifecycle management and governance tracking.

2. Python-Based Orchestration Wrapper

• Developed a robust Python wrapper layer that orchestrates:
• Metadata interpretation from PostgreSQL tables.
• Dynamic payload construction using rule templates.
• Execution triggering via Informatica IDMC CDI Taskflow REST APIs.
• Monitoring and audit logging of rule execution and scoring status.
• This wrapper handles complete lifecycle automation: rule registration → assignment → expansion → execution → scorecard generation, decoupling business logic from pipeline logic.

3. Self-Service UI & Business User Enablement

• Designed a self-service UI interface, backed by metadata, allowing business users to configure, assign, and reapply DQ rules without engineering dependency.

4. API-Based Execution & PDO Optimization

• Implemented fully parameterized DQ rule execution by calling Informatica IDMC CDI Taskflow via REST APIs, supporting dynamic runtime substitution of rule logic, targets and thresholds.
• Optimized execution using Pushdown Optimization (PDO), offloading compute to underlying databases for improved performance and reduced cost during validation at scale.

5. Monitoring, Reporting, and Operational Governance

• Developed interactive Power BI dashboards to visualize rule-level DQ scores, adoption trends, data domain coverage, and failed record trends with drilldowns.
• Designed reusable scorecard logic that seamlessly integrates with rule execution metrics, enabling traceable, auditable, and governance-aligned data quality reporting across domains.

Tech Stack: Python, PostgreSQL, Databricks, EC2, Power BI, Informatica CDGC, IDQ, Rule Engine

Project Description

• ONE IDENTITY Customer will be a single MDM solution for Boehringer Ingelheim, which will source data from various contributing systems to create a single golden record of a customer.
• One customer will also publish mastered information to different consumer systems of Boehringer-Ingelheim.
• There can be two types of source systems: one that provides data in batch mode, and the other that is integrated in real time. Source systems that provide data in batch mode are going to be integrated through the ETL process.

Role & Responsibilities

• Designed and developed complex ETL workflows using IICS, ensuring efficient data integration and validation across multiple data sources.
• Implemented data quality rules and cleansing processes using IDQ, resulting in significant improvements in data accuracy and completeness.
• Collaborated with business stakeholders to identify data requirements, create
  data mappings, and define data integration strategies.
• Conducted performance tuning and optimization of ETL processes, resulting
  in improved processing times and reduced costs.
• Created and maintained technical documentation, including ETL design specifications, data mappings, and process flows.
• Provided technical support to end users, resolving issues related to data integration, data quality, and system performance.

Tech Stack: IDQ, IICS, Oracle SQL, SQL Server, UC4, and GitHub.

Project Description

• WATTS application is workflow and task tracking system that tracks the customer
  requests for wide varieties of services such as Bundle-TV, Internet and Homelife
  etc.

Role & Responsibilities

• Involved in understanding the data model and preparing the inputs for ETL
  high level and low-level design document.
• Assisted in gathering requirements by performing ad hoc analysis of the requirements with the technology teams.
• Using Informatica design and code the mappings, jobs to process data from
  different source system to data warehouse.
• Worked with PEGA utility BIX extracts as a source for streaming.
• Involved in creating SCD tables in the data warehouse to load data from XML.
• Involved in unit testing and deployment of the code to production via Jenkins.
• Developed a PL/SQL procedure for validation purposes.

Tech Stack: Informatica PowerCenter, Oracle, SQL, SQL SERVER,JENKINS, WINSCP.