AI and analytics don’t fail for lack of algorithms—they fail on messy data, missing lineage, and brittle pipelines. Informatica IDMC (Cloud Data Integration, MDM 360, Data Quality, Data Governance & Catalog, Mass Ingestion, API/App Integration) gives you the fabric. YASH brings the architecture, build discipline, and run-ops to land value quickly and keep it durable across Salesforce, SAP/Oracle, Snowflake, Databricks, AWS, and Azure.
Who it’s for
Enterprises with multi-source truth, regulatory pressure, and high stakes for data quality (Manufacturing, HLS, BFSI, Retail, Energy).
Outcomes
trusted golden records, governed self-service, faster time-to-data, and pipelines resilient enough for AI/Agentforce-scale automation.
What we deliver (solution pillars)
Cloud Data Integration (CDI & CAI)
Master Data Management (Customer/Product/Supplier/Reference 360)
Data Quality (DQ) & Observability
Governance & Catalog (CDGC / EDC + Axon-equivalent workflows)
Ingestion & Events (CMI / CDC)
AI/ML & Analytics Readiness
Salesforce & App Ecosystem Integration
Cloud Data Integration (CDI & CAI)
- Design scalable ETL/ELT and API/App integrations across SaaS, on-prem, and data lakes/warehouses.
- CDC and near–real-time patterns for low-latency feeds into analytics and apps.
Master Data Management (Customer/Product/Supplier/Reference 360)
- Match/merge, survivorship, and hierarchy management with stewardship workflows.
- Publish golden records to Salesforce, SAP, commerce, and marketing systems.
Data Quality (DQ) & Observability
- Profiling, rules, standardization, and monitoring tied to business SLAs.
- Scorecards that connect quality to downstream KPIs (conversion, OTIF, loss ratios).
Governance & Catalog (CDGC / EDC + Axon-equivalent workflows)
- End-to-end lineage, policy catalogs, business glossaries, and data ownership.
- Access workflows and “trust labels” for self-service with control.
Ingestion & Events (CMI / CDC)
- High-volume ingestion from databases, files, and streaming; replay and DLQ patterns.
- Event-first contracts to decouple producers/consumers.
AI/ML & Analytics Readiness
- Feature feeds and model-ready tables with drift checks; privacy-by-design pipelines.
- Contracted data products for Snowflake/Databricks with cost and freshness guards.
Salesforce & App Ecosystem Integration
- Clean master/customer views into Sales, Service, Marketing; product/price governance into CPQ/commerce.
- Tie-ins to MuleSoft/Boomi where needed—one spine, not new spaghetti.
How we engage (offerings).
Accelerators & Centers of Excellence
Golden Record Kit
prebuilt match/merge rules, survivorship policies, and hierarchy models for Customer/Product/Supplier; steward playbooks.
DQ Rule Library
postal/phone/email standards, product taxonomy validators, regulatory checks (e.g., addressable PII flags).
Lineage & Trust Dashboards
source→consumption maps, policy tags, data health scorecards, and “blast radius” views.
CDC/Streaming Recipes
patterns for change tables, out-of-order handling, idempotency, and replay.
Salesforce Clean Start
contact/account dedupe, account hierarchies, and data contracts for downstream AI and journeys.
AI-Ready Data Products
templated Snowflake/Databricks tables with cost/freshness guardrails and business metadata.
Agentforce & AI synergy (when Salesforce CRM is in scope)
Agent-safe data
expose governed, contract-first APIs so Agentforce can act on clean master data (renewals, service entitlements, offer decisions).
Autonomous data ops
agents propose DQ fixes, flag drift, and open steward tasks with approvals and audit trails.
Closed-loop activation
golden profiles push to Marketing/Sales/Service; Agentforce executes outreach or service plays and feeds back outcomes.