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.