Cloud Data Integration & Engineering

Why Best

• Lower TCO by up to 65% -  Get automated cost control with our intelligent optimization engine.
• Spend up to 80% less time - save design and development time with AI-powered low-code and no-code tools.
• Reduce complexity - Use a single platform for virtually all integration patterns such as ELT, ETL, and Reverse ETL.

Solution Capabilities

Easy:

• Single, easy-to-use, unified no-code canvas design time experience for all data integration and data engineering needs.
• Easy drag and drop design experience, 100+ prebuilt functions & templates for every data engineering use case.

Efficient:

• Automate and accelerate the design and development of data pipelines with auto-mapping.
• Integrate data on virtually any cloud with ETL, ELT, Spark or a fully managed serverless option.

Cost-Effective:

• Maximize the cost-performance (FinOps) of data pipelines with a single design time experience.
• Pushdown with SQL ELT on AWS, Azure, GCP, Snowflake and Databricks with 50x performance improvements.

Customer Value

One of the largest providers of high-quality rental homes in the United States reduced pipeline design time by 66% and saved $50,000 in hardware cost-saving. There was zero downtime while running 36 task flows and over 1,300+ mappings with Informatica CDI.

Why Best

• Enables ~50X faster processing, with zero data egress charges through SQL ELT for AWS, Azure, Google, Snowflake, ORACLE, and Databricks targets
• Support the broadest array of connectors with the best-in-class performance
• Support cloud data lake (CDL) to cloud data warehouse (CDW) and CDW to CDW use cases.

Solution Capabilities 

Easy:

• Simple onboarding for first-time users with guided experience to build full ELT pipelines
• Specialized experience to accelerate development for SQL ELT pipelines
  

Efficient:

• Improve developer productivity by 28% by designing mapping using the intuitive Informatica graphical mapping designer
  

Cost-Effective:

• Reduce latency by 63% and data egress cost by $50,000

Customer Value

Paycor partnered with Informatica to generate reliable data-driven insights across the company. Reduced data wrangling time by 90% and reporting cycle from months to weeks. Improve the productivity of data engineers with AI-powered intelligence and automation.

Experience

Agnostic ELT Experience

• Single experience for all execution patterns – ETL and ELT, and for all ecosystem and connectors
• Suited for workloads that can be re-purposed for different ecosystems or different execution patterns as needs change or evolve

Cloud Ecosystem focused Experience

• Purpose-built for SQL ELT execution only
• Suited for workloads designed from inception to run on a specific cloud ecosystem in ELT mode

Why Best

• No-code wizard-driven interface to sync data from data warehouse destinations to data producers such as marketing apps
• Flexible configuration on sync strategy from a single object, multiple objects, or queries to define data models
• CLAIRE-powered automapping of fields and built-in scheduling & orchestration

Solution Capabilities

Easy:

• Simple wizard-based approach to enable quick data sync between any data sources

Efficient:

• Robust capability in defining data extraction strategy and built-in orchestration for operationalization of reverse ETL pipelines

Cost-effective:

• Cut down delays by democratizing data availability and multiplying the integration workforce with a wizard-driven interface.

Why Best

• Quickly identify & resolve data inconsistencies with integrated Cloud Data Quality
• Build enterprise-scale AI-ready data pipelines with embedded data quality rules
• Consistent experience and unified metadata across all cloud services.

Solution Capabilities

Easy:

• Embed enforcement of quality rules into data pipelines and business processes
• The frictionless user interface, including low-code support and inline testing, reduces rule development and implementation by 80%

Efficient:

• CLAIRE-based recommendation of Data Quality Rules into CDI mapping canvas.
• Automate application of data quality rules across sources in on-premises and multi-cloud hybrid environments.
  

Cost-Effective:

• Ensure consistency of data quality with centralized rules management and execution.

Data masking is essential for securing data privacy across multiple sources using reusable mapplets tailored for specific data like names and emails. It offers configurable options such as repeatable processes, seed values, and performance enhancements to ensure comprehensive data protection.