Precisely, the global leader in data integrity, today announced availability of the Spatial Analytics and Data Enrichment services for its leading Precisely Data Integrity Suite, as well as the release of a new private API for mainframe replication. The new offerings allow customers to use cloud-native spatial APIs to produce more scalable and performant spatial apps, enrich data with critical third-party datasets that add context and reveal new insights for location data, and access more flexible deployment options for mainframe replication.
With these additions, the Data Integrity Suite now delivers a complete set of capabilities that seamlessly connect through its Data Integrity Foundation. Featuring a shared data catalog, machine-learning-powered intelligence and hybrid execution agents to run workloads in any data environment, the Data Integrity Foundation is key to accessing the most critical capabilities needed for trusted, AI-ready data. This includes Data Integration, Data Observability, Data Governance, Data Quality, Geo Addressing, Spatial Analytics, and Data Enrichment.
Discover the power of business-centric spatial analytics
Every organization’s data has a location element that can be leveraged for deeper insights, but first, the right tools are required to uncover its value. With the Data Integrity Suite Spatial Analytics service, customers can discover patterns, trends, and relationships between location-based datasets and easily share valuable findings through enriched business processes, maps, and out-of-the-box reports to accelerate revenue growth.
With these new capabilities, organizations across industries are empowered to:
- Leverage enhanced location-based context for more accurate risk assessment, optimized resource allocation, and improved property-related performance evaluation
- Find the right audience for new services and produce more accurate, targeted, and timely customer offers with advanced location analytics
- Design custom applications via access to a diverse set of APIs
Maximize data potential with easy enrichment
By appending trusted and relevant third-party datasets, companies can transform their self-generated data into complete, consistent, and reliable business assets that lead to more accurate predictions, fuel trustworthy models, and empower innovation. However, combining first-party data from internal sources with third-party data is typically a complex and time-consuming process.
With the Precisely Data Integrity Suite Data Enrichment service, customers can:
- Save time and resources by quickly enriching data with reliable datasets that are easy to use and require little to no preparation
- Enhance the value, accuracy, and completeness of business data by appending relevant context from curated datasets
- Identify trends, patterns, and anomalies that might not be apparent with first-party data alone
Unlock the value of mainframe data in private environments
A new Private Mainframe Replication API, part of the Data Integrity Suite Data Integration service, provides a container-based solution for mainframe replication. It gives users the freedom to move data according to their needs, whether the target environment is a private data center, an on-premises system, or a hybrid environment.
This is particularly significant for businesses in highly regulated industries, such as financial services, banking, and insurance, which can face stringent deployment requirements. The new offering allows users to meet internal and external deployment needs while accessing valuable mainframe data for advanced analytics, AI, and other critical business initiatives.
“Customers can now access a complete range of data integrity capabilities in the way that works best for their business, allowing them to quickly and easily fuel their organization with highly trusted data,” said Chris Hall, Chief Product Officer at Precisely. “We are proud to lead the way in delivering a converged data integrity solution that uniquely combines everything from data integration to spatial analytics and data enrichment – critical elements for ensuring reliable AI and advanced analytics outcomes.”