Best On-Premise Data Matching Software

(Bank CFO) “I don’t have confidence and trust in our data. We keep discovering hidden risks”. Since 70% of data initiatives fail due to unreliable data (Gartner research), are you risking your reputation by trusting the accuracy of your data that you share with your business stakeholders and partners? Data Trust Scores must be measured in Data Lakes, warehouses, and throughout the pipeline, to ensure the data is trustworthy and fit for use. It typically takes 4-6 weeks of manual effort just to set a file or table for validation. Then, the rules have to be constantly updated as the data evolves. The only scalable option is to automate data validation rules discovery and rules maintenance. DataBuck is an autonomous, self-learning, Data Observability, Quality, Trustability and Data Matching tool. It reduces effort by 90% and errors by 70%. "What took my team of 10 Engineers 2 years to do, DataBuck could complete it in less than 8 hours." (VP, Enterprise Data Office, a US bank)

Senzing® entity resolution API software provides the most advanced, affordable, and easy-to-use data matching and relationship detection capabilities available. With Senzing software, you can automatically resolve records into common entities in real time as new data is received. The complete view of all records related to every person or organization, across all of your internal and external data sources, can help you reduce costs and enable new revenue opportunities. Companies use Senzing entity resolution API to provide highly accurate views of people, organizations, and their relationships. You can deploy the Senzing entity resolution API on premises or in cloud-native deployments. Data remains in your ecosystem and never flows to Senzing. A free proof of concept can be completed in one day on AWS or on BareMetal. Senzing makes human-intelligent decisions without any pre-training or pre-tuning.