Using the Tamr API to Manage Dynamic Information

Connecting and enriching data is a worthy challenge for information-driven enterprises, but data management in the enterprise isn’t a one-time project. Data is dynamic. Almost as quickly as data sources are understood and connected, new information will emerge from various parts of the organization. Here are just a few examples of trends that are impacting corporate data management requirements:

• Moving to the Cloud
• More companies are migrating to SaaS applications such as Salesforce.com and Workday.com. With both companies projected to grow at greater than 30% over the next year, this trend is helping to move customer data to cloud-hosted applications and compelling businesses to conform their data to the standards of these applications.
• New External Data Sources
• What if businesses could understand their prospects’ buying behaviors using external information? Acxiom and other third party information providers make it easier than ever for companies to understand buying preferences of their prospects and customers.
• Mergers & acquisitions
• M&A activity complicates data connection by adding even more heterogenous data sources that need to be managed.

The trends above are largely driven by strategic expectations about how better data management will create competitive advantages and improve quality of service. To make this work, organizations need to be able to execute. They need a nimble way to continuously connect and enrich data as it changes, or else much of the value of these data investments will be lost.

The Tamr API enables organizations to apply expert-guided machine learning to help enrich and connect data continuously. Tamr’s RESTful API supports SaaS, on premise, and hybrid system deployments, making it easy to connect and work with data wherever it is deployed.

To better understand how Tamr enables dynamic management of data, let’s look at two forms of integration made possible by Tamr’s API.

Aggregation

Whether the data is stored on-premise, in the cloud, or a combination of the two, organizations need to be able to take inventory of the information generated by these disparate systems and then to reconstruct the connections between the data. With the Tamr API, organizations can receive data from multiple systems in real time, evaluate the data for changes, and consolidate information to one system. Consider a large multi-national conglomerate that manages supplier relationships and data across hundreds of ERP systems. For operational reasons, it’s not immediately feasible to consolidate to just one system, and as a result, the entire detail of each supplier relationship is often spread across several systems. The Tamr API allows us to aggregate this information, and in turn, create a unified view of suppliers that can be used by downstream applications.

Aggregation workflow

1. Data is updated or added to an external system.
2. The updated data is matched vs. Tamr.
3. Matched records within Tamr added or changed within Tamr.

By using the Tamr API for aggregation, organizations maintain up-to-date referential data to power downstream analytics. The Tamr API ensures data consistency and provides the referential lookup that facilitates reporting across multiple systems.

Correlation

Electronic Health Records (EHR) incentives programs are driving the rapid adoption of online systems by doctors and hospitals to store and share patient data securely and electronically. This trend is helping to drive Health Information Exchange, the process by which important patient information is shared with other caregivers, to both drive costs down and improve quality of patient care.

One form of Health Information Exchange is the Query-Based Exchange. Consider the situation where a patient’s care must transition from one hospital or caregiver to another. Significant cost savings and improved patient health are possible when the patient’s treatment information is shared between the hospitals. For example, redundant CT scans and chest x-rays could be avoided, thereby minimizing test costs and exposure to radiation.

Correlation workflow

1. Patient visits Hospital 1 for first time. While at the hospital, the patient receives a CT scan and chest x-ray.
2. Patient is transferred to Hospital 2 for continuation of their care. Hospital 2 queries the health records of the patient.
3. When record matches found, Hospital 2 can request detailed record data from the Hospital that originally provided care to the patient.

The key benefit here is better patient care through improved sharing of treatment information. Correlation is ideally suited for Tamr matching capabilities and the Tamr API, as it allows for complex workflow processing where data needs to be protected until shared.

Summary

In summary, Tamr’s Match API provides the capability to correlate data in real time. With it, businesses can drastically improve the availability and completeness of information to help make the best, most informed decisions.

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