Data unification at the scale of large enterprises requires domain expertise and world class data engineering capabilities. Tamr Professional Services deliver both to enable customers to enrich and operate their data effectively. The Tamr team utilizes a consistent methodology across deployments to enable the customer to effectively manage their data pipeline and drive business results, whether that’s saving money, increasing revenue, mitigating risk, or enabling R&D. Tamr Professional Services implement best practices developed from successful deployments to optimize each phase:

• Architect: Understand the customer’s existing infrastructure, and tailor the deployment by developing custom pre and post-processing
• Implement: Lead the initial training of Tamr’s models, maximizing the value of each subject matter expert
• Optimize: Define strategy for further optimizing and maintaining results
• Enable: Train / Certify key stakeholders on capturing continuous value from their data through analytics and the Tamr software

The Tamr Professional Services team is highly skilled in core data engineering principles, carrying advanced degrees (many PhDs) in data and technical fields including computer science, physics, and mathematics from top tier universities. This foundational knowledge of data engineering, along with expertise in implementing customer requirements, enables the Tamr software to be deployed in complex environments where a novel approach is required.

The Tamr team possesses domain expertise in areas that are critical to customers’ success, such as pharma, sales & marketing, procurement, and supply chain. This domain expertise has been accumulated within Tamr through a combination of hiring talent with industry experience, extensive experience building Tamr solutions for clients, and developing processes for sharing best practices throughout Tamr.

The close partnership established between the Tamr Professional Services team and the customer during the deployment results in the customer gaining a deeper understanding of their data, realizing increased engagement with data throughout the organization, and having a blueprint for maintaining the unified data required for impactful analytics