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DAS42 Adds Managed Service Offering to its Suite of Data Technology Solutions

DAS42 Accelerates Growth With Acquisition of Elasticiti’s Data Analytics Consulting Team
New offering simplifies data stack maintenance by giving clients ongoing access to expert consulting teams

DAS42, a leading provider of full-stack data technology implementation and advisory services, has begun offering a Managed Service to help clients maintain and maximize the benefits of their modern data stack investment. The customizable service provides companies with ongoing access to DAS42’s deep bench of experts with certifications across best-in-class data technologies.

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“Without deep prior experience, it can be difficult to keep the complete modern data stack solution’s various technologies working together seamlessly as they should”

“Without deep prior experience, it can be difficult to keep the complete modern data stack solution’s various technologies working together seamlessly as they should,” said DAS42 CEO Nick Amabile. “Our Managed Service offering lets companies focus on their core business and avoid the costly investments that can be needed to effectively manage their data and analytics platforms.”

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DAS42’s Managed Service complements its FullStack philosophy for helping organizations meet their data challenges: to have an effective data analytics environment and a data-centric company culture, organizations need a full techstack of products overseen by a single team that is responsible for the entirety of their data flow. Enterprises of all sizes and growth phases need to build and maintain an infrastructure and a culture equipped to capture the vast amounts of variable data across the organization into a single source of truth and transform it into actionable intelligence that achieves business objectives.

DAS42’s Managed Service teams provide ongoing best practices review, architecture recommendations, performance/cost optimizations, user support, and administration. Maintenance, support, and service range from simple requests like adding new users to error handling and code reviews to ensure data analytics systems are functioning as efficiently and effectively as possible, and to accelerate their adoption across organizations.

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