Ralf Schricker
About Ralf Schricker
Ralf Schricker is the Teamlead Inside Sales Business and DWH at Exasol, where he has worked since 2011. He has a background in inside sales and has contributed to the success of notable companies by utilizing Exasol's advanced analytics capabilities.
Work at Exasol
Ralf Schricker has been employed at Exasol since 2011, where he serves as Teamlead Inside Sales Business and Dwh. His role involves overseeing sales strategies and supporting clients in leveraging Exasol's analytics capabilities. Under his leadership, the team contributes to real-time data analysis for major clients, enhancing their operational efficiency and decision-making processes. Exasol is known for its high-performance database technology, recognized as the fastest in TPC-H Benchmark tests.
Previous Experience at Och
Before joining Exasol, Ralf Schricker worked at Och as Vertriebsinnendienst from 2005 to 2009. During his four years in this role, he was based in Mexico City, Mexico. His responsibilities included supporting sales operations and customer relations, which provided him with valuable experience in the sales domain.
Experience at Phocus Direct Communication Gmbh
Ralf Schricker held the position of Inside Sales Professional at Phocus Direct Communication Gmbh from 2010 to 2011. In this role, he focused on Vertriebsunterstützung, contributing to the sales support functions of the organization for a duration of 11 months in Nuremberg, Bayern, Germany.
Client Contributions
Throughout his career, Ralf Schricker has contributed to the success of notable companies such as Adidas Group, Sony Music, and Xing. His work at Exasol has enabled these organizations to utilize advanced analytics capabilities, thereby improving their business intelligence and data-driven decision-making.
Team Contributions and Technology
Ralf Schricker is part of a team that supports real-time data analysis for major clients, including IMS Health and Olympus. His work involves utilizing Exasol's database technology, which has been recognized for its speed and efficiency in handling large datasets.