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Thanks to the profound insights delivered in real time by Oracle Big Data Appliance, we have increased our ability to respond to the needs of more than 1 million loyalty card holders who regularly use our retail network. We also expect to reduce our transportation costs.
mStart is a Croatian provider of business and technological IT solutions oriented towards development, implementation, integration, and IT support for the agriculture, industrial, and retail sectors. mStart is a part of Agrokor Group—which operates more than 100 companies across several countries—and is the go-to point for all the group’s technology needs. The Agrokor Group is predominantly focused on the production and distribution of food, beverages, and retail products sold under the Konzum and Mercator brands, and among its top goals are reducing energy, water consumption, and carbon dioxide (CO2) emissions.
We chose Oracle Big Data Appliance predominantly because of its seamless integration capabilities with the Oracle technologies that underpin our customers’ retail experience. Also, the environmental benefits of deploying an engineered system help us drive sustainability throughout the group.
mStart was formed in 2010 when the Agrokor Group’s IT business was set up as a separate entity with the aim of optimizing IT investment, bringing new services to the competitive market, and reducing the group’s environmental impact through better use of technology. The Agrokor Group is the largest privately owned company in Croatia and one of the leading companies in Southeast Europe. Agrokor has established an Environmental Management System which is certified according to the requirements of the international ISO 14001:2004 standard.
mStart selected Oracle Platinum Partner Neos for its Oracle Big Data Appliance implementation.
“Neos consultants provided us with technical expertise for using big data in the retail industry, deployed the Oracle solution within the expected budget and timeframe, and continue to work with us on several use cases which will enable further reductions in transportation costs using unstructured data sources,” Svetina said.