Neoflex takes part in the Big Data Forum 2018
“Transportation expenses represent one of the components of the price for goods. Reduction in these costs enables companies to maintain a high level of profitability and obtain a competitive advantage in the market. And Fast Data technologies allow them to reach these goals quickly and efficiently”, — said Alexander Ponosov when presenting his report.
This report contains a solution developed for the largest freight forwarder in Russia. It is intended to enhance efficiency of cost planning, transportation forecasting accuracy and operational analysis of stock balances. With this solution, more than 500 operations are processed every second, which allows real-time forecasting of loading for 180 warehouses all over Russia for a week ahead within the accuracy of specific freight. The solution architecture has been developed using Hortonworks Data Platform with Apache Spark, Hadoop, Kafka and SnappyData database.
This is the seventh Big Data Forum hosted by Open Systems Publishing House. The event proved itself to be the main one of the year for the specialists in the field of big data and analytics. It represents the platform bringing together experts seeking opportunities to use large data arrays accumulated by many companies and make them valuable assets contributing to business development. About 400 representatives of companies from different industries, both from among IT-service consumers and IT-providers, took part in the Forum.
Top specialists and leaders in their field in data handling, IT directors and business leaders delivered their reports. This year the Forum was noted not only for the spread of issues covered in the programme, but also for discussion formats – from the plenary session with reports to thematic sessions, round tables and workshops. Thus, the participants took a great deal of interest in the discussion of the DataOps topic, new for the IT-market, the agile-approach to data handling, and discussion of prospective ideas and problems of retail business digitization, artificial intelligence and computer-aided learning as well as in-depth coverage of the issues associated with the efficient data management based on Data Governance.