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Data is one of the most important resources for modern enterprises. Better analytics allow for a better understanding of customer requirements and market dynamics. The more data is collected, the more information can be extracted. However, information value extraction is limited by data processing speeds. Due to fast technological advances in big data management there is an abundance of big data systems. This leaves users in the dilemma of choosing a system that features good end-to-end performance for the use case. To get a good understanding of the actual performance of a system, realistic application level workloads are required.To this end, we have developed BigBench, an application level benchmark focused only on big data analytics. In this paper, we present the vision of BigBench 2.0, a suite of benchmarks for all major aspects of big data processing in common business use cases. Unlike other efforts, BigBench 2.0 will have completely consistent and integrated model and workload, which will allow realistic end-to-end benchmarking of big data systems. |
