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Enterprise data centers (EDCs) are critical infrastructure to large enterprises, government agencies, research institutions, etc. They are used to support a variety of off-the-shelf and customized services. EDCs are different from cloud data centers (CDCs) in two major aspects. Firstly, an EDC is usually built over time and consists of old and new equipment. Secondly, the type of services and applications in EDCs are quite different from those in CDCs. Therefore, we expect that the traffic characteristics in EDCs would also be different from those in CDCs. While most existing data center measurements were from CDCs, we performed extensive traffic measurement and analysis in an EDC that provided multiple services to over a million users. We present the data center architecture, measurement methodology, measurement results, and analysis. The results include traffic matrix, traffic distribution, flow characteristics, and TCP characteristics. Our research reveals that the traffic characteristics in the EDC are indeed quite different from the reported results in CDCs. For example, the traffic matrix tends to be sparse rather than all-to-all. Based on the analysis we provide a few guidelines for EDC design, optimization, and anomaly detection. As the first most extensive study on EDC traffic, our work provides valuable information to future EDC design and implementation, and also helps researchers develop insights into the differences and similarities between EDCs and CDCs.