A data analytics team needs a single, enterprise-class platform that lets them perform extensive statistical modeling, build predictive models, and create interactive business-intelligence dashboards without moving data between separate tools. Which platform best satisfies these requirements?
Hadoop MapReduce
Apache Spark
SQL
SAS
SAS (Statistical Analysis System) is an enterprise analytics suite that unifies data management, advanced statistical procedures, predictive modeling, and business-intelligence reporting in one environment.
SQL is primarily a query language for relational databases; although some implementations add analytic extensions, it is not a full analytics platform.
Apache Spark is a distributed computing engine that includes MLlib for machine learning, but it generally requires additional components or third-party tools to deliver a complete BI solution and is not packaged as an all-in-one enterprise suite like SAS.
Hadoop MapReduce is a batch-processing framework for large-scale data workloads and provides no native statistical or BI capability without add-on projects.
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