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We can build Apache Spark applications in Java, Python or Scala that analyze multiple data streams at the same time, such as financial transactions. These data streams can then be analyzed across the cluster to detect fraudulent behavior.
Through the use of Apache Spark, we can reduce the time and cost needed to extract data from different systems, transform it by a cleaning and standardization process, and then load it into another system to analyze the data and report on it.
Our Apache Spark apps can train software to find more efficient algorithms over large sets of data. Since Spark stores data in memory rather than the hard drive, our developers create applications that can take solutions from known data sets and apply it to unknown data sets rapidly.
Whether a business is in stocks, sales or production, dynamic data exploration is a must: whether via SQL or another method, a system must respond and adapt to repeated similar queries. Our team can use Spark for this ideal purpose because of its ability to respond swiftly.
Drop us a line or give us a ring. We love to hear from you and are happy to answer any questions.
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