Using Spark to Process Data Streams

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.

Data Integration with Spark

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.

Machine Learning Algorithm Training

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.

Interactive Analytics with Spark

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.

Apache Spark Development

Using Spark to Process Data Streams

Data Integration with Spark

Machine Learning Algorithm Training

Interactive Analytics with Spark