Predictiveworks leverages the power of Apache Spark for scalable & distributed in-memory data analytics and machine learning.
Predictiveworks adds Association Rule Mining, Factorization Machines, Markov Models, Sequence Mining and more to Apache Spark.
Predictiveworks is a highly concurrent, distributed and resilient application based on Typesafe Akka.
Predictiveworks adds Event Tracking capability to Apache Spark based on Elasticsearch.
Predictiveworks unifies the data access to Cassandra, Elasticsearch, HBase, MongoDB, Parquet and JDBC data sources.
Predictiveworks offers a common REST API to ingest data, control machine learning and get analytics results.
Predictiveworks leverages a common data structure server to share mining results & predictive models.
Predictiveworks functionality can be accessed leveraging the Elasticsearch API.
Distributed real-time search & analytics platform
Open source NoSQL document database
Fast & distributed data structure server
Scala integration layers on top of Hadoop
Actor-based runtime environment for message-driven applications
REST/HTTP integration layers on top of Akka
Scalable, highly available NoSQL database
Distributed & scalable Hadoop database
Distributed publish-subscribe messaging system
Common columnar storage format for Hadoop
Distributed in-memory processing large-scale data processing
Scalable machine learning library
SQL-based query engine for distributed data
Complex event processing
We prepare your data for optimal use with Predictiveworks.
We integrate Predictiveworks. into your technical environment.
We adapt Predictiveworks. to your specific analytical needs.
Discover and leverage the most relevant
hidden relations in large scale datasets.
Leveraging context-sensitive information
is crucial for personalized predictions.
Uncover the intents of human behavior and reach the ultimate customer understanding.
Find anomalies in large-scale datasets and human behavior for advanced risk reduction.
Find relevant similarities in activity sequences and identify customers by their journey.