AxonData's SOMMA

AxonData's SOMMA

AXONDATA's flagship product is the SOMMA Analytics Platform, which has the following key features: multicloud operation, high-performance big data processing, structured and unstructured data handling and analysis, API, connection to multiple systems and data bases, ingestion of various data types from multiple sources, all main analytical processing tools and algorithms embedded, and intuitive interface. SOMMA has two main building blocks: SOMMA core (analytical backend) and SOMMA Studio, which is the application development interface. SOMMA Technologies: • Big Data / HPC: Apache Spark, Apache Tika. • Machine Learning and Deep Learning: Spark ML, MLib and BigDL, Scikit-learn, Gensim, NLTK, Tensor Flow, Keras, DAAL. • Native Storage (datasets and files): MongoDB. • Connections with other banks: MySQL, Cassandra, Hive, Redshift, Hadoop, S3, others.

*Please note that member solutions are often customizable to meet the needs of individual enterprise end users.

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SOLUTION FEATURES

  • High Performance Computing
    SOMMA has the ability to process data and perform complex calculus at high speeds.
  • Ingestion of various data types from multiple sources
    SOMMA is able to read data from TXT, XLS, CSV, DOC, PDF and many other types. Also, through its API and connectors, it can send and receive data to and from many different systems.
  • Knowledge Discovery from Database (KDD) Process Flow
    SOMMA has already embedded the whole KDD flow, including data preparation, data mining and validation.
  • Intuitive Interface
    SOMMA Studio is our application development interface, designed to provide a minimalist dev environment, facilitating and accelerating the test and deploy of Big Data Analytics solutions.
  • Multicloud
    The SOMMA core can be deployed in various public and private clouds, whilst SOMMA Studio runs over web browsers, providing portability and ease of use.

CATEGORIES

BrazilIntel® Xeon ScalableCSP - Amazon Web ServicesCSP - Microsoft AzureKerasTensorFlowCross-IndustryManufacturingRetailModels can be trained - data input only requiredModels can be trained - online learningModels can be trained - requires labeled dataModels cant be re-trained - Inference onlyAI Platform as a Service (AI PaaS)Linux Intel® Data Analytics Acceleration Library (Intel® DAAL)Intel® Distribution for PythonIntel® Math Kernel Library (Intel® MKL)LSTMOtherData AnalyticsMachine Learning