Orzota BigForce is designed to run big data analytics applications on Apache Spark and Hadoop in the cloud. Using a cloud infrastructure can dramatically lower the time to get a project off the ground. Clusters can be spun up on demand as required, lowering operations cost.
It is built to run on public clouds like AWS and Azure, private clouds like Rackspace as well as bare metal infrastructure within a Data Center.
The goal of Orzota BigForce is to simplify the creation and management of big data analytics applications by automating many of the tasks required to ingest, transform and analyze data. It provides advanced machine learning algorithms and support for statistical environments such as R and Python. Support for ad-hoc visualizations and reports for business users means an end-to-end ability to handle big data based applications.
Orzota provides BigForce as a managed service to manage not just infrastructure or platform software but also your big data analytics applications. This enables organizations to focus on results without worrying about the complexities and day-to-day tasks required to manage Big Data. Orzota offers flexible support options ranging from eight-hour shifts to complete 24×7 coverage.
The BigForce dashboard shows relevant metrics about your Hadoop or Spark clusters and jobs; optimize the creation and management of your clusters by viewing their usage patterns.
Alerts and notifications quickly draw your attention to the most important tasks and issues and can be the starting point for debugging problems.
The first step in creating the new data architecture is ingesting data from the different silos within the organization. Orzota BigForce easily integrates data sources such as SQL, unstructured logs or real-time feeds into the Hadoop cluster. Integrate social media data from twitter as well as third-party platforms to harness the power of Hadoop to obtain deep insights. With support for technologies such as Flume, Sqoop, Kafka, Storm and Spark Streaming as well as an easy to use interface, there is no need for manual, complex setup and editing of configuration parameters.
Big Data Analytics
The process of developing Big Data Analytics applications involves data cleansing and transformation before analytics. Orzota BigForce supports Hadoop MapReduce, Spark, Hive, Pig, Cascading – the standard tools used for data cleansing and transformation. Support for real-time streaming using Apache Spark or Storm is included. Build your big data analytics and machine learning applications using Python, R or Mahout.
The job management module provides you views on what Big Data jobs have been deployed, scheduled, and monitoring while they are running.
Our managed services offering handles data quality, data transformation and a variety of other complex workflows required for data transformation, cleansing and analytics. Our workflows module let’s you see the workflows we’ve created leveraging our pre-built components.