Big Data Platform

Delivering results in weeks, not months

End-to-end Integrated Solution

Big data is a set of techniques and technologies that require new forms of integration to uncover large hidden values from large datasets that are diverse, complex and of a massive scale. It cannot be handled by standard database management systems or software technologies.

We have developed technology for high-speed and low-cost for complex data processing and a high productivity development environment for data store, utilization and availability without service interruption.

We approach with the sophisticated pattern analysis and a layered framework for assuring cloud computing, file, data and network encryption techniques. We provide technology and a platform to manage and transfer big data securely at any scale to fit your business needs.

 

  • Rapid provisioning
  • Customized reports and dashboards
  • Mobile friendly presentations
  • Integration with existing environment
  • Unified data lifesycle across your organization
  • Data Security compliance maintenance

Apache Spark Ecosystem

Big data is a set of techniques and technologies that require new forms of integration to uncover large hidden values from large datasets that are diverse, complex and of a massive scale. It cannot be handled by standard database management systems or software technologies.

We have developed technology for high-speed and low-cost for complex data processing and a high productivity development environment for data store, utilization and availability without service interruption.

We approach with the sophisticated pattern analysis and a layered framework for assuring cloud computing, file, data and network encryption techniques. We provide technology and a platform to manage and transfer big data securely at any scale to fit your business needs.

Big Data Lifecycle Management

As an integrated solution, the platform allows us to manage the entire Big Data Lifecycle, providing all data processing steps from raw data to integrated dashboards.

  • Data collection: gathering static and streaming data from heterogenous sources
  • Data Preparation: Clean-up, Aggregation and Transformation
  • Data Analytics and Machine learning algorithms
  • Reporting and Visualization: Analytical applications and custom Dashboards

Big Data Reporting and Visualization

The platform's data processing results can be provided in various customized formats that fit client's requirements. Results can be visualized in custom reports, graphics, dynamic mobile friendly dashboards or provided as data files and data streams. With API engine, the data processing results can be integrated into client's business applications environment.

  • Get overview of your business processes in near realtime
  • Visualize your data with robust reporting and graphic presentation tools
  • Access your dashboards from mobile devices
  • Customize your dashboards to fit your business needs

Solving Problems

How the Platform helps businesses solving data processings issues

Compliancy

Sending data to the cloud for processing might violate government, enterprise or liability policies (financial records, personal data, internal data etc.)

Solution:

Data will never leave your datacenter premises

Speed

Huge amount of data requires significant investments in networking portion (hardware, traffic, reliability options, latency optimization options)

Solution:

Data will be processed on your datacenter premises, as close to the sources as possible

Security

Sending data to the third party and public cloud significantly increases possibilities of data leaks, intrusions and attacks

Solution:

Data will be stored and transmitted only within protected internal perimeter

Business

Giving the data away to the third party and public cloud opens data minig possibilities for the third parties that might threaten your business integrity

Solution:

Data will be accessed only from within your enterprise controlled environment

Compatibility

In some cases, integrating data from different sources and customizing algorithms and applied models require significant tuning and optimization on the processing side, which might be difficult or impossible on the shared platforms

Solution:

In-house platform can be customized to accommodate any requirements and naturally integrated to the in-house business environment