Overview

Digital Transformation constitutes a new, challenging reality in all business sectors. Intracom Telecom's BigStreamer™ addresses Digital Transformation challenges of multiple industries, including Telecommunications, Financial Services and Utilities with a powerful suite of Big Data Solutions built on the latest technologies.

Our expert Data Engineers and System Administrators use BigStreamer™ to provide a rich set of functionalities, which include:

• Data Ingestion - an extensive Adapters Repository to seamlessly capture data from virtually any information source, including any existing data warehouse.
• Data Management - automated distributed tools that enable the transformation, correlation, enrichment, manipulation, security, anonymization and retention of data ingested into the platform.
• Data Analysis - prepared data can serve for data modelling, complex event processing, alerts & triggers generation and creation of sophisticated reports.
• Visualization - data visualization using BigStreamer BI or integrated with third-party applications and tools via open APIs to help create interesting graphical representations of the data.

BigStreamer can also be connected with Intracom Telecom's Cognitiva™ Enterprise-ready AI Application Suite to provide advanced analytics capabilities based on Machine Learning, Deep Learning and other Artificial Intelligence technologies.

Highlights

Petabytes of Data

BigStreamer Distribution ingests, processes and manages massive structured, semi-structured and unstructured datasets in real-time or batch mode

Advanced & Customizable Visualizations

BigStreamer BI explores and analyzes numerous types of datasets using business intelligence visualization

Milliseconds Responses

BigStreamer Cache in-memory database achieves millisecond response for time-critical applications

Turn Insights to Actions

BigStreamer Rules setup automated triggering of actions & alerts upon threshold crossings on any KPI

Regulatory Compliance

BigStreamer Trust Center controls security and privacy features on sensitive data and meet regulatory requirements

Open Interfaces

BigStreamer APIs make all information available to 3rd party applications for further processing or visualization

Unified Monitoring of HW, SW and data

BigStreamer Monitoring collects, analyzes and displays the most important information of the monitored systems in Big Data clusters

Cloud Enabled

BigStreamer platform is natively cloud enabled, which ensure faster deployment, agility and easy scaling of infrastructure

Applications

BigStreamer's ability to integrate with data sources and process enormous volumes of data, enables data analysts to create revealing reports and visualizations; thus, helping them shed light to pressing challenges. In addition, Cognitiva™ Enterprise-ready AI Application Suite can be leveraged in conjunction with BigStreamer in several Machine Learning, Deep Learning and Artificial Intelligence applications, covering divergent business needs from different industries, according to all principles of a modern data platform, such as:

Data Warehouse where large amounts of data from disparate data sources are aggregated and then stored structured in a unified data repository to support efficient querying, analysis, and eventually data-driven business decisions.

Data Lake where large amounts of structured and unstructured data in their raw, original, and unformatted form are stored in a centralized repository, leading an organisation to advanced insight gains from unstructured data.

Data Virtualization where the application retrieves and manipulates data without requiring technical details about the data, such as knowledge of the data format or the location where the data are physically located.

Data Mesh where the data ownership is distributed among different data domains within an organization; facilitating and accelerating the value extraction from data by applying domain-specific business knowledge dispersed throughout an organization.

Data Lakehouse where the best features from streaming and batch processing of both data warehouses and data lakes are efficiently combined, satisfying high performance and data integrity standards for advanced data analytics and machine learning workloads.

Collateral Files

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