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Unified Data Platform Powered by dView's Data Pipeline Engine.

The data pipeline divides each data stream into smaller chunks that it processes in parallel, conferring extra computing power.

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Unified Data Platform

Construct a Data Lake, 360° Data View, or simply load aggregated data to the Data Warehouse, do it all with dView.io

Data Warehouse

Bring any data from a variety of sources in real-time to build a Single Source of Truth - Data Warehouse in minutes.

Data Lake

Effortlessly ingest both structured and unstructured data from Web Logs, Databases, Social Media, Cloud Applications, and more to build your Data Lake in minutes.

360° Customer View

Get a 360° holistic view of your customer data from various touch points: Mobile App, Website, Database, CRM, Support Tickets, Marketing Applications, and more.

Data Modeling

Optimize query performance by modelling data into analytics database. Using multiple sources, build complex joins and aggregates to create materialized views of data.

Capture Click Streams

Feature Clickstream data from mobile, web, servers, and more to study individual visits in real-time.
Understand customer psyche and uncover patterns by deeply analyzing user interactions and product engagement.

Messaging Queue

Realtime data ingestion into Messaging Queues like Kafka or SQS. Build Machine Learning Models, Recommendation Engine, Fraud Detection Modules, and more. Power personalised customer experiences.

Explore object behavior on an individual level of detail

Mapping out what your business goals and objectives are is the first step towards creating data that matters. with dView.io

  • Real time reporting: Updates occur in real-time with new incoming data.
  • Drill Down: Every visualization is fully interactive and supports drill down.
  • Alerting Out of the box: Alert on custom-defined changes in data.
  • Team collaboration: Create and share drag-and-drop dashboards with your team.

AcumenCog powers their business analytics with dView.io

Data virtualization has enabled companies to gain agility, beyond what was possible using the traditional data integration toolbox.

Data virtualization has become key for integrating the data from big data sources and the existing enterprise data, to provide a holistic view.

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