Data
Virtualization

Solving data integration challenges in real-time

Enterprises often try to break down silos by extracting disparate data into central data stores, such as data marts, data warehouses, and data lakes. This is costly, adds latency to the data, requires accurate metadata, and needs to be co-located. Virtualization, on the other hand, can integrate data in real-time even when the data has not been merged. Torry Harris can help integrate all your data through virtualization using industry-leading tools. By harnessing the power of virtualization, we empower users to work with all kinds of data interfaces in real-time, simplify and expedite analytics on data stored in multiple systems and applications anywhere.

How can we help

Establish a data virtualization architecture

We’ll study your current data management and governance practices, the data sources, and the integration challenges and then recommend a data virtualization solution based on the right product fit.

Align data virtualization with integration

Align your integration framework with data virtualization in terms of enabling API discovery of virtualized data, and secure exposure of APIs on an API gateway through integrating with an API management platform.

 

Build connectors

Develop connectors to your proprietary applications based on the SDK of your chosen data virtualization platform over and above out-of-the-box connectors provided by the platform.

API and virtual tables configuration using data virtualization

Develop APIs and define virtual views using the data virtualization tooling. We will integrate them with your analytics tools.

Data virtualization in action

Use case 1

Tableau dashboard acceleration

Problem statement

  • The lengthy data preparation phase for Tableau visualization requirement
  • Poor user experience on Tableau dashboard due to query performance issue

Solution

  • Data virtualization to accelerate data preparation for BI visualization requirements
  • DIY-based development for BI teams
  • Acceleration of Tableau queries through Smart Query (Summary) Acceleration technique

Expected results

  • Achieve 50-80% time saving for BI project delivery
  • Tableau dashboard loading within five seconds, irrespective of the complexity

Use case 2

Data as a Service (DaaS)

Problem statement

  • Lengthy java development process to expose data sets as APIs
  • The distributed access control setup

Solution

  • Data virtualization to expose data sets as APIs out of the box
  • Centralized role-based access control to enforce data security at the view, column, and row level
  • Achieve 50-80% time saving on exposing data sets as APIs
  • Centralized, granular access control

Our approach to data virtualization

Data virtualization is based on the principle of virtual tables. It allows architects to create a virtual data model and map them to a variety of data sources ranging from raw data, files, web services, legacy applications, cloud services, and other proprietary applications through an extensible adapter framework. Data can be accessed through both APIs and SQL (on virtual tables). Through the mapping of interfaces, both read and write access to data is supported. Data virtualization bridges the best of application and data integration through a unified technology platform.

 
 
What data capabilities, data-driven value and insight do you need? What is our expertise? What tools do we use?
Customer 360, Partner 360, Anything 360
  • Data virtualization-based solution to implement Anything 360 using virtual tables.
  • Aggregating disparate data sources.
  • Building connectors to implement Anything 360.
  • Denodo
  • JBoss Data Virtualization
  • Ab Initio
Modernizing your legacy data warehouse
  • Replace your legacy data warehousing solution with data virtualization and virtual data marts.
  • Establish data virtualization as the standard enterprise-wide semantic data layer.
  • Denodo
  • JBoss Data Virtualization
  • Ab Initio
API enablement of legacy for internal and partner access
  • Expose data sets and other data sources as APIs using the data virtualization platform.
  • Identify and expose APIs securely on an API gateway to third parties.
  • Denodo
  • JBoss Data Virtualization
  • DigitMarketTM API Manager
Analytics and business intelligence
  • Modernize your traditional analytics solutions with data virtualization.
  • Build custom dashboards and visualization solutions driven by data virtualization.
  • Integrate with AI and ML tools for predictive and prescriptive analytics.
  • Denodo
  • JBoss Data Virtualization
  • 4Sight
Cloud-to-cloud integration / cloud-native data virtualization
  • Integrate data from multiple cloud sources (SaaS and PaaS Applications), including data from proprietary applications hosted on IaaS.
  • Building cloud-native solutions (microservices) using container frameworks alongside data virtualization for dynamic scaling.
  • Denodo accelerator built by THIS - Helm Charts for deploying Denodo workloads on Kubernetes cluster
  • Azure, Google Cloud Platform and Amazon Web Services

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