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.
What we do for Data Virtualization
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.
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
Expected results
- 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.
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