Data Virtualization: The Modern Data Integration Solution

Organisations continue to struggle with integrating data quickly enough to support the needs of business stakeholders, who need integrated data faster and faster with each passing day. Traditional data integration technologies have not been able to solve the fundamental problem, as they deliver data in scheduled batches, and cannot support many of today’s rich and complex data types.

Data virtualization is a modern data integration approach that is already meeting today’s data integration challenges, providing the foundation for data integration in the future.

Download this whitepaper to learn more about:

The fundamental challenge for organisations today.
Why traditional solutions fall short.
Why data virtualization is the core solution.

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Whitepaper

1) Does your role involve managing the data architecture within your organization?

Yes
No

2) Which of the following are you currently evaluating or planning to deploy within your organization in the next 6-12 months?

  Big Data & Advanced Analytics
  Agile BI & Self-Service BI
  Data Services / Data as a Service
  Logical Data Warehouse / Logical Data Lake
  Hybrid Cloud Deployment
  Data Virtualization
  Others

3) What is the current data integration challenge(s) faced within your organization? (Select all that apply)

  We have data silos and data fragmentation across distributed data sources.
  We are unable to access and govern enterprise data regardless of its type or location.
  We are unable to simplify and accelerate the journey to cloud modernization.
  We are trying to move all the data into a data lake (or some other repository), and that project is not going well.
  We are unable to manage the end-to-end lifecycle for self-service analytics and data science, with full capabilities for data discovery, data preparation, data modeling and data cataloging, etc.
  Others

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