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What Is AtScale?

AtScale helps organizations transform into insight-driven enterprises. AtScale is the leading provider of intelligent data virtualization for big data analytical workloads. Enterprises worldwide use AtScale to eliminate data silos and create a single-source-of-truth without the need for additional investments in data engineering. AtScale provides rich, atomic level data access to the enterprise to empower their data science and analytics teams using tools they already use.

Who Uses AtScale?

Designed for businesses of all sizes, it is a big data solution that provides data governance, engineering, virtualization, and more.

AtScale Software - Connect to Data Platforms
AtScale Software - Connect to any BI Tool
AtScale Software - Multi-dimensional cubes
AtScale Software - Design Canvas
AtScale Software - Security & Governance

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Reviews of AtScale

Average score

Overall
5.0
Ease of Use
5.0
Customer Service
5.0
Features
5.0
Value for Money
4.0

Reviews by company size (employees)

  • <50
  • 51-200
  • 201-1,000
  • >1,001

Find reviews by score

5
100%
Verified Reviewer
Verified LinkedIn User
Banking, 10,000+ Employees
Used the Software for: 1+ year
Reviewer Source

A pretty cool data modelling software

5.0 5 years ago

Comments: My company used Atscale as our BI solution together with our cloudera and tableau software.
We gained some modelling benefit from Atscale which standardized the development of downstream reporting developments.
We also faced some integration challenge due to the complexity of cloudera and atsacle and tableau.
While overall, we are impressed by the design of Atscale.

Pros:

1. The data modelling is through the web based interface which is quite convenient for mutli user environment; 2. Advanced data caching mechanism which makes some pay-by-click services much cheaper; 3. Excellent performance gain through the caching mechanism; 4. Small but quite senior support team.

Cons:

1. Strict dimensional modelling design maybe not quite fit for the free style data structure; 2. An extra modelling layer may not be always needed; 3. Deployment design changed recently.