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About AtScale

AtScale is a data analytics platform from AtScale that helps make smarter data-driven decisions at scale. It combines a semantic layer, AI & analytics, and business intelligence so organizations can build a self-service data-driven culture. AtScale connects any data source to any AI/BI tool without moving the data, ensuring trusted and consistent metrics across the organization. The platform supports modern analytics for every role and data stack, unifying the data ecosystem for enterprises. Key capabilities: Semantic Layer AI & Analytics Business Intelligence Data Governance & Trust Semantic Modeling Best for: organizations that need a comprehensive solution for data analytics and governance.

AtScale Details

Vendor
AtScale
Year Launched
2013
Location
400 S El Camino Real, Suite 800, San Mateo, CA, United States, California
Deployment
on premise, windows, linux
Training Options
documentation, live online, in person
Countries Served
All Countries
Languages
English
Users
Business Analysts, Data Engineers, Data Scientists
Industries Served
Healthcare, Education, Finance, Retail
Tags
Big Data, Business Intelligence, Data Warehouse, Integration

AtScale's In-App Market Place

Does AtScale have an in-app market place?

Yes

How many Mini-Apps in the marketplace?

1

Mini Apps

N/A

Pricing Options

Free trial
Free version
Request a quote
Promo Offer

Accepted Payment Currencies

USD ($), EUR (€), GBP (£), JPY (¥), AUD ($), CAD ($), CNY (¥), INR (₹)

Pros & Cons

  • • Data Democratization: Empowers business users to access and analyze data independently, without relying on technical experts.
  • • Improved Data Governance: Enforces data consistency and accuracy, reducing errors and improving decision-making.
  • • Enhanced Data Security: Provides robust security measures to protect sensitive data.
  • • Faster Time to Insights: Accelerates the time it takes to derive insights from data, leading to faster decision-making.
  • • Scalability: Can handle large and complex datasets, growing with the needs of the organization.
  • • Flexibility: Supports a variety of data sources and BI tools.
  • • Cost Optimization: Helps organizations optimize cloud costs by providing insights into usage patterns.
  • • AI and ML Integration: Enables the integration of AI and ML models with business data, unlocking new insights and automation opportunities.
  • • Complexity: Implementing and managing a semantic layer can be complex, requiring technical expertise.
  • • Vendor Lock-in: Relying heavily on AtScale can lead to vendor lock-in, making it difficult to switch to other solutions.
  • • Performance Overhead: In some cases, the semantic layer can introduce additional processing overhead, potentially impacting query performance.
  • • Data Quality Reliance: The quality of insights depends on the quality of the underlying data.

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