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Enabling Power BI users to establish a live connection to PB-level big data using DirectQuery for interactive analysis. Quickly designing and building data models from any data source (including relational databases, Hadoop, object storage, etc.) with automated modeling technology. The Smart Pushdown™ engine will route queries not covered in the model to the data source to better support ad hoc queries. Kyligence can be deployed both on-premises and in the cloud, supporting high concurrency and high performance.
Reduce your unit cost with an architecture optimized for total cost of ownership (TCO). You can use computing resources on demand and pay for services on a pay-as-you-go basis.
Deployed on the same virtual network with granular data access control.
Kyligence helps your organization create a unified semantic business model to map complex data into business language. The dimensions, metrics, and hierarchies familiar to business users are synchronized with Power BI through the unified semantic layer to unify and reuse business semantics.
Based on Azure's global cloud infrastructure, Kyligence's intelligent data modeling platform fully leverages Spark's distributed computing capabilities for building a scalable, cost-effective, high-performance OLAP analytics engine that supports OLAP analysis of big data on Power BI. This enables data analysts and business users to quickly identify business value from massive amounts of data in data lakes and make better business decisions.
The Power BI + Kyligence supports two kinds of deployments:
Cloud deployment: Kyligence service is deployed in the virtual network of the public cloud (Azure or other public clouds), and forms a cloud deployment architecture with Power BI Service, Power BI Desktop, and On-premises data gateway
Hybrid deployment: Kyligence is deployed in the local data center and connected to Power BI Service through the On-premises data gateway to form a hybrid deployment.
Learn the evolution of cloud analytics, and how you can achieve performance, efficiency, scalability, and security for your data engineering and analytics workloads on the cloud.
Learn how you can optimize your cloud data lake for both business value and cost, and accelerate your time-to-insight.
Help your business go from data to insight faster than ever with this guide to updating your IT and analytics environment in the age of Big Data.
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