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What is Qlik Staige?

Harness the power of Qlik® Staige™ to turn AI into a practical asset by building a dependable data infrastructure, implementing automation, generating useful predictions, and making a considerable difference throughout your organization. AI is not just about trials and projects; it constitutes a holistic ecosystem brimming with files, scripts, and results. No matter how you choose to direct your investments, we have partnered with top-tier providers to deliver integrations that boost efficiency, ease management, and guarantee quality. Optimize the process of providing real-time data to AWS data warehouses or data lakes, making it accessible via a meticulously managed catalog. Our recent alliance with Amazon Bedrock enables seamless integration with key large language models (LLMs) like A21 Labs, Amazon Titan, Anthropic, Cohere, and Meta. This effortless connection with Amazon Bedrock not only streamlines access for AWS users but also allows them to leverage large language models in conjunction with analytics, leading to meaningful, AI-enhanced insights. By embracing these innovations, businesses can fully realize the transformative potential of their data in unprecedented ways, ultimately driving growth and efficiency across various sectors. Moreover, this strategic approach positions organizations to stay ahead in an increasingly data-driven landscape.

What is Qlik Compose?

Qlik Compose for Data Warehouses provides a modern approach that simplifies and improves the setup and management of data warehouses. This innovative tool automates warehouse design, generates ETL code, and implements updates rapidly, all while following recognized best practices and strong design principles. By leveraging Qlik Compose for Data Warehouses, organizations can significantly reduce the time, costs, and risks associated with business intelligence projects, regardless of whether they are hosted on-premises or in the cloud. Conversely, Qlik Compose for Data Lakes facilitates the creation of datasets ready for analytics by automating the processes involved in data pipelines. By managing data ingestion, schema configuration, and continuous updates, companies can realize a faster return on investment from their data lake assets, thereby strengthening their overall data strategy. Ultimately, these powerful tools enable organizations to efficiently harness their data potential, leading to improved decision-making and business outcomes. With the right implementation, they can transform how data is utilized across various sectors.

Media

Media

Integrations Supported

Amazon Bedrock
Amazon Comprehend
Amazon S3
Amazon SageMaker
Amazon Web Services (AWS)
Apache Hive
Apache Spark
Azure Storage
Cohere
DataRobot
Dropbox
EZConvertBI
Google Cloud Storage
Google Drive
Microsoft 365
Microsoft OneDrive
OpenAI
Pantomath
QVANTUM
Rayven

Integrations Supported

Amazon Bedrock
Amazon Comprehend
Amazon S3
Amazon SageMaker
Amazon Web Services (AWS)
Apache Hive
Apache Spark
Azure Storage
Cohere
DataRobot
Dropbox
EZConvertBI
Google Cloud Storage
Google Drive
Microsoft 365
Microsoft OneDrive
OpenAI
Pantomath
QVANTUM
Rayven

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

QlikTech

Company Website

staige.qlik.com

Company Facts

Organization Name

Qlik

Date Founded

1993

Company Location

United States

Company Website

www.qlik.com/us/products/qlik-compose-data-warehouses

Categories and Features

Categories and Features

Data Warehouse

Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge

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