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What is Qlik Data Integration?
The Qlik Data Integration platform, tailored for managed data lakes, simplifies the provision of consistently updated, reliable, and trustworthy data sets essential for business analytics. Data engineers benefit from the adaptability to quickly integrate new data sources, ensuring effective oversight throughout each phase of the data lake pipeline, which encompasses real-time data ingestion, refinement, provisioning, and governance. This platform serves as a user-friendly and all-encompassing solution for the continuous ingestion of enterprise data into popular data lakes in real-time. By utilizing a model-driven approach, it supports the swift design, construction, and administration of data lakes, whether they are hosted on-premises or in the cloud. Additionally, it features an advanced enterprise-scale data catalog that allows for secure sharing of all derived data sets with business users, significantly enhancing collaboration and facilitating data-driven decision-making within the organization. This holistic strategy not only streamlines data management processes but also empowers users by ensuring that valuable insights are easily accessible, ultimately fostering a more informed workforce. The integration of user-friendly tools further encourages engagement and innovation in leveraging data for strategic objectives.
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.
Integrations Supported
Rayven
Amazon Web Services (AWS)
Azure Synapse Analytics
Clarity Security
Cloudera
DataHawk
EZConvertBI
Google Cloud BigQuery
Google Cloud Platform
Kleene
Integrations Supported
Rayven
Amazon Web Services (AWS)
Azure Synapse Analytics
Clarity Security
Cloudera
DataHawk
EZConvertBI
Google Cloud BigQuery
Google Cloud Platform
Kleene
API Availability
Has API
API Availability
Has API
Pricing Information
Pricing not provided
Free Version
Free Trial Offered?
Pricing Information
Pricing not provided
Free Version
Free Trial Offered?
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
Qlik
Date Founded
1993
Company Location
United States
Company Website
www.qlik.com/us/products/qlik-talend-data-integration-and-quality
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
Data Management
Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge
Integration
Dashboard
ETL - Extract / Transform / Load
Metadata Management
Multiple Data Sources
Web Services
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