Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
IBM's industry data model serves as a comprehensive guide that incorporates shared components aligned with best practices and regulatory standards, tailored to meet the intricate data and analytical demands of various sectors. By utilizing such a model, organizations can effectively oversee data warehouses and data lakes, enabling them to extract more profound insights that lead to improved decision-making. These models encompass designs for warehouses, standardized business terminology, and business intelligence templates, all organized within a predefined framework aimed at expediting the analytics journey for specific industries. Speed up the analysis and design of functional requirements by leveraging tailored information infrastructures specific to the industry. Develop and optimize data warehouses with a cohesive architecture that adapts to evolving requirements, thereby minimizing risks and enhancing data delivery to applications throughout the organization, which is crucial for driving transformation. Establish comprehensive enterprise-wide key performance indicators (KPIs) while addressing the needs for compliance, reporting, and analytical processes. Additionally, implement industry-specific vocabularies and templates for regulatory reporting to effectively manage and govern your data assets, ensuring thorough oversight and accountability. This multifaceted approach not only streamlines operations but also empowers organizations to respond proactively to the dynamic nature of their industry landscape.
Description
Qlik Compose for Data Warehouses offers a contemporary solution that streamlines and enhances the process of establishing and managing data warehouses. This tool not only automates the design of the warehouse but also generates ETL code and implements updates swiftly, all while adhering to established best practices and reliable design frameworks. By utilizing Qlik Compose for Data Warehouses, organizations can significantly cut down on the time, expense, and risk associated with BI initiatives, regardless of whether they are deployed on-premises or in the cloud. On the other hand, Qlik Compose for Data Lakes simplifies the creation of analytics-ready datasets by automating data pipeline processes. By handling data ingestion, schema setup, and ongoing updates, companies can achieve a quicker return on investment from their data lake resources, further enhancing their data strategy. Ultimately, these tools empower organizations to maximize their data potential efficiently.
API Access
Has API
No
API Access
Has API
No
Integrations
BLUE Software
No
EZConvertBI
No
Pantomath
No
QVANTUM
No
Rayven
No
Tenant
No
Integrations
BLUE Software
Yes
EZConvertBI
Yes
Pantomath
Yes
QVANTUM
Yes
Rayven
Yes
Tenant
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
Yes
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
Yes
Types of Training
Training Docs
No
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
IBM
Founded
1911
Country
United States
Website
www.ibm.com/analytics/industry-models
Vendor Details
Company Name
Qlik
Founded
1993
Country
United States
Website
www.qlik.com/us/products/qlik-compose-data-warehouses
Product Features
Data Warehouse
Ad hoc Query
No
Analytics
No
Data Integration
No
Data Migration
No
Data Quality Control
No
ETL - Extract / Transfer / Load
No
In-Memory Processing
No
Match & Merge
No
Product Features
Data Warehouse
Ad hoc Query
No
Analytics
Yes
Data Integration
Yes
Data Migration
No
Data Quality Control
No
ETL - Extract / Transfer / Load
No
In-Memory Processing
No
Match & Merge
No