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
biGENIUS automates all phases of analytic data management solutions (e.g. data warehouses, data lakes and data marts. thereby allowing you to turn your data into a business as quickly and cost-effectively as possible. Your data analytics solutions will save you time, effort and money. Easy integration of new ideas and data into data analytics solutions. The metadata-driven approach allows you to take advantage of new technologies. Advancement of digitalization requires traditional data warehouses (DWH) as well as business intelligence systems to harness an increasing amount of data. Analytical data management is essential to support business decision making today. It must integrate new data sources, support new technologies, and deliver effective solutions faster than ever, ideally with limited resources.
API Access
Has API
API Access
Has API
Integrations
Git
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
833CHF/seat/month
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
IBM
Founded
1911
Country
United States
Website
www.ibm.com/analytics/industry-models
Vendor Details
Company Name
biGENIUS AG
Founded
2011
Country
Switzerland
Website
www.bigenius-x.com
Product Features
Data Warehouse
Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge
Product Features
Big Data
Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates
Data Warehouse
Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge