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Compare FICO Predictive Analytics and IBM Cloud Pak for Data 
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At a Glance
Market Segments
Enterprise (39.1% of reviews)
Enterprise (50.0% of reviews)
Entry-Level Pricing
No pricing available
No pricing available
FICO Predictive Analytics
Star Rating
(25)4.0 out of 5
Market Segments
Enterprise (39.1% of reviews)
Pros & Cons
Not enough data
Entry-Level Pricing
No pricing available
Learn more about FICO Predictive AnalyticsIBM Cloud Pak for Data
Star Rating
(88)4.3 out of 5
Market Segments
Enterprise (50.0% of reviews)
Pros & Cons
Entry-Level Pricing
No pricing available
Learn more about IBM Cloud Pak for DataSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that FICO Predictive Analytics excels in Data Ingestion & Wrangling with a score of 9.5, making it a preferred choice for those needing robust data preparation capabilities. In contrast, IBM Cloud Pak for Data, while strong, has a lower score in this area, indicating it may not be as efficient for users focused on data wrangling.
- Reviewers mention that FICO Predictive Analytics offers superior Model Development features, particularly with its Pre-Built Algorithms scoring 9.1, which users find beneficial for quick deployment. Conversely, IBM Cloud Pak for Data's pre-built algorithms score lower at 7.8, suggesting it may require more customization for similar results.
- G2 users highlight that IBM Cloud Pak for Data shines in Data Interaction with a score of 9.0, which enhances user experience through intuitive interfaces. FICO Predictive Analytics, while effective, scores slightly lower at 8.3, indicating it may not be as user-friendly in this aspect.
- Users on G2 report that FICO Predictive Analytics has a strong edge in Ease of Setup with a score of 8.7, making it easier for teams to get started quickly. In contrast, IBM Cloud Pak for Data's score of 7.2 suggests a more complex setup process that may require additional resources.
- Reviewers mention that IBM Cloud Pak for Data provides better Deployment options, particularly with its Managed Service scoring 8.5, which is beneficial for organizations looking for hassle-free management. FICO Predictive Analytics, while effective, scores higher in application deployment but lower overall in managed services.
- Users say that FICO Predictive Analytics has a strong focus on Quality of Support with a score of 8.5, indicating a reliable support system. IBM Cloud Pak for Data, with a score of 8.3, also offers good support but may not match the responsiveness and effectiveness reported by users of FICO.
Pricing
Entry-Level Pricing
FICO Predictive Analytics
No pricing availableIBM Cloud Pak for Data
No pricing availableFree Trial
FICO Predictive Analytics
No trial information availableIBM Cloud Pak for Data
No trial information availableRatings
Meets Requirements
8.6
18
8.5
47
Ease of Use
8.4
18
8.1
47
Ease of Setup
8.7
5
7.2
26
Ease of Admin
Not enough data
7.6
27
Quality of Support
8.5
17
8.3
42
Has the product been a good partner in doing business?
Not enough data
8.1
25
Product Direction (% positive)
7.9
17
8.8
47
Features by Category
Customization
Not enough data
8.0
5
Not enough data
Not enough data
Not enough data
Not enough data
Infrastructure
Not enough data
Not enough data
Not enough data
9.0
5
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Management
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Infrastructure Provision
Not enough data
7.7
8
Not enough data
8.1
7
Not enough data
7.9
7
Not enough data
8.3
6
Not enough data
8.5
8
Not enough data
7.9
8
Not enough data
8.3
8
Not enough data
8.3
7
Management
Not enough data
8.6
7
Not enough data
8.3
7
Not enough data
8.1
8
Functionality
Not enough data
8.3
8
System
Not enough data
9.5
11
Model Development
Not enough data
8.3
8
Not enough data
8.5
8
Not enough data
9.1
9
Not enough data
8.8
8
Model Development
Not enough data
8.5
12
Machine/Deep Learning Services
Not enough data
8.7
9
Not enough data
9.4
8
Not enough data
9.6
8
Not enough data
9.0
7
Machine/Deep Learning Services
Not enough data
9.2
8
Not enough data
9.3
7
Deployment
Not enough data
9.3
9
Not enough data
9.3
9
Not enough data
8.9
9
Generative AI
Not enough data
8.3
5
Not enough data
8.3
5
Not enough data
8.3
5
Agentic AI - Data Science and Machine Learning Platforms
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Data Management
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
8.3
5
Analytics
Not enough data
Not enough data
Security
Not enough data
9.0
5
Not enough data
Not enough data
Not enough data
Not enough data
Generative AI
Not enough data
Not enough data
Not enough data
Not enough data
Agentic AI - Data Fabric
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Scalability and Performance - Generative AI Infrastructure
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Cost and Efficiency - Generative AI Infrastructure
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Integration and Extensibility - Generative AI Infrastructure
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Security and Compliance - Generative AI Infrastructure
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Usability and Support - Generative AI Infrastructure
Not enough data
Not enough data
Not enough data
Not enough data
Statistical Tool
7.8
10
8.3
5
Feature Not Available
8.8
8
Feature Not Available
8.6
7
Data Analysis
8.6
13
8.7
9
8.3
13
9.0
7
Decision Making
7.2
12
8.3
6
8.3
13
8.8
7
8.5
12
8.8
8
Feature Not Available
8.3
8
Generative AI
Not enough data
Not enough data
Not enough data
Not enough data
Data Transformation
Not enough data
8.5
27
|
Verified
Not enough data
9.1
15
|
Verified
Connectivity
Not enough data
8.0
23
|
Verified
Not enough data
8.6
22
|
Verified
Not enough data
8.1
25
|
Verified
Not enough data
8.7
24
|
Verified
Operations
Not enough data
8.7
26
|
Verified
Not enough data
8.9
25
|
Verified
Not enough data
8.4
23
|
Verified
Not enough data
8.8
24
|
Verified
Not enough data
8.7
13
|
Verified
Building Reports
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Platform
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Categories
Categories
Shared Categories
FICO Predictive Analytics and IBM Cloud Pak for Data are categorized as Predictive Analytics
Unique Categories
FICO Predictive Analytics has no unique categories
IBM Cloud Pak for Data is categorized as Data Fabric, Virtual Private Cloud (VPC), Big Data Analytics, Data Science and Machine Learning Platforms, Infrastructure as a Service (IaaS), and Generative AI Infrastructure
Reviews
Reviewers' Company Size
FICO Predictive Analytics
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
IBM Cloud Pak for Data
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Small-Business
(50 or fewer emp.)
Mid-Market
(51-1000 emp.)
Enterprise
(> 1000 emp.)
Reviewers' Industry
Hospital & Health Care
13.0%
Real Estate
8.7%
Marketing and Advertising
8.7%
Internet
8.7%
Financial Services
8.7%
Other
52.2%
Computer Software
12.9%
Information Technology and Services
8.6%
Banking
8.6%
Financial Services
5.7%
Education Management
5.7%
Other
58.6%
Alternatives
Discussions
FICO Predictive Analytics has no discussions with answers
IBM Cloud Pak for Data has no discussions with answers
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