TrustRadius

Causal vs. IBM Analytics Engine

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Causal
Score 10.0 out of 10
N/A
Causal, from the company of the same name in London, presents a way to perform calculations, visualise data, and communicate with numbers. It helps build models faster, connect them directly to data, and share them with interactive dashboards and visuals. Suggested use cases are financial planning, planning CPC campaigns, track KPIs, or determine employee compensation.
$50
per user, per month
IBM Analytics Engine
Score 7.1 out of 10
N/A
IBM BigInsights is an analytics and data visualization tool leveraging hadoop.N/A
Pricing
CausalIBM Analytics Engine
Editions & Modules
Pro
$50
per user, per month
Business
Contact Sales
No answers on this topic
Offerings
Pricing Offerings
CausalIBM Analytics Engine
Free Trial
YesNo
Free/Freemium Version
YesNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details——
More Pricing Information
Community Pulse
CausalIBM Analytics Engine
Considered Both Products
Causal

No answer on this topic

IBM Analytics Engine
Verified User
Anonymous
Chose IBM Analytics Engine
We have tried the following solutions in the past and I must say they can't compare to IBM Analytics Engine:

Ejaz Hussain | TrustRadius Reviewer
Ejaz Hussain
Senior Analyst
Chose IBM Analytics Engine
Our data analytics team happened to try IBM Analytics just to get acquainted with it & it turned out that this tool fits our business requirement better than the one which we were using in terms of the features along with the level of support that they provide. so, choosing the …
Verified User
Anonymous
Chose IBM Analytics Engine
IBM Analytics is a great tool and a welcome addition to your overall IBM strategy. I think in cases of tools like this, you either go with what your platform works best with or you go completely different with a 3rd party, like Snowflake. We are an Azure shop and just happened …
Verified User
Anonymous
Chose IBM Analytics Engine
We initially wanted to go with Google BigQuery, mainly for the name recognition. However, the pricing and support structure led us to seek alternatives, which pointed us to IBM. Apache Spark was also in the running, but here IBM's domination in the industry made the choice a …
Verified User
Anonymous
Chose IBM Analytics Engine
We did an evaluation of Google Analytics and Microsoft Azure Stream Analytics in comparison to the IBM Analytics Engine product. We choose the product offering from IBM because we felt that for our company, this product offered a more complete and comprehensive package to …
Verified User
Anonymous
Chose IBM Analytics Engine
Hortonworks Data Platform, Apache Spark, Tableau Desktop and Tableau Online
Prasanna Nattuthurai | TrustRadius Reviewer
Prasanna Nattuthurai
Graduate Assistant
Chose IBM Analytics Engine
  • I have been using Azure for my previous analysis, I had a difficult time in understanding the Analytics engine rather IBM provided step by step tutorial for setup.
  • Also turning off a machine was not an option in Azure for some of the services so I had to pay for the service …
Verified User
Anonymous
Chose IBM Analytics Engine
Our professor has worked with IBM And many major tech companies. He’d recommend us which tools to use. And comparing to Azure, IBM is more convenient to use.
Features
CausalIBM Analytics Engine
BI Standard Reporting
Comparison of BI Standard Reporting features of Product A and Product B
Causal
9.3
Ratings
14% above category average
IBM Analytics Engine
-
Ratings
Pixel Perfect reports8.00 Ratings00 Ratings
Customizable dashboards10.00 Ratings00 Ratings
Report Formatting Templates10.00 Ratings00 Ratings
Ad-hoc Reporting
Comparison of Ad-hoc Reporting features of Product A and Product B
Causal
8.3
Ratings
6% above category average
IBM Analytics Engine
-
Ratings
Drill-down analysis9.00 Ratings00 Ratings
Formatting capabilities8.00 Ratings00 Ratings
Report sharing and collaboration8.00 Ratings00 Ratings
Report Output and Scheduling
Comparison of Report Output and Scheduling features of Product A and Product B
Causal
8.0
Ratings
2% below category average
IBM Analytics Engine
-
Ratings
Publish to Web8.00 Ratings00 Ratings
Publish to PDF8.00 Ratings00 Ratings
Report Versioning8.00 Ratings00 Ratings
Report Delivery Scheduling8.00 Ratings00 Ratings
Delivery to Remote Servers8.00 Ratings00 Ratings
Data Discovery and Visualization
Comparison of Data Discovery and Visualization features of Product A and Product B
Causal
8.0
Ratings
3% above category average
IBM Analytics Engine
-
Ratings
Predictive Analytics8.00 Ratings00 Ratings
Pattern Recognition and Data Mining8.00 Ratings00 Ratings
Best Alternatives
CausalIBM Analytics Engine
Small Businesses
Supermetrics
Supermetrics
Score 9.8 out of 10

No answers on this topic

Medium-sized Companies
Supermetrics
Supermetrics
Score 9.8 out of 10
Cloudera Manager
Cloudera Manager
Score 9.9 out of 10
Enterprises
IBM Analytics Engine
IBM Analytics Engine
Score 7.1 out of 10
Apache Spark
Apache Spark
Score 8.9 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
CausalIBM Analytics Engine
Likelihood to Recommend
10.0
(0 ratings)
9.5
(0 ratings)
User Testimonials
CausalIBM Analytics Engine
Likelihood to Recommend
Definitely suited best for B2B / B2B2C product modelling. We used this for B2B / B2B2C / C2C and the C2C side of things was always more complex to model out due to this being dependent on marketing spend (CAC) and factors around virality which really cannot be forecasted (not a shortcoming of Causal, just implied by the mechanics of modelling)
Verified User
Anonymous
Read full review
We are at present utilizing IBM Analytics Engine and it works incredible. Following are the things that I like the most about this product is:- - Simple to Utilize - Reasonable Cost - With only a couple seconds you can ready to fabricate and convey groups - you can without much of a stretch break down information through different applications
Verified User
Anonymous
Read full review
Pros
No answers on this topic
  • We are able to build and deploy clusters within minutes to simplify user experience and increase scalability and reliability.
  • We are able to scale and compute on-demand to handle newer workloads like machine learning.
  • We really like that we are able to access and administer the application via multiple interfaces.
Verified User
Anonymous
Read full review
Cons
No answers on this topic
  • I would like to see a more robust version of their online help
  • The speed of their business support is adequate, but I kind of expect more from such a powerhouse.
  • Problems with duration of cluster life
Verified User
Anonymous
Read full review
Alternatives Considered
No answers on this topic
  • I have been using Azure for my previous analysis, I had a difficult time in understanding the Analytics engine rather IBM provided step by step tutorial for setup.
  • Also turning off a machine was not an option in Azure for some of the services so I had to pay for the service whether I use it or not
Prasanna Nattuthurai | TrustRadius Reviewer
Prasanna Nattuthurai
Graduate Assistant
Read full review
Return on Investment
No answers on this topic
  • It has saved us quite a bit of time managing our catalog of clusters and keeping things organized.
  • Since we had a division we acquired running IBM Cloud, it was easy to get it running and try it out, but we found we prefer our Azure configuration better simply to keep our technology in alignment across corporate functions.
  • I definitely see some cost savings by separating out the storage and compute. It helps you start to put an appropriate price tag on certain instances of big data.
Verified User
Anonymous
Read full review
ScreenShots