What users are saying about

Anaconda

Top Rated
33 Ratings

Anaconda

Top Rated
33 Ratings
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Score 8.8 out of 101

SAP Predictive Analytics

8 Ratings
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Score 6.9 out of 101

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Likelihood to Recommend

Anaconda

Anaconda is great for academic and private organizations that cannot afford more expensive Python/R package managers. Also, it is more appropriate for intermediate to advanced Python users--Anaconda can be somewhat frustrating for beginners, as it takes some practice to get comfortable with the workflow. I find it particularly useful for working in teams, because if everyone uses the same package manager, it is easier to troubleshoot issues and makes for reproducible research. For wealthier organizations, a premium package management system (with tech support) would be ideal. Anaconda is also great for people working independently on code development.
Maike Holthuijzen profile photo

SAP Predictive Analytics

It's a great tool to merge actual data analysis (which Lumira doesn't do that well) with visualization (which Lumira does well) - so it can be seen as Lumira for data analysts. However, a lot of the 'predictive' side is hidden/black box which can be frustrating for those analysts, so you could argue it is too complex for casual users, but too 'black box' for analysts.
Josh Anderson profile photo

Pros

  • Anaconda has iPython- Notebook that facilitates code writing in Python
  • It's very easy to install tour preferred the Python version
  • The risk of messing up the libraries is completely eliminated
Mauricio Quiroga-Pascal Ortega profile photo
  • Ability to use built-in algorithms or expand using R. This means that (with training) casual users can take advantage but also data analysts can do their thing!
  • Integration and consistency with Lumira. Even Lumira on its own has a quick 'predict' functionality (although limited/black box)
  • Ability to do the analysis and then present visually using the Lumira visualization capabilities
Josh Anderson profile photo

Cons

  • Some Python packages are not included to Anaconda, so you have to install them using different ways, like using pip, for example.
  • Sometimes you get stuck because Anaconda still have some little bugs.
  • Anaconda is a little slow when it's initializing.
Alejandro Daniel Copati profile photo
  • It's extremely hard to get started. We even have a data scientist who, when we put Predictive Analytics in front of them, they could not intuitively create a data model and start analyzing. Even with deep knowledge of data analysis, the interface isn't intuitive and it's hard to get to the point of having imported a data set and start analyzing/predicting
  • Our platform team had confusion installing Predictive Analytics, particularly on the BI Platform. Additional complexity came when it came to using APL Libraries (AFL Wrapper or Stored Procedures)
  • We are still working on merging datasets. In theory, we get how to do it but we come across all sorts of issues which don't occur in Spotfire (missing records etc.)
Josh Anderson profile photo

Alternatives Considered

Other systems might be easier to set-up but Anaconda is a fairly flexible analytics toolkit. It can be configured in a way that truly matches the way in which your business or analytics department works. Built on top of lots of open source projects so things aren't siloed and you can avoid vendor lock-in.
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We have typically used Spotfire for data analysis but decided to move to SAP Business Objects due to its innate connection with SAP. I found Lumira to be good for visualizations but it is not meant for data analysis. Therefore, we have introduced Predictive Analytics to see if it can fill that gap. So far, it's been far less intuitive than Spotfire to get started, and as far as I am aware so far, it does not bring many additional capabilities. I do, however, like that it utilizes the Lumira look/feel and integrates very well.
Josh Anderson profile photo

Return on Investment

  • Extremely quick turnaround time to set up data science experiments
  • Reduction of troubleshooting time when deploying new packages and dependencies
  • Low risk environment due to the community edition
Daniel Blazquez profile photo
  • It will potentially save time in forecast creation by giving an algorithm-derived forecast which can then be adjusted vs. starting from scratch. We can call this, a system enabled forecast
  • Thresholds can be created based on historical data to flag actuals as in/out of the 'norm', or to limit the scope of an investigation
  • We spent a lot of time so far and haven't got very far with it - it's been quite frustrating to use and a lot of time/money has been invested
Josh Anderson profile photo

Pricing Details

Anaconda

General
Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No
Additional Pricing Details

SAP Predictive Analytics

General
Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No
Additional Pricing Details