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Everyone being able to work smoothly without unnecessary delays.
I have seen a return on investment; specifically, when we talk about efficiency, it's both time-saving and money-saving.
I have seen a return on investment with time saved by 50% and less downtime, allowing the team to deliver projects faster with fewer errors.
I have seen a return on investment, as the accuracy has really improved in my organization since everything is automated.
Since using this tool, I can now make decisions faster, even when there is just a small change in the data.
Anaconda Business customer support is very active with a quick response time.
Overall, support was reliable when we needed it, just not super-fast every single time.
The customer support for Anaconda Business provides a better approach.
We have a multi-level support system, with the initial level handled by the company we bought the license from and subsequent support from IBM.
Instead, we rely on third-party partners recognized by IBM, who provide cost-effective support.
They have been very dedicated and provided top-notch solutions.
As more environments or users get added, it still runs smoothly without major slowdowns.
Anaconda Business scales very well because it is built around centralized environment and package management.
Anaconda does not have scalability restrictions as it depends on the type of machine running it.
IBM Planning Analytics' scalability is impressive, as it is able to gather data from multiple sources and handle huge amounts of data without any lagging or downtime.
Scalability is quite hard to implement in TM1, largely since the on-premise installation chosen back in 2014.
Scalability is straightforward but it is pricey since it's a SaaS model priced per user.
Earlier, setting up or troubleshooting conflicts could take anywhere from thirty minutes to an hour, but now most setups just work.
Anaconda Business is stable to an extent, but it sometimes crashes on systems with insufficient RAM.
The performance of IBM Planning Analytics has always been fast and reliable for my needs, even when dealing with huge volumes of data.
This stability is really important as we use it for budget calculation, which is time-consuming.
IBM Planning Analytics is stable because the reason we switched from IBM Cognos is that IBM Planning Analytics capability allows us to connect to multiple tools, which we could not do before.
It would also be nice to have clearer error messages when something fails, so it is easier to understand what went wrong without digging too much.
They should enhance the security point of view; it's good, but it needs some more advanced features.
The pricing should be a little lower for a single person to use, as it might be affordable for an organization, but for my single use, it is difficult.
The abundance of features results in complexity, requiring strict guidelines for developers to ensure simplistic approaches are adhered to.
IBM's visualization needs significant improvement.
The advanced features are somewhat complex to understand, and if the data set is very large, it takes a lot of time to process, which causes performance to become slower.
Anaconda is an open-source tool, so I do not pay anything for it.
My experience with pricing, setup cost, and licensing is that it is a little costly, but it is useful.
My experience with pricing, setup cost, and licensing indicates that it is a bit costly, but it is useful.
TM1 is quite expensive, and I'd rate the pricing as an eight out of ten.
While IBM's solutions were costly before, the introduction of SaaS models has reduced prices significantly.
My experience with pricing, setup cost, and licensing for IBM Planning Analytics is that the pricing and licensing cost can be somewhat on the higher side, especially for small organizations.
Anaconda Business has positively impacted my organization because, when discussing the security point of view, it's exceptional; when comparing it to other solutions, Anaconda Business is superior.
We find the advanced security, governance, and collaborative features for organizations using Python and R particularly useful.
Anaconda Business positively impacts our organization by protecting us from compliance and security risks while keeping the environment consistent, allowing our team to focus on insight and innovation instead of worrying about setups, security, and software issues.
Its stability helps controllers win time in their planning processes.
It also integrates machine learning and AI engines, enabling us to use algorithms for inventory forecasting which optimizes our inventory and replenishment rates.
Some of the valuable features of IBM Planning Analytics are its intuitive and user-friendly interface, reporting output and scheduling, access control and security, and mobile capabilities.
| Product | Mindshare (%) |
|---|---|
| Anaconda Business | 2.2% |
| Databricks | 8.2% |
| Dataiku | 5.6% |
| Other | 84.0% |
| Product | Mindshare (%) |
|---|---|
| IBM Planning Analytics | 4.4% |
| Anaplan | 6.8% |
| Adaptive Insights | 5.0% |
| Other | 83.8% |

| Company Size | Count |
|---|---|
| Small Business | 12 |
| Midsize Enterprise | 2 |
| Large Enterprise | 19 |
| Company Size | Count |
|---|---|
| Small Business | 16 |
| Midsize Enterprise | 4 |
| Large Enterprise | 16 |
Anaconda Business provides a comprehensive platform for data science applications, integrating extensive libraries and seamless Python and R compatibility, enhancing developer productivity.
Anaconda Business offers data science professionals a platform combining extensive library support with pre-built models and seamless integration of Python and R environments. With features like a user-friendly interface and integrated Jupyter Notebook, it facilitates real-time code execution and debugging. Environmental management is simplified via Conda, while cloud-based access and package management enhance user experience. Community support and integration with applications like RStudio and Jupyter aid in data science and deep learning tasks.
What are the key features of Anaconda Business?Anaconda Business is widely used in industries like machine learning and data analysis, where it's employed for tasks such as predictive modeling and data visualization. Organizations utilize its compatibility with tools like Scikit-learn and TensorFlow for creating statistical models, supporting applications in fields such as analytics, education, subrogation, and warehouse management.
IBM Planning Analytics offers a robust planning, budgeting, and forecasting platform powered by TM1 technologies, integrating with Excel while offering real-time calculations, data governance, and security.
Supporting flexible scenario modeling and forecasting, IBM Planning Analytics enhances planning processes via machine learning, real-time data calculations, and meaningful collaboration. In-memory processing and data slicing boost automation, reduces errors, and increase performance, while the centralized database facilitates secure and governed data management. Sandbox environments assist users in testing scenarios, and integration with Excel is crucial for financial planning and resource allocation.
What are the key features of IBM Planning Analytics?In multiple industries, IBM Planning Analytics is key in supporting budgeting, planning, and forecasting efforts. Financial services use it for cash flow modeling and resource allocation, while manufacturing sectors benefit from its dashboard-driven data visualization capabilities. Businesses utilize its robust reporting and real-time analysis functionalities to manage resources and assess future risks effectively.
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