Anaconda provides access to the foundational open-source Python and R packages used in modern AI, data science, and machine learning. These enterprise-grade solutions enable corporate, research, and academic institutions around the world to harness open-source for competitive advantage and research. Anaconda also provides enterprise-grade security to open-source software through the Premium Repository.
$0
per month
ibi WebFOCUS
Score 7.0 out of 10
N/A
The ibi™ WebFOCUS® product is an enterprise business intelligence and analytics solution equipped with data management, visual discovery, predictive analytics, and visualizations. Combining these capabilities and data science in one unified containerized platform, the WebFOCUS® solution can be used to make data-driven decisions across the enterprise and provide reports, dashboards, and customer-facing applications at scale.
I am using both; when it comes to application deployment on the server, I use Docker, and sometimes, I use Docker with conda image for deployment when it comes to ML/DL apps.
There are several reasons why Anaconda is better to use for me including that it is much easier to use than Baycharm. Also, the user interface is not as complicated as that of Baycharm. Even Anaconda does not slow down my device, using PaySharm slowed down my device in an …
It provides several IDEs like Spyder and Jupiter that would be enough for me to write my Python script. You can easily install it on a Windows or Linux computer and supports many libraries.
In Anaconda, [it is easy] to find and install the required libraries. Here, we can work on multiple projects with different sets of the environment. [It is] easy to create the notebook for developing the ML model and deployment. Right now, it is the best data science version …
One of the main competitors to Anaconda can be Google products such as Colab. Colab gives you the flexibility to handle large datasets gives it an edge over Anaconda. But again, the ease of access and usability of Anaconda stacks up against Colab. Besides, Anaconda relies more …
It is almost dishonest to compare Anaconda with PyCharm as they do different things in their basic forms unless you spend a lot of time configuring plugins on your PyCharm environment. Anaconda has a lot of things ready and you just need to install your libs and dependencies.
Anaconda has features which overpowers it over the other analytical tools I have used. Also it provides multiple ways to reach to the solution, depending on the developers expertise. When I was a beginner at using Anaconda, since it is open source and the community using …
On top of all the software that I have used, Anaconda is the best because in Anaconda we have built-in packages that provide no headache to install packages and we can design a separate environment for different projects. Anaconda has versions made for special use cases. …
Some analyzed tools, such as Pycharm and Spyder, are simpler to use but still do not have all the libraries needed for those starting out in data science--or in institutions that need to grow in that direction. Anaconda is more robust but stable, more complete, and the …
If the project is not large scale then Jupiter notebooks or Visual Studio Code serve well. If you don't have any dependency on Python versions, these IDEs can be well suited for fast development and deployment.
Anaconda includes many standard data science packages where as the regular python installation does not. Depending on use case, some may feel Anaconda may be "bloated" For ease Anaconda is better, for minimizing extraneous package installation, the regular python installer is …
I know that Pycharm is a IDE and Anaconda is a distribution. However I use Anaconda largely due to Jupyter Notebook, which more or less does the same job as Pycharm. 1 year ago I decided to use Anaconda (Jupiyer Notebook) as it is easier to use it as a beginner(at least my …
MATLAB is more of a pay-as-you-go alternative, which not only does not use Python but is also more bloated and costly. MATLAB takes longer to install, setup, and configure for new users who may require specific packages - such as the Classification Learner (machine learning), …
Compare Anaconda to Unix coding system. You can use PIP to install and create requirement.txt to replace environment.yml to avoid using Anaconda. However, Anaconda is such an excellent tool to maintain your environment and check the version of your package and update the …
Anaconda is very strong in the environment and version control that make data science work much easier. The only thing that might be comparable to Anaconda would be using Kubernetes to control Docker. Another potential improvement would be replacing spyder with PyCharm and Atom …
Anaconda gives freedom to do anything with its packages, compared to other non-programming language-based softwares. It is almost possible to do anything with Anaconda. Anaconda brings ease of integrity because it is possible to integrate anything with a Python Py script, …
I prefer Anaconda due to the control I have at every level over the data and the visualizations. Power BI does a better job at guessing what graphics to use, but these usually aren't the most helpful. Anaconda and the slew of Python extensions that add incredible functionality, …
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 …
Above average. Feature wise [Information Builders WebFOCUS] stands out. User friendliness is OK. It can handle the most complex tasks and its extensions with for example R make it extremely versatile. Support is lagging in western Europe, although i am more than happy with …
We've looked at Tableau as an alternative and the visuals are good in Tableau. One way that WebFOCUS beats Tableau is it doesn't have any issues with a set number of columns in a report. When you need to have an Excel output, which happens, WebFOCUS is far superior. The …
Webfocus handles the side of our business that is involved with our catalogs. Our catalogs is a huge revenue driver for us and this tool has been extremely useful with planning feature catalogs. Tableau is used more for marketing and merchandising purchases since we can filter …
Application Development Analyst and Software Engineer
Chose ibi WebFOCUS
No comparison. Both have their strengths, but WebFocus comes out on top as the clear winner because it is so easy to use and understand for power users. Crystal Reports, like most BI tools, requires more extensive training and is not as easy or user friendly. It is more …
WebFOCUS has a mature and tested product that speaks well to internal personnel who rely on legacy data systems for day-to-day operations and business processes. It is apparent some newer products provide flexibility in user access with limited previous knowledge or experience …
I've used a few other development frameworks, but the desition of the company to use WF was not mine. I came and WF is the tool that the company uses. I think that WF is a very important framework to achieve the goals of the company and I would like this technology to become the …
WebFOCUS is more visual and easier to build for a non-programming user, where with little knowledge on data management and dedication to learn it, you can easily start creating very well presented reporting that is automated. With the Report Caster system it allows you to fully …
Years ago I developed in Business Objects and when it came down to a decision to go with WebFOCUS it was a pretty easy choice. There is really nothing you can't do with the platform given all of the available options to develop the solutions with - HTML pages, parameterized …
I like the ease of development best on webfocus. As compared to Qlikview, it is better at handling large amounts of data and the data access process is much easier in WebFOCUS ( very manual in Qlik). Qlik is better for ad hoc drill through and it is nice how a selector easily …
Business Objects -WebFOCUS is more centered towards the user accessing data without an administrator setting up reporting objects or setting rules on data access. Access is more free form and allows the user more freedom (for better or worse) to design and create the report …
I found WebFOCUS a great tool for reporting purposes as I have used it for a long time. They should compare themselves with new reporting tools like Tableau and Splunk. Tableau's interface is mind blowing. IBI should learn from Tableau and how they have penetrated the big data …
The reason we chose WebFOCUS is because it seemed the easiest to use to create great reporting products. Also, we really liked that the code is transparent and readily available. We were confident in Information Builder's longevity and believed that ultimately, our staff would …
I have asked all my juniors to work with Anaconda and Pycharm only, as this is the best combination for now. Coming to use cases: 1. When you have multiple applications using multiple Python variants, it is a really good tool instead of Venv (I never like it). 2. If you have to work on multiple tools and you are someone who needs to work on data analytics, development, and machine learning, this is good. 3. If you have to work with both R and Python, then also this is a good tool, and it provides support for both.
WebFOCUS is a good comprehensive tool for BI for companies. I feel that scenarios where you want the user to interact and be able to ingest data in different formats would be a good use of the tool. Performing data discovery is easier with InfoAssist, especially the most recent versions, and allows users to customize their views and provide comments.
Installing packages is very easy with Anaconda. Anaconda comes with 'anaconda navigator', a terminal-like utility from which you can easily install R packages and python libraries.
Launching R and python IDEs as well as Jupyter notebooks from anaconda navigator is simple, and Anaconda makes it very easy to keep these packages up-to-date.
I really like the fact that if you don't want to install the full version of Anaconda, you can opt to install a lightweight version (called Miniconda) that includes less python libraries and only core conda. I've installed it when I didn't want to take up as much disk space as Anaconda requires, but it works just the same.
Webfocus reports all have the option to export to Excel. The excel spreadsheet is always very organized and clean, and the information is very easy to read.
Webfocus is able to maintain data from years prior. We can look up what we featured in catalogs and all the sales history attached with it.
Webfocus is able to provide support to a variety of departments. For example, our buying team uses it for planning in advance and our marketing team uses the tool to see how categories and products as the selling
It's really good at data processing, but needs to grow more in publishing in a way that a non-programmer can interact with. It also introduces confusion for programmers that are familiar with normal Python processes which are slightly different in Anaconda such as virtualenvs.
This software is deeply engrained with my organization and has become a tool that would not easily be replaced without spending more money and resources to get the same results. License cost is comparable to other report writing tools and the capabilities are greater than the competition without having to buy multiple apps to do the same thing.
I am giving this rating because I have been using this tool since 2017, and I was in college at that time. Initially, I hesitated to use it as I was not very aware of the workings of Python and how difficult it is to manage its dependency from project to project. Anaconda really helped me with that. The first machine-learning model that I deployed on the Live server was with Anaconda only. It was so managed that I only installed libraries from the requirement.txt file, and it started working. There was no need to manually install cuda or tensor flow as it was a very difficult job at that time. Graphical data modeling also provides tools for it, and they can be easily saved to the system and used anywhere.
Best BI tool/product I have used. The others don't compare overall. Some can look fancier, but when you actually use them with large data and data from numerous systems/sources that is where most of the competition falls away. I also don't like downtime. I have basically none for a large user base with WebFocus. Even SAP Crystal Reports went down for 4 days once - 4 days because the admin password got locked out due to a glitch and we had zero reports for 4 days. WebFocus has never had more than a few minutes of downtime. It's like a tank that just keeps rolling. There is no other choice for reliable BI.
Anaconda provides fast support, and a large number of users moderate its online community. This enables any questions you may have to be answered in a timely fashion, regardless of the topic. The fact that it is based in a Python environment only adds to the size of the online community.
They have extremely knowledgeable techs that I have worked with over the years. Some have actually become really good friends of mine. I see them often at local user groups and when we show them how we are using their tools to save millions of dollars throughout the company
Plan ahead on what data will be accessible and the type of security required on the database and if you will want to use security that is built into the software. It is worth consulting with the vendor on what your plan is and how they recommend you proceed in order to get results you are happy with.
One of the main competitors to Anaconda can be Google products such as Colab. Colab gives you the flexibility to handle large datasets gives it an edge over Anaconda. But again, the ease of access and usability of Anaconda stacks up against Colab. Besides, Anaconda relies more on your machine which makes it safe to use.
Above average. Feature wise [Information Builders WebFOCUS] stands out. User friendliness is OK. It can handle the most complex tasks and its extensions with for example R make it extremely versatile. Support is lagging in western Europe, although i am more than happy with current level. With takeover by tipco it remains to be seen how European strategy will evolve
Positive impact - Multiple options for data presenting , visualizing and sharing. (Eg: R-Markdown).
Positive impact - Ease of access to build complex machine learning models. (I work in NLP, it has multiple built in models to analyze the various contexts).
Positive impact - Conda package let's to deal with external packages which can be used in Jupyter.
We are not yet a success story. Though we've been implementing WebFOCUS for over a year, we have very few products in our Production portal. Of course, this is not all the responsibility of Information Builders, but we were ill-advised by our 'training coordinator' in our training of staff and coming up to speed with the tools has been very slow.
Once skilled analysts and professional IT staff achieve a grasp of the products, they are able to very quickly create polished and well-received products.
The DW/BI project has helped us to establish standards and protocols of communication that will allow us to more quickly meet knowledge transfer requirements