Anaconda vs. GoodData.AI

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.

Incentivized

If you have consistently formatted data, that you want regular reports on, plus flexibility to let end users build their own reports, GoodData is perfect. Especially if your end users are less technical. If you want to be able to embed your reporting into your app, GoodData excels, though the start up process can be involved. If your data structure varies, it could be more challenging to integrate. It may also not be worth the integration if you have people who can already run their own SQL queries.

Incentivized

• 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.

Incentivized

• GoodData helps in simplifying complex data into easy-to-understand visuals. We can create personalized dashboards & tailor them as per requirements. This data can be used from an executive level employee to a team lead employee in the business
• GoodData is a very user friendly platform. The collaborative features simplify sharing and discussing reports among team members which promotes a culture of data-driven decision-making.
• GoodData connects with various data sources and consolidate information from multiple platforms. This flexibility proves invaluable for businesses dealing with data spread across different systems as they can access large amount of data on a single platform.

Incentivized

• More graphics need in Spyder book. If you work for couple of years then you will be bored with the graphics.
• Extra tools are required for making it secure. We uses extra tools for adding Username /Password to Jupyter.
• R Studio Hangs a lot when open from Anaconda Navigator.

Incentivized

• would be nice to be able to add the same filter to a multi-tab dashboard once instead of having to do it for each tab; tedious and time consuming
• Variable use is kind of clunky and would like to be able to hide/show easier
• The newer insight based dashboard method does not have the flexibility classic does

Incentivized

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.

Incentivized

Because gooddata really helps us in processing data to make reports or dashboards. So we are very satisfied when we use it. What we like is the flexible use of charts. We change at will the use of charts to display in reports or dashboards. Thank you Gooddata for helping companies like us who need flexibility in usage

Incentivized

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.

Incentivized

From my experience, overall usability of GoodData platform is great very easy to use, but there is still few features as GoodData platform and interface continuosly evolves, which are not yet available within user interface, but only available via API. For regular users all main and key features and tools are perfect, well defined and very easy to use.

Incentivized

We are approximately one month since go-live. There has been one short outage.

I'm generally impressed with how fast it reflects so much data.

Incentivized

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.

Incentivized

The fast and comprehensive responses we got from GoodData regarding the doubts we had experienced while starting to use the products and metrics were of great help in ensuring the metrics we were obtaining were accurate to what we wanted to know about our customers' experience and our product areas of opportunity.

Incentivized

Petr was a rock star - patient, knowledgeable, clear and easy to work with.

GoodData implementation team was professional and courteous

Implementations are hard and we had limited technical resources. We relied too heavily on GD care team. When we found technical gaps, they weren't simple to overcome

Incentivized

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.

Incentivized

We did our investigation years ago and I wasn't the one leading it but what I do remember was that GoodData had the best balance of price compared to infrastructure demand while not compromising on the power of available features around insight and dashboarding

Incentivized

We now have hundreds of customers on multiple product lines. It's very flexible and we can troubleshoot ourselves.

Incentivized

• 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.

Incentivized

• I personally pushed our management to get GoodData implemented, and there on we have been making much more profits than we ever did!
• Last month we made a decision using the platform and withing a short span of time our ROI gets 7X.
• We also made a marketing spend of $100,000 every quater using the insights and metrics, and we are really happy with the returs.

Incentivized