Item: Anaconda
Rating: 10
Author: Verified User

Use Cases and Deployment Scope

We're using it in our department for data-related business needs, data retrieval, data manipulation, data preprocessing, visualization, forecasting, and prediction. So whether the business problem is a simple data analytics problem or complex modeling, Anaconda is used in our department. We use Anaconda for its Python libraries that come as a package, which is great. Not to mention that it eases the pain of updating all packages that would otherwise be carried out one by one for each. We use Panda's library within Anaconda to read, manipulate, preprocess and write the data. We use Numpy for mathematical functions. We use Matplotlib and Seaborn for data analysis and visualization. Finally and most importantly, we use Sci-kit Learn to create predictive models because it contains almost all the algorithms we need. Sadly, it does not contain XGBoost, CatBoost or LBGM however it is easy to install those with Anaconda because that's what Anaconda is for - helping managing all these packages, whether it is installation or simply updating.

Pros and Cons

Contains every fundamental package about data analytics and machine learning.
It is very easy to install further packages.

It's great that it contains a lot of stuff but it is very slow to boot and is a heavy product.

Return on Investment

It saved us time by taking care of all these packages, and time is our most valuable resource because we carry out all kinds of engineering tasks.
We increase product quality thanks to predictive mathematical models.

Alternatives Considered

KNIME Analytics Platform

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, compared to other low integrity software packages. Not to mention it is very easy to read from Databases with Anaconda. Overall it is the ability and freedom to do anything with Anaconda which caused us to choose and happily use it.

Support Rating

It is 10/10 because I never needed it, which concludes as if it was designed almost perfect that the customer does not need customer support. And for little things I could not resolve, Googling helped because the community is there to help you resolve small little inconveniences that aren't worth contacting support.

Key Insights

Do you think Anaconda delivers good value for the price?

Yes

Are you happy with Anaconda's feature set?

Yes

Did Anaconda live up to sales and marketing promises?

I wasn't involved with the selection/purchase process

Did implementation of Anaconda go as expected?

Yes

Would you buy Anaconda again?

Yes

Other Software Used

KNIME Analytics Platform, Microsoft Power BI, Microsoft Office 365

Likelihood to Recommend

For anyone who's starting data analytics, Anaconda is great because you don't have to deal with installing and knowing all these Python and R packages yourself. Moreover, you learn them as you start using them via Anaconda. If you're going to read, manipulate, preprocess, and write data, Anaconda is great. If you need data visualization, Anaconda has Jupyter Notebook, as well as Matplotlib, and Seaborn. If you need forecasting and prediction, whether it is classification or regression or even unsupervised learning, Anaconda provides the Sci-kit Learn library. Furthermore, you can install Catboost, XGBoost, LGBM via Anaconda, which uses the Sci-kit Learn interface.

All-in-one data science package

Overall Satisfaction with Anaconda