With ever growing Data Science community, and with the growing trend of users shifting and starting with Python, the need of the tools to aide our work is increasing day by day. Anaconda is one such tool which has amassed a huge user base over the years and has proved itself to be one of the most useful package to help Python programmers delve deeper into Data Science.

About Anaconda

Anaconda is now the world’s most popular Python data science platform. The product is lead by Anaconda Inc., which leads other open source projects too. It is a freemium open source distribution of Python for large scale data processing, predictive analysis, and scientific computing and aims to simplify package management and deployment. With over 4.5 million programmers using the Anaconda Distribution, and over 1000+ data science packages, Anaconda Distribution and Anaconda Enterprise provide world class support for production ready deployments of open source, to the programmers as well as over 150+ enterprises, which include giants like IBM, Microsoft, NVidia, Intel etc.. Let’s look into both of them.

Anaconda Distribution: Anaconda Distribution targets the individual programmers and researchers to help them with their data science problems. Majority of the support and use of the whole Anaconda project is from the Anaconda Distribution. Main features of the distribution that entice the developers are as follows:

• Has over 1000 Anaconda- curated and community packages for data science.

• Has a number of IDEs to choose from and develop projects in, for eg. Jupyter, JupyterLab, Spyder etc.

• Numerical and Scientific Computing is a breeze with powerful packages like NumPy, SciPy.

• Analyzing data with scalability and performance with Dask, Pandas, Numba etc.

• Data visualization with the help of Bokeh, Datashader, Holoviews, Matplotlib etc.

• Creates highly accurate and efficient machine learning and deep learning models using theano, Tensorflow, Scikit- learn, h20 etc.

Anaconda Enterprise: Anaconda Enterprise aims at empowering at the organizational level, providing end- to- end platform for developing and deploying data science projects. It aims at three essential requirements for the organizational projects that it provides-

1. Governance: Gives more power to the organization to effectively manage their products, their activity and licensing

2. Scalability: Helping the organization to realize their dream projects easily

3. Security: Securing the proprietary data and products from foreign attacks

To elaborate further, the Anaconda Enterprise provides the following benefits to everyone using the version.

Collaboration

• Centralized, browser-based notebook collaboration with versioning and access control

• Manage and share data science projects and dependencies

Reproducibility

• Upload and share projects and notebooks with portable data science environments

• Mirror data science packages and dependencies within your organization

Deployment

• Industry standard containerization and cluster orchestration technology.

• Scalable on-premises or cloud-based deployment server with configurable cluster sizes.

• Secure project deployments with enterprise authentication and end-to-end encryption.

Scalability

• Easily scale up or down by adding or removing cluster nodes

• Scalable distributed computation resources for project editing and user-deployed data science apps

Security

• Integrated with enterprise-grade identity providers: LDAP, AD, SAML, Kerberos

• Secure network communications and end-to-end TLS/SSL encryption

Governance

• Control packages, versions and tools used by data scientists and analysts

• License filtering and license audit reports

• Event logging and auditing of package, project and deployment activity

Anaconda has been quite successful in providing organizations and users with an immense support for realizing their solutions to data science problems and the community hopes to continue receiving their incredible products further too. You can learn more about Anaconda and its products and can download the same from here.