Anaconda Enterprise is a modern and dynamic data science software platform that allows teams of data scientists to create, supervise, and automate AI-powered data science models and pipelines across production environments and server clusters. Anaconda Enterprise is equipped with collaboration features which enable team members to share data science projects with each other and edit them in real time. They can also make their resources readily accessible to everyone in their team such as machine-learning models, online notebooks, dependencies, and dashboards.
Anaconda Enterprise is a scalable data science solution which means users will be able to quickly provision their data science projects and applications with all the necessary computation resources they need. The platform permits them to deploy their data science models and resources to either on-premises or cloud-based environments.
With Anaconda Enterprise, the tools, data science model versions, and packages being utilized by teams can be easily managed, governed, and controlled. The platform can generate logs that record the activities being performed by each team member. For a more secure collaboration, Anaconda Enterprise implements TTL or SSL encryption so that team members can communicate and collaborate over their network with confidence, without being bothered by security breaches and issues like data leakage, data theft, and more.
Show MoreEnterprise-Ready Data Science Platform
Anaconda Enterprise is an enterprise-ready data science platform. But what is data science really all about? Data science is a field that applies various theories, methods, systems, and processes from different fields and disciplines in order to gain insights and knowledge from data. It combines scientific methods, mathematics, statistics, information science, and computer science; and can be applied to activities related to business intelligence, business analytics, and predictive modeling. Anaconda Enterprise automates how organizations and businesses implement data science projects, models, and processes; helping them perform data analytics much better.
Real-Time Collaboration
Collaboration is one of the key features offered by Anaconda Enterprise. It unifies data science projects and the corresponding resources in one central location and permits team members to collaborate in real time. Team members can share data science projects and dependencies with their colleagues and the latter can access all of them from a convenient place.
Access Convenient Data Science Environments Through Jupyter Integration
As part of its real-time collaboration capabilities, Anaconda Enterprise integrates with Jupyter-based software solutions which include Jupyter Notebooks and JupyterLab. Jupyter Notebooks is an open-source and open-standards web-based tool which allows users to build and share documents for data visualization, data cleaning, numerical simulation, machine learning, or statistical modeling.
These documents are called notebooks or web-based documents that contain live codes, equations, data visualizations, and narrative texts. Meanwhile, JupyterLab is a computational environment that provides an intuitive user interface for managing Jupyter projects. Because Anaconda Enterprise supports integration with these solutions, users will be able to collaborate directly on the Jupyter web-based documents they are sharing with their team members. In addition, the platform lets them handle different versions of their browser-based notebooks as well as control how those notebooks are being accessed.
Scalable Architecture That Can Automatically Adjust
The enterprise data science platform has a scalable architecture, and that can be observed in its ability to distribute Anaconda Enterprise libraries and resources across the clusters of servers handled by Hadoop and Apache Spark. Hadoop is a big-data framework which distributes large collections of data across multiple nodes within a cluster of servers. When it comes to Apache Spark, this is also a big-data framework which is used for processing those data collections. As a scalable data science solution, Anaconda Enterprise can automatically scale up or down depending on the number of cluster nodes that users need to distribute data collections to. For example, users will be able to instantly add new cluster nodes or delete existing ones.
Self-Service Deployment Features
Anaconda Enterprise is built with amazing deployment features. For example, it has a self-service deployment capability which enables users to gain full flexibility and control over the deployment of AI-powered data science models, dashboards, and browser-based notebooks. With just a single click, users can deploy any of these. Another deployment feature available in Anaconda Enterprise is its remote deployment capability. Here, users will be able to remotely deploy their data science projects and models, and computational resources to Hadoop or Apache Spark server clusters. Deployments can also be easily managed for on-premise environments and cloud-based services such as Amazon Web Services (AWS), Microsoft Azure, and Google Cloud.
Complete Governance Of Data Science Packages, Versions, And Tools
Governing data science projects, models, and resources is made easy using Anaconda Enterprise. It has an online repository where on-premises data science packages and stacks can be stored. Furthermore, whatever tools, packages, and versions data analysts and scientists are utilizing; the platform makes sure that they are able to control them.
License Management, Auditing, And Reporting
The data science platform also has license management feature. It lets users filter licenses associated with their data science projects and applications. In addition, the platform has the ability to generate reports as they audit their licenses.
Event Logging And Tracking
Another governance feature of Anaconda Enterprise is that it enables users to record and track all activities and events related to their data science projects, packages, and deployments. Thus, these events and activities can be logged and audited effortlessly.
Token-Based Acess
Anaconda Enterprise provides security features which help teams guarantee that their projects and resources are accessed only by authorized individuals. The platform uses a token-based system of accessing the deployed data science models and applications. In other words, users will be able to utilize their models and applications without exposing any sensitive data or information. In a token-based system, data or information are represented by tokens. Then, these tokens are the ones being stored and processed instead of the original data or information.
Centralized Management Of Access Controls
Furthermore, Anaconda Enterprise centralizes the management of access controls and configurations. Whether users are handling access on a per user, role, or group basis; they can do this in a central location. Additionally, the enterprise data science solution supports integration with identity providers like LDAP, Active Directory, SAML, and Kerberos. Thus, users can access their data science projects, models, and resources using their credentials and profiles from their existing identify provider; streamlining user authentication and access.
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Anaconda Enterprise is one of the top 10 Predictive Analysis Software products
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Every company has different needs and needs a software that can be customized for their size, type of staff members and customers, and the specific industry they are in. For these reasons, no software can provide perfect features out-of-the-box. When you try to find a software app, first be sure what you need it for. Read some Anaconda Enterprise Predictive Analysis Software reviews and ask yourself do you desire basic features or do you need complex tools? Are there any industry-specific features that you are seeking? Get the answers to these queries to aid your search. There are lots of elements that you need to consider and these include your budget, particular business requirements, your organization size, integration needs etc. Take your time, try out a few free trials, and finally select the platform that offers all that you need to enhance your company effectiveness and productivity.
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Anaconda Enterprise supports integration with the following big data frameworks, data management solutions, identity providers, and cloud services:
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ADD A REVIEWThe most favorable review
PROS: What I love about Anaconda is that it provides a certain level of freedom to users, as opposed to other platforms in the market. For one, I can easily modify R code and python as I see fit. Not to mention, it is designed in a way that promotes a smoother workflow and faster processing, especially with its environment easily configured according to my specific needs too. I can either use its tools separately or as part of a more intricate work process by installing several available packages. There are also a myriad of literature (including videos and a supportive community of users) within the program that can guide novice and seasoned users alike. Some of the features that I like include RStudio, Spyder, Jupyter Notebook, and Jupiter Lab, just to mention a few. The platform installation is fairly easy plus can be integrated with some of the programs and data libraries that we already use.
CONS: Nothing at all - Anaconda works perfectly fine in my opinion.
The least favorable review
PROS: First of all, Anaconda is equipped with a dozen helpful tools. It allows me to work continuously (and with lesser room for error) within its environment without having to switch from one program to another. It is designed with an intricate web of inter-dependencies between tools so that it supports the user in every possible scenario and various work modules.
CONS: Anaconda, as complete and well-designed as it may be, requires a certain level of trust from the user. Just think about it: you will need to save all of your in-progress projects within it. So if the system crashes and fails, you run the risk of losing your project altogether. Another disadvantage is that you will have to draft and code your own module if you need something different from what the program already provides.
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Well-designed and comes complete with intricate inter-dependencies within its network.
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PROS: Within Anaconda is a set of robust programming tools and bundles that addresses a myriad of needs. The Spyder, Jupyter notebook, the visual studio, and R studio code are just some of its tools that I use regularly. Users, like myself, no longer need to install additional IDEs just to work with multiple languages. Not only that, but switching between programming languages is not only possible but easy to boot.
CONS: In terms of performance and power, I really have nothing negative to say about Anaconda. However, to fully maximize this program and to enjoy its full potential, you will need to launch it in an equally powerful and updated device because it does require a lot of memory.
Can take up too much RAM space but otherwise great!
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PROS: Setting up the program and understanding its inner workings are easy enough. Its straightforward design leaves very little space for confusion with its four major tabs in the interface: the home tab, environment learning, and the community tabs. If ever you do hit walls, the program provides tutorials as well as a platform for users to interact as a community of programmers within the system. The environment tabs are for easy installation of modules and the interpretation of IDEs.
CONS: To be honest, Anaconda can be quite hefty in terms of power and RAM usage. Browsers often crash and stop responding after a while of usage. Of course, the best way to circumvent this issue is to make sure that your PC or laptop is sufficiently powerful and updated.
Complete and all-inclusive
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PROS: Anaconda has an impressive breadth of machine learning tools. Its main selling point is its user-friendliness. Plus, it comes complete with in-tool devices such as the Spyder, Jupyter notebook and lab, and so much more.
CONS: I have yet to encounter a facet of Anaconda that I don't like.
Lets me work with multiple languages
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PROS: First of all, Anaconda is equipped with a dozen helpful tools. It allows me to work continuously (and with lesser room for error) within its environment without having to switch from one program to another. It is designed with an intricate web of inter-dependencies between tools so that it supports the user in every possible scenario and various work modules.
CONS: Anaconda, as complete and well-designed as it may be, requires a certain level of trust from the user. Just think about it: you will need to save all of your in-progress projects within it. So if the system crashes and fails, you run the risk of losing your project altogether. Another disadvantage is that you will have to draft and code your own module if you need something different from what the program already provides.
Provides all the tools I need to complete projects.
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PROS: Anaconda facilitates a smooth workflow - from the beginning to the end of a project - thanks to its intricate web of inter-dependent tools. Of course, it doesn't hurt that I continue to enjoy its benefit at no cost too.
CONS: You will have to purchase licenses if you want to work with NumbraPro, for example.
It truly delivers and helps me complete my projects in record time.
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PROS: I work with data daily and Anaconda is probably one of the most reliable tools that I've worked with. So far, it has provided me with a satisfying amount of data analysis tools. There's Jupyter notebook, Spyder, R studies and so much more - all in one robust program.
CONS: The tool can be quite clunky. It takes a while to load the program itself and an even longer while to open larger files to work. I think that users will feel less frustrated with the pace if there can be a cloud integration somehow.
Great support for software analysts like me
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PROS: What I like best about Anaconda is its ability to translate and work with multiple programming languages all at once. Because of this, it allows developers like me to analyze more than one program at a time. It provides an in-depth investigation of the program so that users like me can pick apart some of its facets and integrate them into another project.
CONS: Without a doubt, Anaconda is a robust programming tool. However, some of its inclusions, such as the Jupiter Notebook, requires a hefty amount of space for it to work smoothly. Personally, my browser has crashed one too many times while on this program. If you decide to run Anaconda, you might as well resign yourself to the fact that it will be the only program you'll be working with for the duration of your computer usage.
The best tool in its category!
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PROS: Anaconda allows me to breeze through my python programming projects. It helps me work at an unimpeded pace. For me, its the best option for running analytics and large data processing projects.
CONS: None that immediately comes to mind.
The perfect open-source platform for data scientists
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PROS: What I love about Anaconda is that it provides a certain level of freedom to users, as opposed to other platforms in the market. For one, I can easily modify R code and python as I see fit. Not to mention, it is designed in a way that promotes a smoother workflow and faster processing, especially with its environment easily configured according to my specific needs too. I can either use its tools separately or as part of a more intricate work process by installing several available packages. There are also a myriad of literature (including videos and a supportive community of users) within the program that can guide novice and seasoned users alike. Some of the features that I like include RStudio, Spyder, Jupyter Notebook, and Jupiter Lab, just to mention a few. The platform installation is fairly easy plus can be integrated with some of the programs and data libraries that we already use.
CONS: Nothing at all - Anaconda works perfectly fine in my opinion.
Can recognize multiple programming languages at a time.
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PROS: Out of all the programming tools available, Anaconda works best for me and my team because its settings can easily be configured according to every user's needs. We don't have to spend a lot of hours trying to adjust the settings. In fact, I might even go as far as to say that it anticipates the needs of its users by providing a set of integrated bundles.
CONS: Without a doubt, Anaconda is equipped with powerful tools that can aid analysts and programmers in their projects. However, the downside to this robustness is that it asks too much installation time and power from your processor to run it smoothly. I've also noticed a few glitches in its configuration that can only be fixed by uninstalling and then reinstalling the program.
The tutorials and its community can help you maximize this tool.
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PROS: The design of the program itself is usable and easy to understand. There's a plethora of tutorials available and a ready community to assist you if you run into trouble while using it as well. The environment tab makes it easy to build your own data library too.
CONS: It requires a sizeable RAM for it to run smoothly.
User-friendly even to beginners
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PROS: The Anaconda platform is perfect for developing python projects. It is well designed - straightforward and easy to understand. It offers a complete suite of tools and is beginner-friendly too.
CONS: It's easy to use, yes, but installing and getting the program up and running can take up a lot of your time.
An impressive tool that lets me work with different languages in one place.
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PROS: There are many things that you can do in Anaconda thanks to its multi-faceted design. There's Jupyter notebook, R studio, Spyder, etc to help you tick to-do lists on your programming projects. If you require further tools, installing them into the program is easy and does not require an inordinate amount of steps too. Some modules, of course, can take more time to install but the process is otherwise smooth.
CONS: More than anything, Anaconda is robust and is an all-in-one tool that supports a myriad of programming languages. Because of this, it can be quite heavy to use and requires a substantial amount of RAM for it to work smoothly. There's also the risk of losing your progress all at once because you'll be putting all your eggs in one basket, so to say.
Probably has one of the most complete suite of services within a programming tool.
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PROS: Anaconda makes it possible to deal with the simplest and/or most complicated programming language. Whatever project or code I need to complete, I can easily run it by Anaconda to create a unified environment, regardless of the medium. It makes the configuration and management of Python modules seem like a walk in the park. I also love how it comes complete with pre-installed programming languages so you can get to work right after installation.
CONS: Admittedly, Anaconda can be quite clunky. It takes time to install; and it takes a considerable amount of power to operate. On top of this, there are chinks in its seemingly robust armor as well. It tends to freeze just at the most crucial part of every project.
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Well-designed and comes complete with intricate inter-dependencies within its network.
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Can take up too much RAM space but otherwise great!
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Complete and all-inclusive
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Lets me work with multiple languages
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Provides all the tools I need to complete projects.
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