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
Reveal
Score 10.0 out of 10
N/A
Reveal embedded analytics enables teams and customers to drive data insights with embedded intelligence, transforming the user experience of apps.
Built with embed in mind first, on modern architecture, Reveal’s API aims to remove the complexity of embedding analytics into applications. Reveal’s native SDKs can be integrated into applications on any
platform and tech stack including: .NET Core, Java, NodeJS (coming soon), and
front-end technologies such as React, Angular, WebComponent,…
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Pricing
Anaconda
Reveal
Editions & Modules
Free Tier
$0
per month
Starter Tier
$9
per month
Business Tier
$50
per month per user
Enterprise Tier
60.00+
per month per user
Embedded Analytics - Contact Us!
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Offerings
Pricing Offerings
Anaconda
Reveal
Free Trial
No
Yes
Free/Freemium Version
Yes
No
Premium Consulting/Integration Services
Yes
Yes
Entry-level Setup Fee
No setup fee
Optional
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More Pricing Information
Community Pulse
Anaconda
Reveal
Features
Anaconda
Reveal
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Anaconda
9.3
25 Ratings
11% above category average
Reveal
-
Ratings
Connect to Multiple Data Sources
9.822 Ratings
00 Ratings
Extend Existing Data Sources
8.024 Ratings
00 Ratings
Automatic Data Format Detection
9.721 Ratings
00 Ratings
MDM Integration
9.614 Ratings
00 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Anaconda
8.5
25 Ratings
1% above category average
Reveal
-
Ratings
Visualization
9.025 Ratings
00 Ratings
Interactive Data Analysis
8.024 Ratings
00 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Anaconda
9.0
26 Ratings
10% above category average
Reveal
-
Ratings
Interactive Data Cleaning and Enrichment
8.823 Ratings
00 Ratings
Data Transformations
8.026 Ratings
00 Ratings
Data Encryption
9.719 Ratings
00 Ratings
Built-in Processors
9.620 Ratings
00 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Anaconda
9.2
24 Ratings
9% above category average
Reveal
-
Ratings
Multiple Model Development Languages and Tools
9.023 Ratings
00 Ratings
Automated Machine Learning
8.921 Ratings
00 Ratings
Single platform for multiple model development
10.024 Ratings
00 Ratings
Self-Service Model Delivery
9.019 Ratings
00 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Anaconda
9.5
21 Ratings
11% above category average
Reveal
-
Ratings
Flexible Model Publishing Options
10.021 Ratings
00 Ratings
Security, Governance, and Cost Controls
9.020 Ratings
00 Ratings
BI Standard Reporting
Comparison of BI Standard Reporting features of Product A and Product B
Anaconda
-
Ratings
Reveal
7.0
10 Ratings
0% below category average
Pixel Perfect reports
00 Ratings
6.58 Ratings
Customizable dashboards
00 Ratings
7.410 Ratings
Ad-hoc Reporting
Comparison of Ad-hoc Reporting features of Product A and Product B
Anaconda
-
Ratings
Reveal
7.3
10 Ratings
7% below category average
Drill-down analysis
00 Ratings
7.09 Ratings
Formatting capabilities
00 Ratings
7.310 Ratings
Report sharing and collaboration
00 Ratings
8.09 Ratings
Data Discovery and Visualization
Comparison of Data Discovery and Visualization features of Product A and Product B
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.
As a company responsible for people money we have to deal with following challenges every day: Clients who want to track the status of their transfers. Licensing agencies who need to ensure professional standards are met. Internal team managers who need to track client and staff progress to ensure company progression and success. Reveal does a good job as self-service tool enabling the accountable parties to have full access to important insights 24/7. The prebuilt dashboard themes save time and investment as we don’t need to hire a dedicated data analyst. The interactive dashboards give full transparency. The ability to easily create, analyze and report keeps clients, partners and stuff on the same page.
Anaconda is a one-stop destination for important data science and programming tools such as Jupyter, Spider, R etc.
Anaconda command prompt gave flexibility to use and install multiple libraries in Python easily.
Jupyter Notebook, a famous Anaconda product is still one of the best and easy to use product for students like me out there who want to practice coding without spending too much money.
Ease of Use - Reveal is super intuitive when it comes to creating dashboards. You don't need to be a data expert, which is key for me.
Sharing - The ability to share across our teams, locations, and with clients is great. We create teams for our different clients and share dashboards there that also are connected to our company dashboards.
Support and Roadmap - Reveal support has been great. They care about the needs of their customers. They have released 3 updates in the last few months, and they are adding a lot of value.
I used R Studio for building Machine Learning models, Many times when I tried to run the entire code together the software would crash. It would lead to loss of data and changes I made.
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.
As a developer of the project, I feel comfortable with this tool for its peculiarities: acceptable costs, simple configuration, creation and maintenance of simple reports, fairly complete account management, also, not least, I appreciate the work done by their technical support always timely intervention and, above all, resolutive. Furthermore, as far as end users are concerned, I found a good appreciation of the proposed reports
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.
Reveal has a great usability for any level of computer user. The only major thing I see that is not exactly user friendly, is the color scheme issue I stated earlier in my review. Although, I am coming from a graphic design background, I need a platform that every team member in our office can use.
This assessment is due to the fact that I have not yet found Reveal not available for use. Apart from some problems of development crash, then fixed by the product assistance service, I have not found any particular problems or loss of time caused by the instrument.
The pages load rather quickly even in the presence of several elevations in the same dashboard that insist on different data sources and with visualizations that insist on different types of graph. I can only be satisfied with these performances.
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.
None in particular, however, would be welcome if improvements were made in the personalization of the prospects and in the connection between them (perhaps being able to transfer the selections present in one prospect to another recalled by the first).
I have experience using RStudio oustide of Anaconda. RStudio can be installed via anaconda, but I like to use RStudio separate from Anaconda when I am worin in R. I tend to use Anaconda for python and RStudio for working in R. Although installing libraries and packages can sometimes be tricky with both RStudio and Anaconda, I like installing R packages via RStudio. However, for anything python-related, Anaconda is my go to!
Lacks ability to generate analytics as complex as Tableau and not as easy to embed and interface with other software and databases as Looker. But a very good option for those not needing the complexities found in other products.
This evaluation is the result of the fact that I have not had the opportunity to deepen the Reveal interface with other tools and / or other software, so the evaluation that I am giving follows what I have been able to read regarding the characteristics of the product online.
It has helped our organization to work collectively faster by using Anaconda's collaborative capabilities and adding other collaboration tools over.
By having an easy access and immediate use of libraries, developing times has decreased more than 20 %
There's an enormous data scientist shortage. Since Anaconda is very easy to use, we have to be able to convert several professionals into the data scientist. This is especially true for an economist, and this my case. I convert myself to Data Scientist thanks to my econometrics knowledge applied with Anaconda.