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43,622 views|35,128 comparisons
Featured Review
Find out what your peers are saying about Alteryx, Databricks, Knime and others in Data Science Platforms. Updated: January 2022.
564,322 professionals have used our research since 2012.
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"It's interesting. It's user friendly. That's what makes it outstanding among the others. It has a collection of R, Python, and others. Their platform strategy has a collection of many other visualization tools, apart from Spyder and RStudio, which is really helpful for data science. For any data science professional, Anaconda is really handy. It has almost all the tools for data science.""With Anaconda Navigator, we have been able to use multiple IDEs such as JupyterLab, Jupyter Notebook, Spyder, Visual Studio Code, and RStudio in one place. The platform-agnostic package manager, "Conda", makes life easy when it comes to managing and installing packages.""The product is responsive, sleek and has a beautiful interface that is pleasant to use. It helps users to easily share code.""The documentation is excellent and the solution has a very large and active community that supports it."

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"Although Tableau isn't the best for us when it comes to processing and working on live data, it is very good at extracting data for analysis.""It's very easy to visualize data with this product. The visualization maps of and frames that we have been able to cross-reference has been excellent.""The most valuable feature is the user experience.""The ability of filtering and segmentation of the data makes it very flexible compared to other tools.""The geospatial maps representation and the visualizations are nice.""Tableau has improved my organization in a variety of ways, one of its uses being that of data analysis. A feature I have found most valuable is the ease of use and straightforwardness, in addition to the flexibility of Tableau.""It's very easy to set everything up.""From the data science point of view, we use it for model building purposes. For example, if we are using it for a bank and we want to understand how much loan the bank can provide, we can use visualization to show the educational qualification, salary, gender, and city of a customer, and by using this information, we can arrive at the loan amount that this person is eligible for. I can also use it to view all prospective customers, so essentially, this is going to help me in model building as well as in understanding and segmenting customers and doing forecasting and predictive analytics. We use model widgets, and we can create thousands of visualizations, such as motion charts and bubble charts. We can also create animated versions of the graphs and view the data from multiple dimensions. These are the features that we typically use and like."

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Cons
"It crashes once in a while. In case of a reboot or something unexpected, the unseen code part will get diminished, and it relatively takes longer than other applications when a reboot is happening. They can improve in these areas. They can also bring some database software. They have software for analytics and virtualization. However, they don't have any software for the database.""Anaconda should be optimized for RAM consumption.""When you install Anaconda for the first time, it's really difficult to update it.""One thing that hurts the product is that the company is not doing more to advertise it as a solution and make it more well known."

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"I have used Power BI as well as Tableau. There are a couple of interesting features that I like in Power BI, but they are not present in Tableau. For example, in Power BI, if I am looking at country-wise population, I can type and ask for the country that has the maximum population, and it will automatically give an answer and address that query. This kind of feature is not there in Tableau. Similarly, in Power BI, for integrating with the latest ML algorithms, we have decision trees and primarily multiple machine learning algorithms. The decision tree essentially visualizes the patterns in the data. We don't have such a feature in Tableau. If Tableau can integrate with the machine learning algorithms and help us to do visualizations, it would be a wonderful combination. Most of the people are going for Tableau primarily for visualization purposes. However, in the data science industry, users want to do model building as well as tell a story. As of now, Tableau is fulfilling the requirements for visualization purposes. If they can bring it up to a level where I can use it for machine learning purposes as well as for visualization, it would be very helpful. Many people who want to do data science don't want to write a code. Tableau is anyway a drag and drop tool, and if they can provide those options as well, it will be a powerful combination.""Implementation requires a technical background.""Areas for improvement would be visualization and augmented analytics. In the next release, I would like to see automated insights from the data added to the dashboard.""In the cloud sometimes the performance is a little bit slow.""The integration with other program languages, like Python, needs to be better.""I am not a frequent user of this solution, so I am not sure what they've been doing recently. The last time when I used it, I had to use other tools with it for data extraction and cleansing. Its price should also be improved. It is more expensive than Power BI. In terms of training, there is generally better online training for Power BI, but I am not sure of that. It would be helpful to know from where to access its training.""Other tools are more competitively priced.""Whenever it comes to specialized visualization, Tableau is an absolute failure."

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Pricing and Cost Advice
  • "The product is open-source and free to use."
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  • "The company chose to purchase a creator license for me, which was $70. With that license, you can also be an administrator. We also have 20-25 extra licenses and they cost around $20-$35 each. Those are for normal users who will be viewing the dashboards. Those are monthly charges."
  • "Tableau's licensing is pretty straightforward and simple."
  • "ROI is very high, but it requires a data preparation/blending tool."
  • "The cost of the solution should be improved."
  • "It is reasonable and cheap as compared to other major tools. It has a good price, and people go for it because of its pricing."
  • "Pricing is not bad. It's competitive."
  • "At $70 per month, I think the price is a bit scary. I have a small consulting firm in Ghana, working in about 15 different African countries, and when it comes to our part of the world, $70 a month is a lot of money for software."
  • "The professional version of Tableau is quite expensive."
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    Comparison Review
    Guillermo (Bill) Cabiro
    I do use both Tableau and QlikView. Although very different, I really like both solutions. They belong to the new BI generation known as Interactive Visual Analytics. In my opinion, QlikView has a more intuitive interface for regular users or executives that are not technical experts but the development side is a little more complex. Up to version 12 QlikView did not provide drag & drop features. If a user wanted to see something not included in the application the new object had to be created by a power user or developer because Qlikview's scripting has somewhat of a learning curve. On the positive side, QlikView's scripting is a great asset as it functions as an ETL allowing the integration of hundreds of different data sources into the same visual app. Another feature that’s extremely useful is Qlik’s proprietary Associative Model that allows the users to visualize data relationships that exist as well as those that do not. Tableau on the other hand is a lot easier to use for developers, analysts or power users who need to connect, manipulate and visualize data rather quickly. While this makes Tableau a better fit for the more analytical crowd, it may not be as appealing or intuitive to the regular or casual business users as QlikView is. Tableau has full pivot, drag & drop and drill down capabilities that are great for developers or power users. They can rotate measures and dimensions and graph them instantly using visualization best practices as suggested by… Read more →
    Questions from the Community
    Top Answer: 
    With Anaconda Navigator, we have been able to use multiple IDEs such as JupyterLab, Jupyter Notebook, Spyder, Visual Studio Code, and RStudio in one place. The platform-agnostic package manager… more »
    Top Answer: 
    With Anaconda Navigator, we have been able to use multiple IDEs such as JupyterLab, Jupyter Notebook, Spyder, Visual Studio Code, and RStudio in one place. The platform-agnostic package manager… more »
    Top Answer: 
    It depends on the Data architecture and the complexity of your requirement. Some great tools in the market are Qlik Sense, Power BI, OBIEE, Tableau, etc. I have recently started using Cognos… more »
    Top Answer: 
    Both tools have their positives and negatives. First, I should mention that I am relatively new to Tableau. I have been working on and off Tableau for about a year, but getting to work on it… more »
    Top Answer: 
    Tableau is easy to set up and maintain. In about a day it is possible for the entire platform to be deployed for use. This relatively short amount of time can make all the difference for companies… more »
    Ranking
    11th
    Views
    5,552
    Comparisons
    4,680
    Reviews
    3
    Average Words per Review
    523
    Rating
    9.3
    Views
    43,622
    Comparisons
    35,128
    Reviews
    66
    Average Words per Review
    607
    Rating
    8.0
    Comparisons
    Also Known As
    Tableau Desktop, Tableau Server, Tableau Online
    Learn More
    Overview

    Anaconda makes it easy for you to install and maintain Python environments. Our development team tests to ensure compatibility of Python packages in Anaconda. We support and provide open source assurance for packages in Anaconda to mitigate your risk in using open source and meet your regulatory compliance requirements.

    Python is the fastest growing language for data science. Anaconda includes 720+ Python open source packages and now includes essential R packages. This powerful combination allows you to do everything you want from BI to advanced modeling on complex Big Data

    Tableau helps people and organizations become more data-driven as the trusted leader in analytics.

    The Tableau platform provides the breadth and depth of capabilities to serve the needs of even the largest global enterprises in a seamless, integrated experience. Tableau is designed to fit, not dictate your data strategy, and adapts to your environment with unmatched flexibility and choice, while meeting the toughest governance and security requirements.

    People love using Tableau because it is both powerful and intuitive—and offers a fundamentally different user experience by empowering people of all skill levels to explore and analyze data using visuals and natural language. Tableau has become the standard language of analytics for modern business users and continues to lead the industry with the most passionate and engaged user community in analytics, a customer base with millions of users at more than 80,000 organizations, and a deep commitment to customer-focused innovation

    Evaluation Guide: How to choose the right BI & analytics platform

    Redefining the role of IT in modern BI world

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    Sample Customers
    LinkedIn, NASA, Boeing, JP Morgan, Recursion Pharmaceuticals, DARPA, Microsoft, Amazon, HP, Cisco, Thomson Reuters, IBM, Bridgestone
    Accenture, Adobe, Amazon.com, Bank of America, Charles Schwab Corp, Citigroup, Coca-Cola Company, Cornell University, Dell, Deloitte, Duke University, eBay, Exxon Mobil, Fannie Mae, Ferrari, French Red Cross, Goldman Sachs, Google, Government of Canada, HP, Intel, Johns Hopkins Hospital, Macy's, Merck, The New York Times, PayPal, Pfizer, US Army, US Air Force, Skype, and Walmart.
    Top Industries
    REVIEWERS
    Financial Services Firm22%
    Manufacturing Company22%
    Non Tech Company11%
    Pharma/Biotech Company11%
    VISITORS READING REVIEWS
    Computer Software Company23%
    Comms Service Provider18%
    Financial Services Firm13%
    Government7%
    REVIEWERS
    Financial Services Firm13%
    Computer Software Company10%
    Healthcare Company8%
    Energy/Utilities Company7%
    VISITORS READING REVIEWS
    Computer Software Company25%
    Comms Service Provider14%
    Financial Services Firm10%
    Government7%
    Company Size
    REVIEWERS
    Small Business38%
    Large Enterprise63%
    REVIEWERS
    Small Business28%
    Midsize Enterprise20%
    Large Enterprise52%
    VISITORS READING REVIEWS
    Small Business27%
    Midsize Enterprise15%
    Large Enterprise58%
    Find out what your peers are saying about Alteryx, Databricks, Knime and others in Data Science Platforms. Updated: January 2022.
    564,322 professionals have used our research since 2012.

    Anaconda is ranked 11th in Data Science Platforms with 4 reviews while Tableau is ranked 2nd in Business Intelligence (BI) Tools with 93 reviews. Anaconda is rated 9.4, while Tableau is rated 8.0. The top reviewer of Anaconda writes "Responsive, sleek and had a beautiful interface that is pleasant to use". On the other hand, the top reviewer of Tableau writes "Lets me train new users quickly, easily, and intuitively". Anaconda is most compared with Databricks, Amazon SageMaker, Microsoft Azure Machine Learning Studio, Cloudera Data Science Workbench and Alteryx, whereas Tableau is most compared with Microsoft BI, SAP Analytics Cloud, MicroStrategy, ELK Kibana and Qlik Sense.

    We monitor all Data Science Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.