What users are saying about
53 Ratings
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Top Rated
89 Ratings
53 Ratings
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Score 8.6 out of 101

Google Data Studio

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Top Rated
89 Ratings
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Score 8.3 out of 101

Likelihood to Recommend

Anaconda

Anaconda is great for academic and private organizations that cannot afford more expensive Python/R package managers. Also, it is more appropriate for intermediate to advanced Python users--Anaconda can be somewhat frustrating for beginners, as it takes some practice to get comfortable with the workflow. I find it particularly useful for working in teams, because if everyone uses the same package manager, it is easier to troubleshoot issues and makes for reproducible research. For wealthier organizations, a premium package management system (with tech support) would be ideal. Anaconda is also great for people working independently on code development.
Maike Holthuijzen profile photo

Google Data Studio

Well Suited: Simple/complex reports as long the source is from a Google app; for super quick reporting with an Excel file; If you are not a data professional but still want to start with reporting. Less appropriate: If you have used an enterprise reporting tool such as Power BI or Tableau, you might not see this as an equivalent tool or replacement tool.
No photo available

Feature Rating Comparison

Platform Connectivity

Anaconda
6.7
Google Data Studio
Connect to Multiple Data Sources
Anaconda
9.0
Google Data Studio
Extend Existing Data Sources
Anaconda
8.0
Google Data Studio
Automatic Data Format Detection
Anaconda
3.0
Google Data Studio

Data Exploration

Anaconda
7.7
Google Data Studio
Visualization
Anaconda
8.0
Google Data Studio
Interactive Data Analysis
Anaconda
7.3
Google Data Studio

Data Preparation

Anaconda
7.4
Google Data Studio
Interactive Data Cleaning and Enrichment
Anaconda
8.0
Google Data Studio
Data Transformations
Anaconda
8.7
Google Data Studio
Data Encryption
Anaconda
6.0
Google Data Studio
Built-in Processors
Anaconda
7.0
Google Data Studio

Platform Data Modeling

Anaconda
7.9
Google Data Studio
Multiple Model Development Languages and Tools
Anaconda
9.0
Google Data Studio
Automated Machine Learning
Anaconda
6.5
Google Data Studio
Single platform for multiple model development
Anaconda
8.3
Google Data Studio
Self-Service Model Delivery
Anaconda
7.7
Google Data Studio

Model Deployment

Anaconda
7.0
Google Data Studio
Flexible Model Publishing Options
Anaconda
7.4
Google Data Studio
Security, Governance, and Cost Controls
Anaconda
6.7
Google Data Studio

BI Standard Reporting

Anaconda
Google Data Studio
7.9
Pixel Perfect reports
Anaconda
Google Data Studio
7.4
Customizable dashboards
Anaconda
Google Data Studio
8.5
Report Formatting Templates
Anaconda
Google Data Studio
7.6

Ad-hoc Reporting

Anaconda
Google Data Studio
7.9
Drill-down analysis
Anaconda
Google Data Studio
7.4
Formatting capabilities
Anaconda
Google Data Studio
7.7
Integration with R or other statistical packages
Anaconda
Google Data Studio
7.4
Report sharing and collaboration
Anaconda
Google Data Studio
9.2

Report Output and Scheduling

Anaconda
Google Data Studio
8.2
Publish to Web
Anaconda
Google Data Studio
8.7
Publish to PDF
Anaconda
Google Data Studio
8.1
Report Versioning
Anaconda
Google Data Studio
7.5
Report Delivery Scheduling
Anaconda
Google Data Studio
8.1
Delivery to Remote Servers
Anaconda
Google Data Studio
8.7

Data Discovery and Visualization

Anaconda
Google Data Studio
7.6
Pre-built visualization formats (heatmaps, scatter plots etc.)
Anaconda
Google Data Studio
7.7
Location Analytics / Geographic Visualization
Anaconda
Google Data Studio
7.8
Predictive Analytics
Anaconda
Google Data Studio
7.2

Pros

Anaconda

  • Clear install story. There are a lot of ways to install python. There's only one way to install anaconda. This makes teaching and standardizing much easier.
  • Batteries included. It's easy to install things in python, but anaconda ships with most of what you need out of the box. This helps with standardization and reproducibility.
  • Good integrations with Jupyter and other visual tools. Jupyter is really convenient when learning various python packages. Anaconda makes these tools easy to launch and to use.
Matthew Deakyne profile photo

Google Data Studio

  • Pre-loaded Report Templates: Without a data visualization experience/training it's most likely difficult to set up the desired dashboard you envision. Fortunately, Google Data Studio offers pre-loaded reports for the most common data source connections. These common connections include: Google Ads, Firebase, Google Search Console, Google Analytics, and more. They save a lot of time and are easy to substitute data variables.
  • Being a remote company, it can be difficult to share in real-time... not with Google Data Studio. If our team is viewing the data on a call, we are able to update the dashboard in real-time and everyone is able to see the changes made without refreshing. Subsequently, as one user is able to change data parameters (dates, labels, etc) and the rest viewing the data are able to follow along.
  • It can be difficult to get ideas how you should prepare your data - which KPIs should I include? In what order? Should I use a pie graph or bar chart? Thanks to Featured Data Studio reports I'm able to look at shared reports generated by others to get ideas on how to set up similar data.
Sam Lepak profile photo

Cons

Anaconda

  • Although some other users mentioned the installation is "simple", we did encounter some challenge in a highly controlled environment (due to security reasons).
  • Jupyter Notebook is extremely slow when the client/server side of the network's speed/bandwidth is not balanced.
  • Bootstrapping Anaconda takes too long, sometimes I even started doubting it would respond any more.
  • If there are extra python packages you need but are not by default installed by Anaconda, then some efforts will be required to figure out how to put them in the right place.
No photo available

Google Data Studio

  • Community connectors are developed by third parties and sometimes cost money, which can disrupt building free dashboards
  • Reconciling disparate / multiple file types can be a hassle and usually requires doing it off-site (in SQL) to create a master data set for ingestion and viz in the Data Studio platform
Leah Jakaitis profile photo

Likelihood to Renew

Anaconda

Anaconda 7.0
Based on 1 answer
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.
Matthew Deakyne profile photo

Google Data Studio

No score
No answers yet
No answers on this topic

Usability

Anaconda

Anaconda 8.0
Based on 1 answer
It's really good at installing and getting started. It's less usable and configurable after that. If you stay in the ecosystem, and don't know how to Python any other way - it works really well.
Matthew Deakyne profile photo

Google Data Studio

Google Data Studio 9.0
Based on 3 answers
Google Data Studio has a clean interface that follows a lot of UX best practices. It is fairly easy to pick up the first time you use it, and there is a lot of documentation on line to help troubleshoot, if needed
Meredith Walter profile photo

Support

Anaconda

Anaconda 8.0
Based on 1 answer
Prompt response.
No photo available

Google Data Studio

Google Data Studio 6.2
Based on 5 answers
I give it a lower support rating because it seems like our Dev team hasn't gotten the support they need to set up our database to connect. Seems like we hit a roadblock and the project got put on pause for dev. That sucks for me because it is harder to get the dev team to focus on it if they don't get the help they need to set it up.
Jordan Comstock profile photo

Alternatives Considered

Anaconda

ANACONDA VS Alteryx Analytics: Even though I find Alteryx to be an excellent tool for managing extremely massive data, Anaconda is much better and easy for analytics.Anaconda VS. MicroStrategy Analytics: Compared with Anaconda, MicroStrategy Analytics is very difficult to use and counter-intuitiveAnaconda VS. Power BI For Office 365: One of the main advantages of BI for Office 364 is its capacity to data connectivity. However, it's very hard to edit data connections, once BI for Office is deployed in other platforms
Mauricio Quiroga-Pascal Ortega profile photo

Google Data Studio

Before using Data Studio, I was just pulling reports from Google Analytics and building presentations/dashboards with that data. This took a lot more time and forced me to make manual updates regularly. Data Studio takes on more of that behind-the-scenes work - but it still is necessary to have a human eye on the numbers to make sure the reports are built in the right way and are showing things that make sense
Ben Rubenstein profile photo

Return on Investment

Anaconda

  • We can get any new employee set-up on Python for Machine learning in minutes, without any assistance from IT. That's real $ savings.
  • We started to experiment with Machine Learning a lot more, which leads to creating new projects which can have a tremendous impact on the business.
No photo available

Google Data Studio

  • Once the reports are set up, this definitely saves time on the regular reporting deadlines (monthly, biweekly, etc.)
  • However, when you run into a roadblock while translating a current report into GDS (i.e. GDS doesn't have a feature you need), it's hard to work around it. So until GDS becomes extremely robust, there are still cases where it can't be used.
Tegan Jenner profile photo

Pricing Details

Anaconda

General

Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No

Google Data Studio

General

Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No

Rating Summary

Likelihood to Recommend

Anaconda
8.5
Google Data Studio
8.3

Likelihood to Renew

Anaconda
7.0
Google Data Studio

Usability

Anaconda
8.0
Google Data Studio
9.0

Support

Anaconda
8.0
Google Data Studio
6.2

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