21 Reviews and Ratings
267 Reviews and Ratings
Dataiku DSS is very well suited to handle large datasets and projects which requires a huge team to deliver results. This allows users to collaborate with each other while working on individual tasks. The workflow is easily streamlined and every action is backed up, allowing users to revert to specific tasks whenever required. While Dataiku DSS works seamlessly with all types of projects dealing with structured datasets, I haven't come across projects using Dataiku dealing with images/audio signals. But a workaround would be to store the images as vectors and perform the necessary tasks.Incentivized
Does great at open canvas editing and letting you fully customize without the need for a grid. It is democratizing self-service no-code analytics. You do not need to be a data or analytics engineer to get started, and you can go very far based on how intuitive and straightforward the UI is. Some of the biggest challenges with Looker Studio relate to user management/security, embedding options, and issue support. For a long time, every user needed to have a Gmail to invite them to view a dashboard via login, not sure if that has been improved yet. You can let any user view without logging in, but that is not always recommended due to security reasons. In terms of embedding, you can only iframe dashboards. More sophisticated BI tools let you embed elements via API or Javascript. Iframing dashboards also make drill downs and dashboard to dashboard navigation tricky/near impossible. There is also no ability to contact Google for support when bugs or outages happen. They point everyone to the Data Studio community. There is some ability to get in contact with Google if you have an enterprise-level contract with Google Cloud, but the path for support is very ad hoc and not always fruitful.Incentivized
The intuitiveness of this tool is very good.Click or Code - If you are a coder, you can code. If you are a manager, you can wrangle with data with visualsThe way you can control things, the set of APIs gives a lot of flexibility to a developer.Incentivized
Self-serviceEasy to use, point and clickLittle to no training requiredEasy to share internally and externallyRich visualizationsCanned reportsEasy to copy/paste/dupe existing reportsAbility to join data setsEasy integration with various data sourcesFlexible data integrations, including lowest common denominator (CSV, XLS, G-Sheets)Wide range of APIsSecure / authentication via Google SSOEasy to share / re-assign ownership of reports and data sourcesIncentivized
End product deployment.Incentivized
Few functionalities are very exclusive only for data studio.It's time taking to load data and at the same time only single Data source can be connected.When editing the reports you have to switch between Edit and View mode to see how does the change looks like.
It is the simplest and least expensive way for us to automate our reporting at this time. I like the ability to customize literally everything about each report, and the ability to send out reports automatically in emails. The only issue we have been having recently is a technical glitch in the automatic email report. Sadly, there is almost no support for this tool from Google, but is also free, so that is important to take into consideration Incentivized
As I have described earlier, the intuitiveness of this tool makes it great as well as the variety of users that can use this tool. Also, the plugins available in their repository provide solutions to various data science problems.Incentivized
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 Incentivized
The support team is very helpful, and even when we discover the missing features, after providing enough rational reasons and requirements, they put into it their development pipeline for the future release.Incentivized
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.Incentivized
Strictly for Data Science operations, Anaconda can be considered as a subset of Dataiku DSS. While Anaconda supports Python and R programming languages, Dataiku also provides this facility, but also provides GUI to creates models with just a click of a button. This provides the flexibility to users who do not wish to alter the model hyperparameters in greater depths. Writing codes to extract meaningful data is time consuming compared to Dataiku's ability to perform feature engineering and data transformation through click of a button.Incentivized
Google Data Studio provides a great feature set considering its price point, especially when compared to commercial options from Microsoft and Tableau. While it may not be as versatile when it comes to working with and developing complex datasets, there is enough charm in its simple, easy-to-use UI to allow not-so-complex analytics to be conducted without having to hire a data analyst.Incentivized
Given its open source status, only cost is the learning curve, which is minimal compared to time savings for data exploration.Platform also ease tracking of data processing workflow, unlike Excel.Build-in data visualizations covers many use cases with minimal customization; time saver.Incentivized
Free, so the only investment is timeBecause it doesn't have native support of non-Google sources, it can cost more money than TableauThe time spent formatting the templates or building connectors can have a negative impact on ROIAs a agency, charging for the reporting service is profitable after the first month or two after building the dashboard.Incentivized