Azure Data Science Virtual Machines (DSVM) vs. Looker Studio

Azure DSVM is useful in [a] Machine Learning environment where GPU-based processing is [required]. [The] most relevant [users] for the Azure DSVM is in ML/AI for model training and processing [high-end] CPU tasks with GPU compatibility. Azure DSVM is built for [a] startup to low medium IT environments where the ML/AI-based projects are [carried] out.

Visualizing cross-channel campaign performance can blend data from a few different sources to compare performance metrics like spend, clicks, and conversions side-by-side in a single view, which helps in quick budget reallocation decisions. When dealing with massive volumes of data (millions of rows) or highly complex queries, Looker Studio dashboards can become slow, laggy, or even crash. Performance issues are a frequent complaint when working with large datasets, making it unsuitable for enterprise-level companies

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• Leveraging data.
• Computer vision.
• Data science.

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• Breath of data - the number of ways to interrogate the data is endless, and the options to view metrics alongside each other make for comprehensive datasets.
• Data visualisation and customisation - the options for presenting data and separating out across pages allow for clean visuals and segmented information.
• Easy shareability/usability - a quick and simple tool to introduce colleagues to, and easy to grant access for them to be able to view the data, without having to understand the setup itself.

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• Azure DSVM pricing must be reduced so that an AI-based start-up can use the Azure DSVM.
• Azure must create an environment to use Azure DSVM offline as well.
• Lack of frameworks

• It needs better handling of complex logic. We often need workarounds to perform complex custom calculations, and it can be really unpleasant at times.
• Felt it got slow with a larger data set, and in one minor report, we had to set up time filters so that calculations during spikes could be traced more quickly.
• Compare to competition they need to improve with notification things.

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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

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Looker Studio is easy to use, and it offers a sufficient variety of predefined visualizations to choose from. It's easy for us, and anyone can set up basic reporting without extensive data visualization skills. The interface layout is easy to understand, and it doesn't take long to get used to.

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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.

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It's within the Azure environment and it's easy to manage.

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Looker Studio is far easier to implement, stand up, and learn. The interface is simpler and user-friendly for various levels of data visualization/analysis knowledge and experience. The biggest benefit of Looker Studio, however, is its ease of connection to GA data and speed. Furthermore, since it is an online program/tool, it requires less CPU/battery/storage on the user's device.

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• Azure DSVM is little costly with long term support for ML based environments.
• Azure DSVM is very good for short tasking and costs us [a] little low than the on-prem server.
• [Scaling] option is very convenient.

• Free, so the only investment is time
• Because it doesn't have native support of non-Google sources, it can cost more money than Tableau
• The time spent formatting the templates or building connectors can have a negative impact on ROI
• As a agency, charging for the reporting service is profitable after the first month or two after building the dashboard.

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Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info