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Great hardware to safeguard our accounts with 2FA, which includes a great cryptographic security to enhance identification.

It could have a good design or improvements to the hardware and can be improved and made powerful after all its google product can have improvement with type b and c with same hardware

Protection against any kind of phishing safe browsing environment with awesome speed cryptography hasn't slow down the bandwith

Extracting all kind of data you want in a very User-Friendly interface, The capability of merging multiple explores. Replaces the standard understanding of DBM

Browsing through the Explores without knowing the details of each Refreshing the data Clearing the cache takes time some times

Analysing Data Gap Analysis Market Analysis Root Cause Analysis

Looker makes it easy to identify potential upsells.

Loading reports will take a while. Seriously.

Finding potential candidates for upsells.

What I like the most is the ease of creating beautiful analytic views, well structured and without compromising the performance of my application. Also, the customer success teams' support is excellent.

There are not many things I don't like. What I have are suggestions. Maybe making the connection between Dashboard a little more flexible would be an interesting improvement. Another suggestion would be to make it possible to create dynamic LookML parameters. Finally, to provide a mechanism to allow creating a filter suggestion from a derived table that has a constant as a parameter.

I work creating reports with visuals, dashboards, and real-time dashboards. The greater benefit is the value we can provide to the client with the data visualization we created.

Easy to implement and manage in Android applications with firebase account setup and trust of google. It is showing detailed traces and has good analytics tool.

It should link all common system level exceptions to solutions otherwise working fine.

Add and manage crash analytics management in Android applications.

Easy to integrate in applications like mobile and web applications. Real time callback is best thing to update fast in UI.

More complex data structures are become slower cause it store as json but still it provides fast connection within table

To store and manage data for firebase keys in multiple applications.

We have integrated our internal system, which doesn't have great reporting, with Looker and so live data feeds into it. This allows for a wealth of reporting and data collation. The possibilities really are endless.

Naturally, because it is such a powerful tool, it does take some getting used to, which could also be a positive. I have been using it for 12 or so months now and feel as though I have only scratched the surface of what Looker can deliver.

As stated previously, our internal system doesn't allow for great reporting, which Looker fixes 10-fold.

Looker, besides being a powerful BI tool for both developers and business users, Looker offers strong customer service and technical support. Representatives are happy to work through problems with you and regularly go above and beyond. If a solution hasn't been found, a feature request will be made.

I have found version control in Looker to be a challenge.

Looker provides a fast go-to-market by allowing us to visualize data already available in our warehouse quickly.

It integrates with all ETL platforms on the market.

I've to explore more, nowdays I'm focus on bigquery integration with ETL plataforms.

Creating a data lake.

For a BI tool, Looker is surprisingly easy to use. We had some basic internal training to learn the platform, but I was quickly up to speed.

Looker's design could be improved. Other BI tools look better from a design perspective.

Looker enabled me to identify top users of our product to run effective targeted advocacy campaigns. I was quickly able to add filtering criteria to identify geographical groups.

Easy to integrate with pvc and so it is fast

Online user interface, it needs improvement but you can expect the basics

I have integrated with our private cloud to deploy microservices on GKE

This software seamlessly integrates with Bitbucket and Github. It is very user-friendly, offering a click interface. Even non-computer scientists use it and look at the sections of the code they understand to provide feedback. This tool has improved our productivity and made code writing by multiple people much more straightforward.

The software states that it works best while using the chrome browser (which I do not like). I noticed that most of the features of the software work great in other browsers, but using chrome is the best choice.

Before google cloud source repositories, having more than one person work on a code was very painful. With this software, collaborations are seamless, and the group is more productive. It is a win-win situation using this software; the people writing the code are spending less effort to achieve the same outcome. The non-code writing people in the group can still look at the code sections relevant to their work and provide feedback immediately.

As a product manager, I can easily take Firestore data from Google Cloud and create dashboards that allow me to visualize data in seconds without writing any code. Data studio is free and gets the job done. 100% recommend.

Permissions settings and ownership can get complex in a bigger organization which can lead to broken data connections.

GDS solves the problem of not being able to visualize data stored in Firebase without creating a custom front-end or using an expensive 3rd party tool.

The action hub in looker is amazing , we can connect multiple third party applications and do effective analysis. Integrates well with all data tools One and only BI tool with version control

Cost is bit high compared with other BI tools

We can fully automate a workflow using looker and do real time analytics

IT syncs seamlessly to SFDC and pulls into all the relevant data I need to view at any given time. It also updates very quickly!

Every once in a while when updates are made to our SFDC instance things can break but I don't necessarily attribute that to Looker - more on our end.

Keeping track and visualizing data that is stored in multiple platforms - it helps a lot with organization

Allows Look ML modeling and data exploration through models. Has an excellent structure for Lineage and Data dictionary and supports multiple external vendor integrations. There is a learning curve to understanding the LookML language but its easy once you get going. PDT is also another great functionality for faster data explorations.

Having a lot of Logic and PDT in Looker and LookML could be riskier for the business since all the data lies in looker and cannot be easily accessed outside the looker environment.

Data Modeling and Self Serve Analytics

Super easy to set up and the syntax is easy to learn, very similar to SQL. It's very flexible and can sit on top of multiple different types of databases, like the most commonly used snowflake and redshift. It can also be used together with GitHub or other version control tools so you can collaborate with other team members easily. Because it's easy to learn and use, it's enabling lots of users with no technical background to query databases directly through Looker. Teams in analytics, marketing, reporting, and product can all collaborate using the same tool easily. Looker is the best for exploratory analysis, you can easily pivot, filter, or join data from different views, finding trends and differences is a lot easier.

It's generally a great tool to use, but I don't like some smaller things related to it and also hope Looker could improve. On the data visualization side, I wish there are more different color palettes. The default ones are sometimes too bright and sometimes not helpful enough to visualize the differences. And for the customizing dimensions and measures, finding an existing dimension or measure is always auto-filled but I would rather fill in the dimension name by myself instead of the wrong auto-filled one. Besides formatting data into thousands, millions and percentages are sometimes tricky.

I'm using Looker for a lot of ad-hoc, business reporting, and also exploratory analysis when abnormal happens. For ad-hoc analysis, it's fast and convenient as long as the Looker Developers build a good foundation of the explores, with enough dimensions and measures to use. For business reporting, it was also convenient and generating lots of impacts. Various dashboards are scheduled to send to different stakeholders so they don't have to refresh and wait for the dashboards every day. For exploratory analysis, because it's such a powerful visualization tool, it helped me figure out a lot of data problems either temporary or long term.

The attention they give you is always the best. You can always find answers by chatting with them in the help section.

The community is small compared to other tools, and there are still some things to improve.

Dashboards and sales data analysis in real-time. Looker is pretty versatile.

The options it gives to show the data as visual

Nothing as of yet. It feels way better in ever release. Maybe video tutorials are lacking

We are generating reports for our banking customers

Cloud Dataflow offers serverless processing for handling Big Data. It can crunch millions of records in any form event based or batch and has excellent throughput. With the different sdks it provides like Python, Java etc. it is very developer friendly as well.

Nothing really. There need to be some added features to the Python sdk like in Java, but that will happen as the product grows.

Processing Big data. Both stream and batch processing.