Google Cloud-anmeldelser og produktdetaljer

The new design, the way I can visualise the results and present them in a professional way to my supperiors.

There are some lags with the search bar but I believe you guys will fix them soon.

I am an analyst and thanks to Looker I can research some data quickly and save a lot of man hours in head banging. The whole team benefits from Looker.

Easy to maintain and integrate without application

Need more stat/reports that way we can understand whats going

Unlimited storage

Easy to use functions. They even have a course to understand report, data source and other stuff

It becomes a bit slow when the data is huge

Interactive dashboards for reporting and analytics

It protects against threats like malware and provides high protection. It has a big community, whenever I am stuck in something I can find the answer from google cloud as it has a big community which gives quick response . This app is very effective and easy, and safe to use.

It sometimes needs coding which is not possible for some people and the UI is also confusing, that's its drawback otherwise this app is excellent with no other limitations and drawbacks in it.

It is a good platform providing feasible cloud-based services and it helps me a lot in my projects . The Google cloud storage helps in storing, processing and managing the data. Here the community is very large which gives a quick response to every problem.

Google Dataflow is great as it provides the easiest and smoothest experience of loading data, be it in Batch or Streaming. The best aspects are ; 1. It provides 100% efficient Big Data processing along with easy data migration. 2. Ability to create custom Apps and design APIs. 3. Its developer-friendly user- interface and working.

I think it is one of the best platforms to work on Big Data but the fact that it is very difficult to understand. Even the helping guides and documentation are limited and the community is not so big. I know in the coming years it can be solved and I hope that it is achieved as soon as possible.

Our company works on emerging technologies to understand the availability and demand of tools and data handling mechanisms. So, we use Google Cloud Dataflow basically to manage data and its manipulation. Also, we manoeuvre its features like Predictive Analysis, Model management, Automation and Machine Learning along with working with Big Data.

it is free. and most importantly the eco system of data connectors make it one of the most powerful data visualisation tool in the market. you can never beat a free software!

the interaction is rather slow and laggy. to maximise GDS, you most likely need 3rd party software like supermetrics. which i have seen their subscription increasing in the last few years.

for now aside from the laggy-ness. it is perfect for my digital agency. i also seeing more and more functionality added. i recall in the past you cant even export as pdf or schedule regular email.

The best thing about Google Cloud Debugger is that it is a very user-friendly debugger that significantly speeds up the debugging process.

One thing that I dislike about Google Cloud Debugger is I had trouble getting started with it and needed to watch several YouTube videos to understand it.

Some problem that I am able to solve using Google Cloud Debugger is utilizing the cloud to deploy machine learning models.

I love it, it is uncomplicated and has very good capabilities to make life easier for BI teams. I like that it is so customizable and able to compile large amounts of data with unique speed. The customer service is very good, as is their online support community. Overall, I am pleased with Looker, its analytical capabilities, its data management and all that it provides to our organization.

It imposes a learning curve at first, but this is easy to overcome. On the other hand, the processes can be prolonged depending on the traffic.

Looker has made it easier for us to collect, visualize, analyze and generally manage large amounts of data through a single platform. It has helped us find patterns and problems, as well as ways to solve them through the use of data. Their customer service is exceptional and they have a good support community that iterates often about the software and use cases.

Google Data Studio is frequently used by our marketing team for its great analytical capabilities. It allows us to very easily view marketing performance data, ads, google data analytics, among others. It is amazing how easy it is to learn and how easy it is to integrate with Google Ads and reporting tools. Installation is quick and setup is not complicated; I really like this Google tool.

It is free, but there is a possibility that you may have to pay for some connectors to make it work with other google and third party platforms.

Through use of this tool we have been able to create monitoring dashboards to closely track our marketing performance, e-commerce and audience interaction with our ads. It is quite easy to share the dashboards with colleagues and clients so they can access them from anywhere. In conclusion, it allows us to work our marketing smoothly, quickly and efficiently.

I was very helpful and ease of utilization

nothing, I think all is working good and working fine

It solve our hardware issues and maintenance of cloud in easy.

The ease of use, trust of google with one click expansion of computing resources and with assured stability and reliability in both terms of security and durability .

most of the services are not available on the students free version and are mostly paid, they should provide some more resources for students to get a good hands-on rather than keeping it in paid version

App deployments and getting good hands-on on virtual machines, accademic purposes and it also was used inn certain personal projects that were made . Hosting and reduced latency was the main upsides of using it.

Cloud SQL is a fully managed solution for deploying Sql instance with various machine types and disk sizes. It allows us to create direct sql users as well as edit configuration and create read replicas with ha over various zone

Not yet has a multi regional kind of deployment which is needed for a total regional failure.

It manages SQL deployment and allows various connectivity using sql proxy or direct username password. Since disk sizes are expandable it helps for scaling.

The scalability that Google Cloud SQL provides is simply the best. In my current project's work, we need to work on databases which are of Terra Bytes in size and thus scalability is major concern for us. With Google Cloud SQL we get this problem solved with lowest latency.

As of now, I personally don't find any downside of Cloud SQL. However, just one suggestion that i could make is that the documentation for Google Cloud SQL is bit complex and can be simplified for the first time users.

As I mentioned, the relational database that we work in our organization is of very large size and at the same time consists sensitive information in it. So, for our business requirements, scalability and security is major concern. Google Cloud completely solves these problems for us with highly scalable database in multiple regions along with Google's trusted managed security service.

Me gusta el hecho de que es fácil transferir mis archivos an otro dispositivo. Puede comprar almacenamiento por tan independent 0,99 centavos. ¡Utilizo el almacenamiento de archivos que guarda mis archivos durante task un año! Entonces, aunque cambié an Icloud por Apple, todavía tengo archivos importantes conectados a mi cuenta de Google que no tengo en iCloud.

Vaya! La aversión que me viene a la mente es la herramienta de Migración. La versión 4 del engine de migración M4ce de Google es muy difícil de configurar, una configuración tan compleja. Un buen alivio es la versión 5 de M4ce, que admite la migración desde vmware, cuya configuración es muy basic y he migrado cargas de trabajo fácilmente. Pero luchó mucho con la versión 4.

Facilidad de uso. Lo que más me gusta como administrador en comparación con otros proveedores de la nube, la especificación se puede personalizar y el nuevo tipo de CPU N2d que brinda un mejor rendimiento a un precio menor. Máquinas virtuales fáciles de implementar.

Bigquery is easy to set up and connect to data sources using Fivetran. Exploring data is intuitive, queries (SQL-like) are easy to learn and familiar. There are some innovative features, like automatically nesting tables (which is very interesting and not typical in a traditional database).

If data sources (from DBT, for example) update, there is no option to reload data in Bigquery without refreshing the whole page, which is heavy and takes a moment to load. Working in a schema with 18 tables, I quickly have a ton of tabs open, and the interface is not super for navigating so many tabs at the same time, at least not on a laptop screen.

We're using BigQuery as a warehouse for Fivetran. Data is imported and transformed along the way, so we are also using BigQuery to check and test those transforms. when satisfied, we move Data from BigQuery into a PostGRES database using Node.js and an SDK from NPM. From the standpoint of connecting from custom sources like Node, we find that BigQuery is, again, easy to use and work with.

Cloud SQL provides an infinite level of flexibility, you can customize your machine type. It is a highly scalable, durable & secured solution for Database as a service.

The Cost of Cloud SQL, especially for MS SQL Edition cost is too high compared to other cloud platforms. Apart from this, the service of cloud SQL is very good & user friendly to use.

Migration of On-premises databases to cloud SQL gives endless flexibility & there is no headache to manage the database platform, as well as the report genetration, which is quite easy. Cloud SQL can configure easily & the dashboard of the GCP console for cloud SQL is extremely user-friendly for monitoring purposes.

Its simplicity, not very complex like others, easy to understand, and quick to get up and running

Sometimes tend to lag a bit when joining more than 3 data sources.

Marketing Analytics and Reporting, Automated the report generation. It only took two weeks to create the dashboards while joining 10 data sources and very easy to use.

Easy Configuration. No need to worried about the backend procedure. Easy Scale-up & ability to handle flexible traffic is a great offering by cloud SQL. According to reports, cloud SQL is very much faster compared to other managed database platforms like Azure for SQL, Amazon RDS etc.

The Price is comparatively high for running a small instance of SQL, but performance-wise, it is undoubtedly a good solution.

Using Cloud SQL, the Database migration service is very easy & also configured the replication and backups to protect the data. I have noticed the data encryption model of cloud SQL also, which ensures the security parameters too. Now, I can easily focus on my application coding, with no need to take a headache of infrastructure.

Role management for the team is quite useful

As with every cloud provider service, you need a credit card to start using it

Storing all source code into one secure service.

It manages and automates the projects and other tasks which gives more time for coding. This directly leads to quick build of the apps. Also, it can be easily integrated to apps within Gcloud.

Everything's good. Would love it if the free trial period is increased to at least 40-45 days which helps understand the overall Cloud system and integration part.

It automates the projects and helps connect with other apps on the Google Cloud ecosystem. The instance can be easily saved and reused without any code changes. Also, the storage can be easily managed and optimised whenever needed.