Description de Google Cloud BigQuery
BigQuery est un data warehouse multicloud sans serveur qui vous permet de travailler plus facilement avec tous types de données pour vous aider à obtenir rapidement de précieuses informations commerciales. Conçu au cœur du cloud de données de Google, BigQuery vous permet de simplifier l'intégration des données, de faire évoluer votre analytique de manière rentable et sécurisée, de partager des expériences de données riches avec une BI (Business Intelligence) intégrée et de former et de déployer des modèles de ML (Machine Learning) avec une interface SQL conviviale pour centrer les opérations de votre entreprise sur les données.
Qui utilise Google Cloud BigQuery ?
BigQuery aide les entreprises de toutes tailles à décomposer les silos de données et à tirer le meilleur parti de leurs données.
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Google Cloud BigQuery
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Commentaires : I use this tool daily and it meets my expectations, easy to create jobs in the form of scheduled queries, easy import of data from Google Sheets, integration with Google GAS and many other advantages that I have discovered
importing information from Google Sheets seems like a super advantage to me, as does the ability to execute large queries without affecting performance.
I have no complaints about the tool so far
Alternatives envisagées précédemment :
Great serverless cloud data warehouse
Commentaires : We used BigQuery to analyze firebase events data from our mobile apps. Considering the sheer volume of this dataset, querying has been mostly very fast and reliable, albeit at a high cost.
I like the serverless nature of BigQuery. It takes away most of the maintenance costs involved in maintaining and fine-tuning a data warehouse.
I didn't really like the on-demand pricing of BigQuery. Monthly costs tend to blow up excessively. I think they have a different pricing option now to resolve this though.
Get started with BigQuery, A powerful tool for analysing Big data
Our salesforce campaigns relies heavily on data warehouse, which is the backbone of everything we do. This data set contains both row data sets and BigQuery is used to aggregate this sets by running schedule queries on it.
This platform requires strong SQL skills. Huge dependency on tech team to fix queries sometime.
Great serverless tool
I use this tool in my first professionnal experience as Data Engineer and I still use it today. I used BigQuery for Datawarehouse : make data available for everyone (data analyst, developer...). Today, I use it too for the logs of an ELT pipeline, it's still very simple to use this tool.
It's necessary to understand how costing works in detail, especially if you have a lot of data.
"Google Cloud BigQuery: The Ultimate Solution for Big Data Management and Analysis"
Commentaires : My experience using Google Cloud BigQuery has been very good. It is a strong software for data warehousing and analytics, capable of handling large datasets efficiently. Navigation and execution of queries are fast and user-friendly. The pay-per-use pricing model is cost-effective and it offers robust features such as high performance, flexibility, and security. It is an ideal choice for companies that want to extract valuable insights from big data.
Google Cloud BigQuery is a powerful and user-friendly software for data warehousing and analytics. It can easily handle extremely large datasets, making it perfect for businesses that process and analyze massive amounts of data. The queries are executed quickly, even on large datasets, allowing for efficient data analysis and insights. The user interface is intuitive and easy to navigate, making it accessible for users of all skill levels. It integrates seamlessly with other Google Cloud products, such as Google Analytics and Google Cloud Storage, which allows for a streamlined workflow. The pricing is pay-per-use and the cost is generally lower for larger amounts of data, which makes it cost-effective. Additionally, it offers high performance, flexibility, and strong security features.
Google Cloud BigQuery is a great tool for data warehousing and analytics. One thing to keep in mind is that it can have a steep learning curve for those who are not familiar with SQL and data warehousing concepts. Additionally, it may not be as customizable as some other data warehousing and analytics tools. But overall, it offers a wide range of functionalities and a user-friendly interface, making it a great option for many use cases. I've found it to be a reliable and efficient tool for processing and analyzing large datasets.