Likelihood to Recommend Google BigQuery really shines in scenarios requiring real-time analytics on large data streams and predictive analytics with its machine learning integration. Teams have been using it extensively all over. However, it may not be the best fit for organizations dealing with small datasets because of the higher costs. And also, it might not be the best fit for highly complex data transformations, where simpler or more specialized solutions could be more appropriate.
Read full review In operations we use the tool for many different topics, from factory quality systems to high level reviews. We have created kind of an internal "App Store" based on Power BI where you have a lot of different dashboards for different solutions (cost, cash, health and safety, sales, factories, distribution centers...) and you as an user just need to get in that "App Store" and enter in whatever tool can be useful for you. It is open to all the operations employees and can use on demand. Also it has raised the imagination of our colleagues, as they are not only working by themselves creating new reports, but also raising fantastic ideas that can be extended for the usage of all the community.
Read full review Pros Its serverless architecture and underlying Dremel technology are incredibly fast even on complex datasets. I can get answers to my questions almost instantly, without waiting hours for traditional data warehouses to churn through the data. Previously, our data was scattered across various databases and spreadsheets and getting a holistic view was pretty difficult. Google BigQuery acts as a central repository and consolidates everything in one place to join data sets and find hidden patterns. Running reports on our old systems used to take forever. Google BigQuery's crazy fast query speed lets us get insights from massive datasets in seconds. Read full review Quickly filter and view granular data sets with easily configurable reporting figures. The ability to quickly switch between tabs allows for historical data comparisons and progress tracking. It's helpful to dive into the data and break it down from high levels to small. Achieve actionable insights faster by using real-time data. It's incredible to have online access to reports. Read full review Cons It is challenging to predict costs due to BigQuery's pay-per-query pricing model. User-friendly cost estimation tools, along with improved budget alerting features, could help users better manage and predict expenses. The BigQuery interface is less intuitive. A more user-friendly interface, enhanced documentation, and built-in tutorial systems could make BigQuery more accessible to a broader audience. Read full review The desktop app is great but needs a lot of performance improvements No MacOS Version for the Desktop app, this is a big limitation for business since executives prefer Macs Premium Cloud Version of Power BI is awfully expensive On-Premise Version of the Power BI Reports Server is bundled only with SQL Server Enterprise License and cannot be purchased separately and requires Software Assurance Subscription On-Premise Power BI Report Server doesn't support ADFS, AzureAD or any Claims-Based authentication platform, a sad disadvantage for enterprises Read full review Likelihood to Renew We have to use this product as its a 3rd party supplier choice to utilise this product for their data side backend so will not be likely we will move away from this product in the future unless the 3rd party supplier decides to change data vendors.
Read full review I find it helpful and easy to use
Read full review Usability web UI is easy and convenient. Many RDBMS clients such as aqua data studio, Dbeaver data grid, and others connect. Range of well-documented APIs available. The range of features keeps expanding, increasing similar features to traditional RDBMS such as Oracle and DB2
Read full review At this point, I think we all know who has taken the lead in the business intelligence and analytics market worldwide. With fresh new updates every other day on top of an already robustly built product with all features that one can dream of is a no brainer, I feel. Microsoft will invariably be synonymous with quality and professionalism.
Read full review Support Rating BigQuery can be difficult to support because it is so solid as a product. Many of the issues you will see are related to your own data sets, however you may see issues importing data and managing jobs. If this occurs, it can be a challenge to get to speak to the correct person who can help you.
Read full review I can't really speak to the support overall, [but] I will say that in the almost three years I have used the system, I have only needed to contact their support team once. I think the team was helpful, but it did take some time for us to resolve the issues/ request that they had. I guess the good news is that the system is pretty stable, and I personally have rarely needed to contact their technical support team.
Greg Watkins Senior Customer Success Manager (Strategic Accounts)
Read full review Alternatives Considered I have used
Snowflake and
DataGrip for data retrieval as well as Google BigQuery and can say that all these tools compete for head to head. It is very difficult to say which is better than the other but some features provided by Google BigQuery give it an edge over the others. For example, the reliability of Google is unmatchable by others. One thing that I really like is the ability to integrate Data Studio so easily with Google BigQuery.
Read full review [Microsoft] Power BI is practical and effective, like a hammer for a nail, it is easy to use and produces very quickly the results that in most cases are urgently required by clients (nice reports to share on the web). To start using [Microsoft] Power BI you need a business email address, with that you create an account in Power BI Service and in less than 1 hour you will have installed Power BI Desktop, a report will have been created and it will have been published on the web .
Dustin Ghia Lead Consultant - Solutions Architect - Software Engineer
Read full review Contract Terms and Pricing Model None so far. Very satisfied with the transparency on contract terms and pricing model.
Read full review Professional Services Google Support has kindly provide individual support and consultants to assist with the integration work. In the circumstance where the consultants are not present to support with the work, Google Support Helpline will always be available to answer to the queries without having to wait for more than 3 days.
Read full review Return on Investment Pricing has been very reasonable for us. The first 10 GB of storage is free each month and costs start at 2 cents per GB per month after that. For example, if you store 1 terabyte (TB) for a month, then the cost would be $20. Streaming data inserts start at 1 cent per 200 megabytes (MBs). The first 1 TB of queries is free, with additional analysis at $5 per TB thereafter. Meta data operations are free. Big Query helps reduce the bar for data analytics, ML and AI. BQ takes care of mundane tasks and streamlines for easy data processing, consumption. The most impressive thing is the ML and AI integration as SQL functions, so the need for moving data around is minimized. The visuals of ML models is very helpful to fine tune training, model building and prediction, etc. Read full review It helps us track and achieve company goals. It shows us [our] performance in areas we could not previously track and allows us to see and work on how to improve their performance. Quick easy access for executives to use in helping teams and addressing issues. Read full review ScreenShots Google BigQuery Screenshots Microsoft Power BI Screenshots