Google's BigQuery is part of the Google Cloud Platform, a database-as-a-service (DBaaS) supporting the querying and rapid analysis of enterprise data.
$6.25
per TiB (after the 1st 1 TiB per month, which is free)
Visual Studio
Score 8.8 out of 10
N/A
Visual Studio (now in the 2022 edition) is a 64-bit IDE that makes it easier to work with bigger projects and complex workloads, boasting a fluid and responsive experience for users. The IDE features IntelliCode, its automatic code completion tools that understand code context and that can complete up to a whole line at once to drive accurate and confident coding.
In my opinion, Google BigQuery is custom made to be the best data lake system that is easy to use, scalas to fit any business size, has inbuilt security, as well as tools for data integrity. Although a few other tools have some of the same functionality, Google BigQuery is the …
Event-based data can be captured seamlessly from our data layers (and exported to Google BigQuery). When events like page-views, clicks, add-to-cart are tracked, Google BigQuery can help efficiently with running queries to observe patterns in user behaviour. That intermediate step of trying to "untangle" event data is resolved by Google BigQuery. A scenario where it could possibly be less appropriate is when analysing "granular" details (like small changes to a database happening very frequently).
When working with base C# code for desktop and web projects, then Microsoft Visual Studio is ideal as it provides the libraries and interfaces needed to quickly create, test and deploy solutions. It is when slightly more complex scenarios are required that issues can arise. The built-in integration for things like PowerBI Paginated Reports and dashboards is far from ideal.
GSheet data can be linked to a BigQuery table and the data in that sheet is ingested in realtime into BigQuery. It's a live 'sync' which means it supports insertions, deletions, and alterations. The only limitation here is the schema'; this remains static once the table is created.
Seamless integration with other GCP products.
A simple pipeline might look like this:-
GForms -> GSheets -> BigQuery -> Looker
It all links up really well and with ease.
One instance holds many projects.
Separating data into datamarts or datameshes is really easy in BigQuery, since one BigQuery instance can hold multiple projects; which are isolated collections of datasets.
Please expand the availability of documentation, tutorials, and community forums to provide developers with comprehensive support and guidance on using Google BigQuery effectively for their projects.
If possible, simplify the pricing model and provide clearer cost breakdowns to help users understand and plan for expenses when using Google BigQuery. Also, some cost reduction is welcome.
It still misses the process of importing data into Google BigQuery. Probably, by improving compatibility with different data formats and sources and reducing the complexity of data ingestion workflows, it can be made to work.
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.
VS is the best and is required for building Microsoft applications. The quality and usefulness of the product far out-weight the licensing costs associated with it.
I think overall it is easy to use. I haven't done anything from the development side but an more of an end user of reporting tables built in Google BigQuery. I connect data visualization tools like Tableau or Power BI to the BigQuery reporting tables to analyze trends and create complex dashboards.
I love the overall usability of Microsoft Visual Studio. I’ve been using this IDE for more than 20 years, and I’ve seen it evolve by leaps and bounds. Today, with AI and code-suggestion/completion features, developers no longer need to remember countless libraries, methods, or language syntax, or invest a huge amount of programming effort to complete a project. It truly offers everything a developer needs to program, debug, test, and deploy in a single IDE.
I have never had any significant issues with Google Big Query. It always seems to be up and running properly when I need it. I cannot recall any times where I received any kind of application errors or unplanned outages. If there were any they were resolved quickly by my IT team so I didn't notice them.
I think Google Big Query's performance is in the acceptable range. Sometimes larger datasets are somewhat sluggish to load but for most of our applications it performs at a reasonable speed. We do have some reports that include a lot of complex calculations and others that run on granular store level data that so sometimes take a bit longer to load which can be frustrating.
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.
There are many resources available supporting Visual Studio IDE. Microsoft whitepapers, forum posts, and online Visual Studio documentation. There are countless demonstration videos available, as well. If users are having issues, they can call Microsoft Support, but depending on the company's agreement with Microsoft, the number of included support calls will vary from organization to organization. I've found that Microsoft support calls can be hit or miss depending on who you get, but they can usually get you with the right support person for your issue.
IT is very complicated to understand all the functions that the environment has if you are not familiar with this type of development environments. It is important to select a good in-person training to achieve to understand all the possibilities and the capacity of the application. In this case, you will be able to develop a lot type of different applications.
If you are not accustomed to develop in this type of development environments it would be complicated to follow all the parts of the course because if the course does not include a great tour with all the concepts to develop you will not have the option to understand all the functions.
PowerBI can connect to GA4 for example but the data processing is more complicated and it takes longer to create dashboards. Azure is great once the data import has been configured but it's not an easy task for small businesses as it is with BigQuery.
I personally feel Visual Studio IDE has [a] better interface and [is more] user friendly than other IDEs. It has better code maintainability and intellisense. Its inbuilt team foundation server help coders to check on their code then and go. Better nugget package management, quality testing and gives features to extract TRX file as result of testing which includes all the summary of each test case.
We have continued to expand out use of Google Big Query over the years. I'd say its flexibility and scalability is actually quite good. It also integrates well with other tools like Tableau and Power BI. It has served the needs of multiple data sources across multiple departments within my company.
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.
Previously, running complex queries on our on-premise data warehouse could take hours. Google BigQuery processes the same queries in minutes. We estimate it saves our team at least 25% of their time.
We can target our marketing campaigns very easily and understand our customer behaviour. It lets us personalize marketing campaigns and product recommendations and experience at least a 20% improvement in overall campaign performance.
Now, we only pay for the resources we use. Saved $1 million annually on data infrastructure and data storage costs compared to our previous solution.
Using the integration between Visual Studio and our source control service, the cost of re-work and losing code is drastically reduced.
Paid versions of Visual Studio enable developers to be so much more productive than hacked-together open source solutions that it's hard to imagine developing in Windows without it.
When combined with support subscriptions and the vast array of free online help options available, Visual Studio saves our developers time by keeping them coding and testing, not wasting their time trying to guess their way out of problems or spend endless hours online hoping to find answers.
