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)
Notepad++
Score 9.0 out of 10
N/A
Notepad++ is a popular free and open source text editor available under the GPL license, featuring syntax highlighting and folding, auto-complete, multi-document management, and ac customizable GUI.
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).
well suited for 1) Coding and Development - Writing and editing code, Quick prototyping and testing of code snippets, Debugging and inspecting code using syntax highlighting and line numbering, 2) web development - Creating and editing HTML, CSS, JavaScript, and other web-related files .Managing and organizing web projects with multiple files and directories. Not suited for - 1) processing huge files 2) graphic designing 3) complex gui designs 3) Data Analysis and Manipulation - Editing and cleaning up text-based data files before importing them into analytical tools. Applying regular expressions to extract, transform, and manipulate data. 4) System Administration and IT - change system configuration file
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.
Notepad++ allows us to keep open files in tabs. Like in a web browser, these tabs let us access these files quickly and easily. Furthermore, even if we forget to save the files when closing the program or shutting down the PC, Notepad++ retains them in the open tabs when we reopen it.
Notepad++ supports many different file types. We usually save our files created in Notepad as normal text files, but sometimes as JSON, PHP, and HTML files.
Notepad++ is lightweight and requires little resources. Using it is snappy and responsive.
The developer of Notepad++ frequently updates the software with bug fixes, performance improvements and new features.
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.
Sometimes the number of options are overwhelming and require a quick search to figure out where to locate a particular function.
Some way to do a diff between files would be great. Still need to resort to another paid app for that - unless it is a buried function I don't know about or there's a plugin for it.
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.
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.
There are lot of features to talk about. Especially the usability is good. Everyone can easily to use and user-friendly. Can also update easily. Can also write and execute the programming languages like C, C++ etc. Encoding is also the major feature that helps me a lot and converter as well.
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.
I haven't needed to utilize any support related to Notepad++. I guess this is a good thing because I found it to be quite intuitive. There are almost infinite features you can tweak and plugins you can download but I haven't had to do that because Notepad++ is really good right out of the box.
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.
Notepad for Windows, Microsoft Word...LibreOffice Writer....I have used all of these for code writing and editing. Once again I like the universal feel of Notepad++. Basic Notepad, is just that, basic...and kind of clunky for what it is. This is a cool that I have installed on all my computers and also keep it on a thumb drive if I need it elsewhere.
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.
