Dreamweaver is a web development tool built for designing pages with HTML and CSS using template pages, text editing, and a what you see is what you get editor.
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Brackets
Score 9.3 out of 10
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Brackets is a free and open source text editor developed at Adobe under the MIT license, featuring inline editing, live preview, and a wide range of extensions.
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Google BigQuery
Score 8.8 out of 10
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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)
Brackets can be considered as the barebones version of a more complex piece of software like Dreamweaver. We selected Brackets due to the simplicity of the UI and the ease of use. In our case we do not need all the additional tools and gadgets that other, more complex software …
This program is a must-have if you work in any HTML-based programs. It's convenient for HTML emails and tweaking code used in Wordpress. It's also greta for editing older PHP sites I manage for clients, I do not use it for new websites anymore as I feel other solutions are more suitable for my clients.
Brackets can handle most text editing problems, at least if you have a file small enough that it opens. But with so many free and open-source editors out there, it is easy to have multiple tools that fit specific niches. If you are editing HTML and CSS, get Brackets.
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).
The Live Preview feature is extremely helpful. You can make tweaks to your CSS and then see how it affects the pge you're coding.
The recently added file tree feature is really a time saver. You can move files with a drop and drag feature without ever minimizing the program.
One of my favorite features is the ability to update the core program with extensions. Some of the extensions are simple, like adding themes, while others are a offer a little more assistance like creating Lorem Ipsum text for you.
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.
Adobe Dreamweaver is very useable and easy to navigate. It's features are fantastic and documentation on how to use the software is very detailed. If you can't find how to do something, the help file is fantastic and works great!
As far as usability, text editors are about as simple as you can get in the GUI world. The little features that make Brackets unique are intuitive enough that you don't really need a manual to find them and come to rely on them. If anybody knows enough about coding and markup enough to be looking for different editors, they will be up to speed before the download finishes.
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 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.
Brackets has a very extensive support site. Everything is organized nicely for easy navigation. If you can't find an answer you can easily file an issue with them and they will be quick to respond. What's cool is you can also message them on Slack, if you request an invite first. Slack is a very popular program right now so it's great having that integration.
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.
Google Web Designer is what I used to use but Dreamweaver was better. Google did not offer the functionality I needed. Google was also messy and had limited design options. Google seems better for creating animated banners or animated photos, but not for designing a full website or designing HTML.
Brackets can be considered as the barebones version of a more complex piece of software like Dreamweaver. We selected Brackets due to the simplicity of the UI and the ease of use. In our case we do not need all the additional tools and gadgets that other, more complex software packages offer. We need something that's quick, easy, uncluttered and focuses specifically on our needs, which are seeing code and editing code. In this case no frills and complex UIs are required.
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.
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.
ROI is great. The version of the tool we are using is free so not a whole of lot “investment” went into it. And the work we can accomplish with it more than makes up for the “cost.”
The ease of use makes it simple for anyone new to the tool to start using it and contributing to the project.
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.
