dbt is an SQL development environment, developed by Fishtown Analytics, now known as dbt Labs. The vendor states that with dbt, analysts take ownership of the entire analytics engineering workflow, from writing data transformation code to deployment and documentation. dbt Core is distributed under the Apache 2.0 license, and paid Teams and Enterprise editions are available.
$0
per month per seat
Looker
Score 8.3 out of 10
N/A
Looker is a BI application with an analytics-oriented application server that sits on top of relational data stores. It includes an end-user interface for exploring data, a reusable development paradigm for data discovery, and an API for supporting data in other systems.
Airflow can accomplish the same work as dbt (data build tool), however, dbt's (data build tool) development workflow and UI can open up data transformation and modeling work to non-data engineering teams. Looker might also be able to define data models via LookML with a …
dbt is very flexible and can fit into most data pipelines. This is a pro for most organizations that aren't fully bought into one platform (Google Cloud, etc.)
If you company is using Google suite products, Looker is a no-brainer. Tableau is probably the most flexibly but as a result it has the least governance capabilities. Power BI is kind of old-school in terms of how it feels to use it. I think in general, Looker brings a lot of …
Looker is more mailable; it allows more dynamic visualisations, filters, drilldowns etc. It's sharing capabilities are also more streamlined than AWS Quicksight. However in contrast to this AWS Quicksight can leverage AWS IAM roles and policies which can be quite scalable. …
The prerequisite is that you have a supported database/data warehouse and have already found a way to ingest your raw data. Then dbt is very well suited to manage your transformation logic if the people using it are familiar with SQL. If you want to benefit from bringing engineering practices to data, dbt is a great fit. It can bring CI/CD practices, version control, automated testing, documentation generation, etc. It is not so well suited if the people managing the transformation logic do not like to code (in SQL) but prefer graphical user interfaces.
When data drives potential for new orders, Looker earns its place in our tech stack. If, on the other hand, we are hoping for pipeline generation, Looker is useful if you are willing to repeatedly go check customer utilizations .... it is not appropriate if you are hoping to automate data analysis for this purpose.
Show visited pages - sessions, pageviews - which programs are viewed the most.
Displays session source/medium views to see where users are coming from.
It shows the video titles, URLs, and event counts so we can monitor the performance of our videos.
It gives a graphic face to the numbers, such as using bar charts, pie graphs, and other charts to show user trends or which channels are driving engagement.
Our clients like to see the top pages visited for a month.
I like the drop-and-drag approach, and building charts is a little easier than it was before.
I give it this rating because it deems as effective, I am able to complete majority of my tasks using this app. It is very helpful when analyzing the data provided and shown in the app and it's just overall a great app for Operational use, despite the small hiccups it has (live data).
dbt is very easy to use. Basically if you can write SQL, you will be able to use dbt to get what you need done. Of course more advanced users with more technical skills can do more things.
Looker is relatively easy to use, even as it is set up. The customers for the front-end only have issues with the initial setup for looker ml creations. Other "looks" are relatively easy to set up, depending on the ETL and the data which is coming into Looker on a regular basis.
Somehow resources heavy, both on server and client. I recommned at least 50Mbs data rate and high performance desktop comouter to be abke to run comolex tasks and configure larger amount of data. On the other hand, the client does not need to worry when viewing, the performance is usually ok
Never had to work with support for issues. Any questions we had, they would respond promptly and clearly. The one-time setup was easy, by reading documentation. If the feature is not supported, they will add a feature request. In this case, LDAP support was requested over OKTA. They are looking into it.
I actually don't know what the alternative to dbt is. I'm sure one must exist other than more 'roll your own' options like Apache Airflow, say, bu tin terms of super easy managed/cloud data transforms, dbt really does seem to be THE tool to use. It's $50/month per dev, BUT there's a FREE version for 1 dev seat with no read-only access for anyone else, so you can always start with that and then buy yourself a seat later.
Looker Studio, you can easily report on data from various sources without programming. Looker Studio is available at no charge for creators and report viewers. Enterprise customers who upgrade to Looker Studio Pro will receive support and expanded administrative features, including team content management. So it's good.
Looker has a poignant impact on our business's ROI objectives. As an advertising exchange we have specific goals for daily requests and fill, and having premade Looks to monitor this is an integral piece of our operational capability
To facilitate an efficient monthly billing cycle in our organization, Looker is essential to track estimated revenue and impression delivery by publisher. Without the Looks we have set up, we would spend considerably more time and effort segmenting revenue by vertical.
Looker's unique value proposition is making analytical tools more digestible to people without conventional analytical experience. Other competing tools like Tableau require considerably more training and context to successfully use, and the ability to easily plot different visualizations is one of its greatest selling points.