Using SQL queries, it is easy platform to transform the data. Review collected by and hosted on G2.com.

For legacy system its is not useful for tranformation Review collected by and hosted on G2.com.

DBT is user friendly and helps keep our data reliable, updated and secure Review collected by and hosted on G2.com.

Upgrading from core is really expensive without there being any significant differences besides number of users Review collected by and hosted on G2.com.

dbt is the best Transformation tool out there in the industry and I love dbt for its testing capabilities and modeling and semantic layer. Ease of use and how easily you could maintain

It is easy to integrate with other tools like integration. Review collected by and hosted on G2.com.

dbt should add more AI capabilities faster Review collected by and hosted on G2.com.

At its core, DBT aligns three technologies to deliver knowledge better: SQL, YAML, & Jinja. You can do a lot with just SQL and YAML. Adding in Jinja makes SQL feel a lot more like traditional development. I kinda missed that. It's like seeing an old friend that you really liked but haven't seen for a while.

dbt is magic for transforming and modeling data. It's a platform that allows us to wrangle, shape, and organize the data to model the business. With the help of DBT, we can implement the principle of separation of concerns to organize and manage our transformations.

One of the key tools DBT offers is Directed Acyclic Graphs (DAGs), maps that illustrate the path our data takes from source to the final destination. These maps illustrate the data transformation arc. We start with the source data, which is often messy and unrefined. We use DBT to perform a series of transformations, taking the data on a journey from a multiverse of chaos to a world of understanding. We clean the data, apply business rules, and ensure the data conforms to our business dimensional models. These models or core business logic serve as the foundation for reporting.

As we progress along the transformation arc, our data starts to take shape. We can build data marts for specific business areas or functions. These data marts are built with our business dimensional models, ensuring that the data is structured in a way that supports efficient analysis and reporting.

Reporting on top of our business dimensional models. With the data now organized and modeled in a meaningful way, we can unlock valuable insights and empower decision-makers with actionable information . . . at scale. We can slice and dice the data, apply filters, and drill down into specific dimensions to understand trends, patterns, and outliers. The reports we develop are consistent because they come from a single source of truth, the business dimensional model. Review collected by and hosted on G2.com.

dbt requires a mindset change. You have to buy into how they think about modeling. It's opinionated. dbt is method-agnostic (data vault, mesh, kimball). But structure matters and you need to spend some time to understand dbt's mindset around structure. Review collected by and hosted on G2.com.

Its easy to use even for newcomers and dbt also uses sql that is the most democratic language for data manipulation. From the start is very quick to integrate with your data stack in just a few clicks. I use dbt for for data transformation and data modelling every day and its many features like data lineage, version control, ci and slim ci, testes, documentation, model contracts make it easy to apply DataOps in you project Review collected by and hosted on G2.com.

Its feature to model in python depends on the data plataform you are using. Its IDE still misses some of the functionalities that other IDE have that make development more easy, but new features are rolling out every new release of dbt cloud Review collected by and hosted on G2.com.

Easy to write transformation in SQL language augmented by Jinja templating techniques. Support of Python models is powerful. Good library of Open source Macros makes life easy for Analytics engineers. Write test cases to test model results. Powerful documentation capabilities. Works very well with Snowflake. Review collected by and hosted on G2.com.

To use DBT effectively, one needs to learn how to modularize SQL using CTEs. Bit advanced knowledge in SQL really helps. Review collected by and hosted on G2.com.

dbt Cloud - I recommend it to every org to get Data Analysts & Analytics engineers up and running quickly without having difficulty setting up during the onboarding.

It's easier to adopt new teammates when they get to dive into the models immediately and add value sooner and solidify their grasp early. Review collected by and hosted on G2.com.

I dislike navigating the logs in the Job Runs tab.

The titles don't seem intuitive and the content could be more streamlined for finding faults. Review collected by and hosted on G2.com.

I'm thrilled to explore how dbt revolutionizes our work by delving deeply into the data world. It's a total game-changer providing remarkable simplicity in formulating and utilizing data code within our warehouse. When it comes to version control, dbt streamlines the entire process ensuring a smooth experience and maintaining crucial data models for analysis. Review collected by and hosted on G2.com.

It would be good if dbt made it easier for new folks. It can do a lot with data stuff, but figuring how to set it up and use all its cool things can feel hard at first. More intuitive guides or a simpler way to learn the basics would make it nicer for people just starting with data changes. Review collected by and hosted on G2.com.

In my role I absolutely love using dbt - it's the ultimate tool for transforming data with ease. It effortlessly integrates into our current systems making our analytics work a breeze. We're all in on dbt because it excels at data transformation and organization boosting our efficiency and collaborative efforts tremendously. Review collected by and hosted on G2.com.

It would be fantastic if dbt could enhance its toolkit for visual data modeling. At present, it's heavily focused on coding but integrating a more visual approach to working with data would undoubtedly elevate its utility, especially for individuals who gravitate towards graphical methods for data analysis. Review collected by and hosted on G2.com.

Using DBT Cloud, the IDE is very intuitive, project lineage diagrams are very helpful. The general use of Jinja referencing and CTE's within the models made the flows very easy to follow, even with very large complex datasets that require lots of transformation. DBT integrates very easily with multiple ELT tools that we have used. Have all transformations in SQL form just makes everything easier. Being scheduled easily, we run multiple DBT pipelines daily. Review collected by and hosted on G2.com.

With DBT Cloud you can only have one project per user without paying for a payed tier of the product, which is fair but makes for harder collaboration at this level. Review collected by and hosted on G2.com.