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Excellent tool for data transformation
What do you like best about the product?
It has helped us transform our data and structure it better and its easy use
What do you dislike about the product?
It should provide a tool to better enable model documentation.
What problems is the product solving and how is that benefiting you?
We can have the data structured through code; This helps us when migrating data to any type of DWH.
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Making data transformations easier
What do you like best about the product?
Its simplicity and focus on transforming data in a reproducible and maintainable way.
What do you dislike about the product?
Sometimes,its learing curve can be steep for beginners and managing comples transformation might require advanced knowledge.
What problems is the product solving and how is that benefiting you?
dbt simplifies data transformation making analytics pipelines easier to manage and more reliable,which benefifits users by stramling workflows and improving efficiency.
A great environment and a powerful daily tool for Data Analysts and Engineers.
What do you like best about the product?
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.
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.
What do you dislike about the product?
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.
The titles don't seem intuitive and the content could be more streamlined for finding faults.
What problems is the product solving and how is that benefiting you?
Easy onboarding - streamlined development - the guided point-and-click adventure for github saves a ton of time and is probably the best in class solution I have seen for managing state. Please dont ever change this.
dbt data modeling and test building is a fun experience on dbt cloud, my day to day work is fun because of dbt.
Testing is super easy for pro-active data quality checks.
I wish there was more visible ways to incorporate REACTIVE testing, like Metaplane's monitors, into dbt.
DBT support was a bit slow here in Africa when the Github outage took place last year - some frustration around how slow responses were, how unclear processing was but I have personally learnt how to navigate these issues outside of dbt env.
dbt data modeling and test building is a fun experience on dbt cloud, my day to day work is fun because of dbt.
Testing is super easy for pro-active data quality checks.
I wish there was more visible ways to incorporate REACTIVE testing, like Metaplane's monitors, into dbt.
DBT support was a bit slow here in Africa when the Github outage took place last year - some frustration around how slow responses were, how unclear processing was but I have personally learnt how to navigate these issues outside of dbt env.
Our analytics are more reliable and efficient
What do you like best about the product?
Im thrilled to explore how dbt revolutionizes our work by delving deeply into the data world. Its a total gamechanger 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.
What do you dislike about the product?
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.
What problems is the product solving and how is that benefiting you?
In my role as a data management specialist, I have seen how dbt changed how we change data. It keeps changes same under control and tested well guaranteeing how exact our analyzing is. The automatic things of dbt have helped us work better freeing our team for strategic things not manual data work. This made us more quick and able to answer with data that helps our group make choices based on data.
Using dbt has improved accuracy and collaboration in our data projects
What do you like best about the product?
In my role I absolutely love using dbt - its the ultimate tool for transforming data with ease. It effortlessly integrates into our current systems making our analytics work a breeze. Were all in on dbt because it excels at data transformation and organization boosting our efficiency and collaborative efforts tremendously.
What do you dislike about the product?
It would be fantastic if dbt could enhance it's toolkit for visual data modeling. At present its 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.
What problems is the product solving and how is that benefiting you?
As data enthusiasts we consider dbt our everyday superpower dramatically enhancing our data analysis while effortlessly managing complex data changes. Its our goto tool smoothing our data work and ensuring our insights are as sharp as a tack allowing us to make informed decisions to propel our business forward.
Good tranformation tool for data engineers : Complete SQL Magic.
What do you like best about the product?
DBT has been game changer in the realm of data analaytics for me.
Its One of standout feature is abilty to transform data in warehouse itself it makes it lightning fast
The powerfult modular sql based approach to define transformation makes it fall in love for data engineers.
Its automatic document generation feature is simply outstanding.
Its SQL based moduler approach makes it easy for implementation.
Its One of standout feature is abilty to transform data in warehouse itself it makes it lightning fast
The powerfult modular sql based approach to define transformation makes it fall in love for data engineers.
Its automatic document generation feature is simply outstanding.
Its SQL based moduler approach makes it easy for implementation.
What do you dislike about the product?
If someone is not well-versed in SQL it will be dificult to implement it initially.
The main feature it doesnt have is inbuilt scheduler.
The scheduler will make it complete transformation tool for data engineers.
The main feature it doesnt have is inbuilt scheduler.
The scheduler will make it complete transformation tool for data engineers.
What problems is the product solving and how is that benefiting you?
Ability to create moduler, version control models ensures my transformation code is well maintanable and scalable.
Its version control feature makes it very easy for developers to collabrate.
Its feature of auto generating insights/ documents makes it outstand.
Its version control feature makes it very easy for developers to collabrate.
Its feature of auto generating insights/ documents makes it outstand.
so usefull
What do you like best about the product?
we can made maintainalble and scalable data infrastructure, this make user easy for working with data, transforming data become easy, that is why we use it in our projects also provides some standardies features
What do you dislike about the product?
we can not able to load the data from source , we can only able to use data present in dataware houses, new users may face difficulties while learning, support also not that good from community
What problems is the product solving and how is that benefiting you?
It provides standardize transformation process that help in less error, version control is also a good feature
Transforming data with dbt
What do you like best about the product?
dbt is an efficient solution that is capable of transforming raw data into important insights. I've been utilizing it for data transformation and it integrates easily with most of the elt tools. It has tons of features that enhances the development experience.
What do you dislike about the product?
I've experienced issues when it comes to managing dependencies between models also realtime work isn't possible which is much needed.
What problems is the product solving and how is that benefiting you?
dbt helps us in data quality checks and preparation before making it available for everyone. It ensures data accuracy and maintains regularity of the transformed data through automation testing.
It's like seeing an old friend that you really liked but haven't seen for a while.
What do you like best about the product?
At it's 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.
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.
What do you dislike about the product?
dbt requires a mindset change. You have to buy into how they think about modeling. It's opinionated. dbt is method-agnostic (data vallt, mesh, kimball). But structure matters and you need to spend some time to understand dbt's mindset around stricture.
What problems is the product solving and how is that benefiting you?
Let me tell you about the state of our data. At the time, we didn’t know. That was the issue. It was a black box. Our data model was opaque with logic scattered all across the data stack. As we pick around the edges a picture starts to form. Imagine a dense, thorny briar patch, each thicket representing a tangled mess of information. That's how I see it—unruly, interlacing, and chaotic. Management has a different take. They call it "spaghetti," a swirling plate of tangled noodles. It’s actually not far from the truth. Each report fed directly from the source, the logic for each was self-contained and sometimes borrowed.
Transformation step of ETL/ELT pipelines made easy
What do you like best about the product?
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.
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.
What do you dislike about the product?
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.
What problems is the product solving and how is that benefiting you?
Previous functions that were performed as adhoc scripts in python were made easy, running at a fraction of the time due to being rewritten in a significantly more efficient manner. Various functions across the business that require some sort of data transformation or manipulation, often previously manually were centralised all on one platform being DBT. Workflows and pipelines flowed more logically, and were scheduled and automated easily. Reports that are used daily by the business run quickly and very reliably. Tests and checks to validate data that was also previously done manually are all now integrated into the pipelines and automated, making multiple teams lives easier.
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