Clear Analytics vs. dbt

Clear Analytics has almost all the features which are mostly required by the organizations for their data analytics and transformation activities. Clear Analytics is built on the support of a parallel query engine which makes it handle large volume requests and also provides optimized results. However, every solution has some limitations, Clear Analytics lacks advanced features such as Predictive Analytics which is a very demanding feature in the market as most organizations are adopting AI/ML automation for their businesses. Also, it needs to add a lot of advanced visualizations so that the user has the choice of selection. Overall a good solution to be recommended.

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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.

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• Quick management of the data through Excel thanks to the tools Clear Analytics provides such as filtering different information for an easier view.
• Ability to add new KPIs to measure different areas of our business.
• Drag and drop tool which makes an easier usage of Excel.
• Cost-effective. I find Clear Analytics to be affordable considering the number of features added and the unlimited sharing and editing it provides.

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• dbt supports version control through GIT, this allows teams to collaborate and track the data transformation logic.
• dbt allows us to build data models which helps to break complex transformation logic into simple and smaller logic.
• dbt is completely based on SQL which allows data analyst and data engineers to build the transformation logic.
• dbt can be easily integrated with snowflake.

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• For Charts and Graphs , getting the Power Point Deck would be helpful. As of now we use the data from Excel Reports

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• Field-level lineage (currently at table level)
• Documentation inheritance - if a field is documented the downstream field of the same name could inherit the doc info
• Adding python model support (in beta now)

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I have really enjoyed working with Clear Analytics. This platform has contributed to increased production and reliable data control processes. It has flexible user interface that can be operated by any organization member. Reports are shared on simple and transparent way in the dashboard for easy access. Data analytics from all departments have created manageable working environment that have increased production.

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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.

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I have had multiple scenarios where I had to reach out to the support team of Clear Analytics, be it access-related, general queries, during initial implementation, etc. My overall experience has always been good. I got the needed support every time without any delay. I can definitely recommend Clear Analytics simply on the basis of its excellent support team.

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There are other great tools that are out there but Clear Analytics is reasonable for our business and provides a lot of features that we specifically needed

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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.

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• Super useful to get started immediately
• Didn't have to rely on migrating data
• Easy to add members
• Easy to learn and build charts

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• Simplified our BI layer for faster load times
• Increased the quality of data reaching our end users
• Makes complex transformations manageable

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A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info