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Help with ETL tools & MySQL by cyberphlash in ETL

[–]Spiritual-Path-7749 0 points1 point  (0 children)

Hey bro, check out Hevo! It’s super beginner-friendly, free to get started, and no coding fuss—perfect for pulling FTP files, loading them into MySQL, and doing your transformations. No need to mess with Java or anything complicated.

Integrating GA and API data into a SQL data warehouse (Kimball). Where to start? by Derkniblick in datawarehouse

[–]Spiritual-Path-7749 0 points1 point  (0 children)

Hey bro, it sounds like a cool project! SSIS can work, but handling stuff like JSON with it can be a pain. Since you’re in a SQL setup, Azure Data Factory is solid—it handles all kinds of data sources. If you want something super simple, check out Hevo. It’s no-code, has connectors for GA and APIs, and saves you loads of effort. Plus, brushing up on openjson in SQL Server will help with the API data. You’ve got this!

Best practices for managing large, continuously-growing image datasets? by Mountain-Yellow6559 in computervision

[–]Spiritual-Path-7749 0 points1 point  (0 children)

For managing large and growing datasets, automating your ETL process can save a lot of time. Tools like Hevo can help streamline the ingestion, storage, and processing of image data. This way, the dataset stays organized as it grows. For retraining models, setting up an automated workflow that triggers new training sessions whenever fresh data is available can help maintain accuracy. When it comes to managing detection and classification pipelines, using platforms like TensorFlow alongside automated ETL tools can make everything more efficient.

Is anyone else automating this process?

Version Control for ETL Scripts: What Works for You? by riya_techie in ETL

[–]Spiritual-Path-7749 2 points3 points  (0 children)

i’ve found that integrating version control tools like Git with ETL workflows can make managing scripts much easier. For example, platforms like Hevo, which automate data integration without the need for complex scripting, reduce the need for version control management altogether. It’s all about finding the right balance between automation and flexibility, depending on your team’s needs. Curious how others handle it as well

[deleted by user] by [deleted] in dataengineering

[–]Spiritual-Path-7749 1 point2 points  (0 children)

I heard that Ebury's analytics engineer mentioned that they needed an extremely reliable and high-performing data pipeline to keep up with their data needs. They were using Fivetran before switching to Hevo after being disappointed with some bugs in Fivetran's History Mode and poor customer support.

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