Alternatives
Products that do what DataScreenIQ does
Stop Bad Data Before It Breaks Your Pipeline
- 1IB
Every data pipeline job I had to tackle required quite a few components to set up: - One tool to ingest data - Another one to transform it - If you wanted to run Python, set up an orchestrator - If you need to check the data, a data quality tool Let alone this being hard to set up and taking time, it is also pretty high-maintenance. I had to do a lot of infra work, and while this being billable hours for me I didn’t enjoy the work at all. For some parts of it, there were nice solutions like dbt, but in the end for an end-to-end workflow, it didn’t work. That’s why I decided to build an…
2024 · github.com
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- 3DA
2022 · github.com
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- 10DP
2022 · mage.ai
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- 14WO
WhatTheDuck is an in-browser sql tool to analyze csv files that uses duckdb-wasm under the hood. Please provide feedback/issues/pull requests.
2024 · github.com
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- 20AI
2022 · github.com
- 21PP
I’ve found that I don’t have any context about the data in my pipelines only know if the pipeline is successful or not. So I built panda-patrol which allows you to monitor each node in your DAG, use AI to generate data tests for your data, store data profiles, and more. All with this comes with dashboards and alerts. You can easily drop it into your Python-based data pipeline (i.e. Airflow, Dagster, Prefect, etc.) and just run your pipelines are you normally would — but with monitoring and more context. Hope its valuable to some people
2023 · panda-patrol.vercel.app
- 22SR
Hi HN, we are so excited to be sharing this on here! Siege is the fastest and the simplest way to spin up a real-time data pipeline, which you can then query, filter, visualize with just clicks of some buttons, no need for any instrumentation or code changes. It works by capturing JSON data from your API transactions, transforming this data, and then storing it in an optimized columnar database for easy and fast querying. I've put together a 3-minute demo on Loom just now, showing you how I made real time dashboards in minutes:…
2024 · siegeai.com
- 23OS
Hey HN! We are building *open source infrastructure for deploying customer-facing data pipelines.* Here’s our repo https://github.com/pipebird/pipebird and website https://pipebird.com/. Pipebird (YC W22) is designed to enable companies that generate important data to offer secure data pushes to their customers’ warehouses, directly from their products. Our team was previously building in fintech, where we heard from many of our peers that their customers wanted data pushed directly to their warehouses. Customers wanted to bring data into their source of…
2022 · github.com
- 24CA
Hi HN! We’re Clemens and Felix from Cito - thrilled to show you what we’ve built to help data engineers stay on top of data quality issues. Think Datadog meets Incident.io. Tests in dbt are great when checking whether specific expectations are true, but don’t work well for use cases where data patterns may change over time. When relying on testing alone, data teams regularly face situations where business stakeholders identify data issues in dashboards first, eroding trust. In such situations, understanding the implications of an issue and debugging can be a very manual and time-consuming…
2022 · citodata.com
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