Data Engineering Services: Solving Business Data Challenges
Learn how robust data pipelines, automated workflows, & efficient data management improve decision-making, operational efficiency, & support business growth.
@cssoftsolutions.bsky.social
@cssoftsolutions.bsky.socialData Engineering Services: Solving Business Data Challenges
Learn how robust data pipelines, automated workflows, & efficient data management improve decision-making, operational efficiency, & support business growth.
@databased-work.bsky.socialA second look at the CSV Canary app. We see how to detect CSV file header changes and how to export your reports to HTML, markdown and Excel.
@databased-work.bsky.socialHave bad CSV files? There's an app for that.
This 18-minute intro will show you have to detect issues with your data BEFORE you try to ingest it. Analyze data type violations, see the number and % of empty rows for each column.
@hackernoon.comI fixed a recurring data ingestion bottleneck by working with a vendor to introduce date-partitioned exports and reduce unnecessary file discovery. #dataengineering
@news.karthihegde.devHow shredding JSON is giving Logfire 1000x query speedups
Discussion | lobsters | Author: typesanitizer
@tgvalidator.bsky.socialEver get a response from an API that doesn't say 'registered' or 'unregistered'? A non-zero business code signals an undecided state, not a simple 'no.' Use these signals to refine your data pipeline logic. Learn more at https://tgvalidator.com/api-docs?utm_source=bsky #API #DataEngineering
@powerbitips.bsky.social567 - Customers need a portal to drop files into. Now you can build the uploader as a Fabric app and the file lands in your lakehouse on its own. Here's what that unlocks for notebooks.
@iam.slys.devPostHog's hard problem is not adding another tool. It is making analytics, replay, flags, experiments, and customer data keep the same meaning in one stack. The value is the event contract, not the screen count. #SystemsLiteracy #DataEngineering
@purplefrogdata.bsky.socialYour pipeline succeeded. So why is your data still wrong? 👀
Hard-deleted source rows can quietly remain in a warehouse because there's no ModifiedDate for an incremental load to catch.
Jon explains how to handle them🐸⤵️ www.purplefrogsystems.com/2026/09/how-... #DataEngineering #ETL
@sriwworldofcoding.bsky.socialYour data lake probably has thousands of Parquet files.
But without a table format, it cannot reliably answer:
Which files are current?
Did this write commit?
What did the table look like yesterday?
Can I safely update one row?
@carrierlookup.bsky.socialStop treating carrier lookup as a simple address book. Start using the country_code signal as a diagnostic layer to validate E.164 consistency across your data pipelines. Learn more about data health at https://carrierlookup.online/?utm_source=bsky #DataQuality #DataEngineering
@numberchecker.bsky.socialStop treating your data-pipeline like a 'set-and-forget' batch task. By monitoring REST API response patterns, you can build robust error-handling logic directly into your workflow instead of managing lists manually. Explore our API: https://numberchecker.ai/?utm_source=bsky #DataEngineering #API
@survive-or-die.bsky.socialSCD2 tip: test the exact change boundary. Python/SQLite kit: 9 tests + checklist. £5; educational. #DataEngineering
@infoq.comWhat is an ontology, and why is #Netflix using one for observability?
An ontology encodes meaning through simple Subject-Predicate-Object triples, helping connect data and make it more useful for enterprise AI.
🎥 Watch the full video: buff.ly/fIoqHqD
@artestomellivoura.bsky.social0HFLOW: OPEN-SOURCE DATA PIPELINES POWERING THE FUTURE OF ROBOTICS & PHYSICAL AI 🤖⚙️
#HFlow #HebbianRobotics #PhysicalAI #Robotics #ArtificialIntelligence #OpenSource #MachineLearning #RoboticsEngineering #AITraining #DataEngineering #DataPipelines #RobotLearning #Automation #Python #FutureOfAI
@tgvalidator.bsky.socialStruggling with API ingestion errors? Often, a failing check isn't about the service—it's about the input format. Ensure your identifiers are strictly E.164 compliant to keep your pipeline running smoothly. Learn more at https://tgvalidator.com/?utm_source=bsky #API #DataEngineering
@rajeshdataai.bsky.social
