Top Tweets for #analyticsengineering
So, i just finished Phase 1 of my streamwatch project.
Data Validation for a clearer and accurate business analysis.
Please engage on LinkedIn and check out the project on GitHub.
Gracias✨
#SQL #Snowflake #DataAnalytics #AnalyticsEngineering #DataEngineering #BuildInPublic
What does it take to become a Lead Analytics Engineer?
It’s more than SQL and dbt. From data modeling and pipelines to cloud platforms, data quality, BI, and leadership, these 10 skill areas define the role.
#AnalyticsEngineering #DataEngineering #SQL #dbt #DataAnalytics #CloudComputing #DataCareers
Look what finally made it into our hands! 📚🤩
Analytics Engineering with Microsoft Fabric and Power BI is officially a real, physical book!
@ShbWatson
#MicrosoftFabric #PowerBI #AnalyticsEngineering #OReilly #MicrosoftData
Just completed an ELT Data pipeline
#dataengineering #dataanalysis #analyticsengineering #datamodeling
Practiced data modeling using dbt and SQL
GitHub repo below 👇🏾
The difference between a beginner and a senior SQL analyst isn’t syntax. It’s planning, validating data, optimizing performance, and writing queries others can trust and maintain. Clean SQL solves problems. Great SQL prevents them. #SQL #DataAnalytics #AnalyticsEngineering #CareerGrowth #DataCareers
Like, Retweet, Bookmark and Follow @aiguidehq for more such posts
DBT project
لينك البروجكت علي الجيت هاي في أول ريبلاي
#dbt #DataEngineering #AnalyticsEngineering
https://t.co/Y54wvsGrSF
The difference between a beginner and a senior SQL analyst isn’t syntax. It’s planning, validating data, optimizing performance, and writing queries others can trust and maintain. Clean SQL solves problems. Great SQL prevents them. #SQL #DataAnalytics #AnalyticsEngineering #CareerGrowth #DataCareers
Like, Retweet, Bookmark and Follow @aiguidehq for more such posts
The difference between a beginner and a senior SQL analyst isn’t syntax. It’s planning, validating data, optimizing performance, and writing queries others can trust and maintain. Clean SQL solves problems. Great SQL prevents them. #SQL #DataAnalytics #AnalyticsEngineering #CareerGrowth #DataCareers
Honored to be named a finalist for Technical Contributor of the Year at the dbt Community Awards! 🏆
So grateful for this community and to be recognized alongside such inspiring finalists. See you at dbt Summit on Sept 17!
#dbt #analyticsengineering #data
Introducing DBTLint 🔍 A linter for your dbt projects — catch issues, get a clarity score, and keep your data models clean before they ship.
Check it out👇
https://t.co/1hkBAhOOjF
#dbt #sqlfluff #analyticsengineering
Just shipped Shopflow, a fully automated e-commerce analytics pipeline
Python → BigQuery → dbt → GitHub Actions → Power BI
28 data quality tests. Daily automation. Zero manual steps
Repo: https://t.co/9kx3tDwcrH
#AnalyticsEngineering #dbt #BigQuery #DataAnalytics
A strong reminder that the biggest gains often come from choosing the right execution model, not micro-optimising code.
#DataEngineering #Scalability #PerformanceOptimisation #BigData #AnalyticsEngineering
Why Data Products Need Stable Interfaces
Applications need stable interfaces. Not direct access to tables, schemas, and query logic.
That is what separates a data product from raw data.
#dataengineering #analyticsengineering #dataproducts #analyticsbackend #ai
The Difference Between a Semantic Layer and an Analytics Runtime
A semantic layer defines analytical data.
An analytics backend helps serve it.
Gaur Data is building the backend for data applications.
#dataengineering #analyticsengineering #analyticsbackend #semanticlayer #ai
Warehouses provide data.
Applications need analytics APIs, permissions, and stable interfaces. That's an analytics backend.
Gaur Data is the backend for data applications.
#dataengineering #analyticsengineering #analyticsbackend #dataapplications #ai
Why Is Embedded Analytics Still So Hard?
Because the charts are not the hard part.
Permissions, semantics, APIs, and runtime behavior are.
Gaur Data is building a runtime for analytical data.
#dataengineering #analyticsengineering #embeddedanalytics #semanticlayer #ai
Should Customer Dashboards Have Their Own Backend?
Most customer dashboards become analytical systems.
The real question: is the backend intentional?
gaur is building a runtime for analytical data.
#dataengineering #analyticsengineering #embeddedanalytics #semanticlayer #ai
What If Analytics Had APIs Before Dashboards?
Analytics grew around dashboards. So dashboards became the architecture.
What if contracts came first?
gaur is building a runtime for analytical data.
#dataengineering #analyticsengineering #semanticlayer #api #ai
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