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Day 76: Automating Daily ETL Pipelines for Enterprise Data πŸš€ Manual ETL processes don’t scale ❌ ADF helps automate enterprise data pipelines with scheduling, monitoring & orchestration at scale ⚑ βš™
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Day 75: Real-Time Data Processing Pipeline for IoT 🌐⚑ IoT devices generate massive streams of data every second πŸ“‘ ADF + Azure services help process this data in near real-time for faster insights οΏ½
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Day 74: Building a CDC Pipeline with SQL Server πŸ”„πŸš€ Stop reloading full tables ❌ Use Change Data Capture (CDC) to load only inserts, updates & deletes efficiently ⚑ βš™οΈ CDC Pipeline Flow 1️⃣ Enable
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Day 73: Implementing Data Warehouse Pipelines πŸš€ Turn raw data into structured, analytics-ready insights with ADF-powered data warehouse pipelines πŸ“Š βš™οΈ Pipeline Flow 1️⃣ Ingest β†’ Source systems (D
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Day 72: End-to-End Data Integration with ADF πŸš€ ADF enables complete data integration β€” from ingestion to insights πŸ“Š βš™οΈ End-to-End Flow 1️⃣ Ingest β†’ APIs / DB / Files 2️⃣ Store β†’ ADLS (Raw/Bronze)
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Day 71: Building a Data Lake Pipeline from Scratch πŸš€ Want to build an end-to-end data lake pipeline in ADF? Here’s a simple blueprint πŸ‘‡ βš™οΈ Pipeline Flow 1️⃣ Ingest β†’ Source (API/DB/Files) β†’ ADLS
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Day 70: Industry Best Practices for ADF Projects πŸš€ Building enterprise-grade Azure Data Factory solutions? Follow these industry-proven best practices to ensure scalability, security, and reliabilit
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Day 69: ADF vs Data Factory V2 – What’s New? πŸš€ Confused between ADF (V1) and ADF V2? Let’s simplify πŸ‘‡ βš”οΈ Key Differences ADF V1 (Old) ❌ Limited transformations ❌ No visual UI (mostly code-based)
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Day 68: Implementing Data Lineage in ADF πŸ” Understand where your data comes from, how it transforms, and where it goes. Data lineage in Azure Data Factory ensures transparency, trust, and governance
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Day 67: Deploying ADF Pipelines with DevOps πŸš€ Take your ADF pipelines from Dev β†’ Test β†’ Prod seamlessly using Azure DevOps CI/CD ⚑ βš™οΈ Deployment Flow 1️⃣ Develop pipelines in Git-enabled ADF 2️⃣ P
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Day 66: Automating ADF Deployment using ARM Templates πŸš€ Manual deployments = errors & delays ❌ Use ARM Templates to automate ADF deployments across environments ⚑ βš™οΈ How It Works 1️⃣ Develop pipel
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Day 65: Version Control & ADF Collaboration with Git πŸš€ Working in teams on ADF? Git is a must πŸ”₯ It enables version control, collaboration & safe deployments βš™οΈ How Git Works with ADF 1️⃣ Connect
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About @data_coffe

Abhishek Tripathi is a Instagram nano influencer in the Science, Technology & Engineering category. With 3.1K followers and 12 posts, data_coffe's account shows a follower-to-following ratio of 49.9:1. View all content anonymously on Pictame - no login required.

data_coffe's engagement rate sits at 0.20%. For accounts with 1K-10K followers, the average is around 5%, so there's some room to grow β€” though every community is unique.

Out of the last 12 posts, 0% are videos and 100% are photos. Content shows up about every 4 days. Captions lean detailed, averaging 1652 characters.

0.20% engagement rate β€” room to grow compared to average for 1K-10K follower accounts.
Posts about every 4 days.
49.9:1 follower-to-following ratio.

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data_coffe
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@data_coffe

Abhishek Tripathi

PublicScience, Technology & Engineering
Posts
12
Followers
3.1K
Top Hashtags
#cloud#cloudtech#cloudtechnology#cloudcomputing#cloudcomputingservices#cloudengineer#cloudengineering#azuredata

Explore the most impactful hashtags used in recent posts. These tags highlight the core interests and trending topics that define this profile's digital influence and content strategy.

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Popular Hashtags

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Following
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Avg. Likes
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Engagement
0.19%

⚑️ Data β€’ SQL β€’ Data Engineering πŸ‘¨β€πŸ’» Big Data β€’ Databricks . Data Architect ☁️ Azure | AWS | Google Cloud β˜•οΈ #datae...

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