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Automating Stock Data ETL pipeline using Python API on Databricks to Azure Sql Database
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🚀 Building Your First Azure ETL Pipeline with Python: A Simple Guide🚀
In this video, we're diving deep into the creation of Azure Automated ETL pipelines using PySpark on Databricks for Indian stock market data.
And guess what? We're waving goodbye to those pesky Py4JJ errors by tapping into the magic of Databricks.
Java Runtime error.
🛠 What's in Our Toolbox:
PySpark (because, let's face it, it's awesome)
Databricks (our secret sauce for smooth PySpark operations)
Azure SQL Server (for all our data storage needs)
JDBC Connection (because connecting the dots is key!)
And here's the twist—we're spicing things up with the bsedata library! 🌶️ Yes, we're making our data game even stronger.
📅 Why Daily Automation?
Imagine waking up every morning with fresh, updated data on the Nifty 50. 🌞 That's right, we're not just here to play around—we're automating ETL pipelines to run daily. Stay ahead of the curve and keep your financial data game on point!
💼 The End Goal: Financial Models!
Now, why are we doing all this? Because we're gearing up for the big leagues—we want to create kickass financial models! 💹 Our end goal is to empower you to build robust models that can analyze, predict, and make sense of the ever-dynamic financial landscape.
📈 What's on the Menu:
PySpark Basics (we're keeping it simple and fun)
Databricks Integration (your Py4JJ errors don't stand a chance!)
Azure SQL Server Connection (because data needs a home, right?)
Workflow Automation (let's set it and forget it)
📚 Who's Invited to the Party:
Data Engineers (come sharpen those ETL skills)
Data Scientists (let's sprinkle some magic on that data)
Python Developers (because Python makes everything better)
Azure Enthusiasts (you're in for a treat)
And hey, if you're wondering about Nifty 50, we got you covered! We'll be using it as our playground to create insightful financial models.
So, grab your favorite beverage, hit play, and let's navigate the world of PySpark, Databricks, and financial data together. If you're as excited as we are, don't forget to like, share, and subscribe! 🚀✨
#Azure #PySpark #Databricks #ETLPipelines #DataProcessing #SQLServer #JDBCConnection #StockMarketData #bsedata #Nifty50 #FinancialModels
BOOK A SESSION WITH MENTOR @amazon @google @microsoft -
In this video, we're diving deep into the creation of Azure Automated ETL pipelines using PySpark on Databricks for Indian stock market data.
And guess what? We're waving goodbye to those pesky Py4JJ errors by tapping into the magic of Databricks.
Java Runtime error.
🛠 What's in Our Toolbox:
PySpark (because, let's face it, it's awesome)
Databricks (our secret sauce for smooth PySpark operations)
Azure SQL Server (for all our data storage needs)
JDBC Connection (because connecting the dots is key!)
And here's the twist—we're spicing things up with the bsedata library! 🌶️ Yes, we're making our data game even stronger.
📅 Why Daily Automation?
Imagine waking up every morning with fresh, updated data on the Nifty 50. 🌞 That's right, we're not just here to play around—we're automating ETL pipelines to run daily. Stay ahead of the curve and keep your financial data game on point!
💼 The End Goal: Financial Models!
Now, why are we doing all this? Because we're gearing up for the big leagues—we want to create kickass financial models! 💹 Our end goal is to empower you to build robust models that can analyze, predict, and make sense of the ever-dynamic financial landscape.
📈 What's on the Menu:
PySpark Basics (we're keeping it simple and fun)
Databricks Integration (your Py4JJ errors don't stand a chance!)
Azure SQL Server Connection (because data needs a home, right?)
Workflow Automation (let's set it and forget it)
📚 Who's Invited to the Party:
Data Engineers (come sharpen those ETL skills)
Data Scientists (let's sprinkle some magic on that data)
Python Developers (because Python makes everything better)
Azure Enthusiasts (you're in for a treat)
And hey, if you're wondering about Nifty 50, we got you covered! We'll be using it as our playground to create insightful financial models.
So, grab your favorite beverage, hit play, and let's navigate the world of PySpark, Databricks, and financial data together. If you're as excited as we are, don't forget to like, share, and subscribe! 🚀✨
#Azure #PySpark #Databricks #ETLPipelines #DataProcessing #SQLServer #JDBCConnection #StockMarketData #bsedata #Nifty50 #FinancialModels
BOOK A SESSION WITH MENTOR @amazon @google @microsoft -
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