learn here about data pipeline for FREE.....data pipeline consists of several stages that work together to ensure that data is processed efficiently and accurately. it involves....1. data ingestion2. data transformation3. data analysis4. data visualisation5. data storage📌 complete data pipeline diagram can be found here....https://lnkd.in/gdifVyHY📌 FREE guide to data pipeline in AWS, Azure cloud....https://lnkd.in/gtq_8rd9📌 learn more... Continue Reading →
Big Data Learning Plan
Step by Step Plan to learn Big Data (All Free resources Included)1. Learn SQL Basics - https://lnkd.in/g9NEJMVE SQL will be used at a lot of places - Hive/Spark SQL/RDBMS queriesJoins & windowing functions are very important2. Learn Programming/Python for Data Engineering - https://lnkd.in/gr6fFPdU Learn Python to an extent required for Data Engineers.3. Learn the Fundamentals... Continue Reading →
Step by Step approach to Master Big Data (Free Resources)
Step by Step approach to Master Big Data (Free Resources)Step 1 - Learn SQL📌 Basics -https://lnkd.in/gdnhRk8b📌 Advanced -https://lnkd.in/g8tyEKbU📌 Leetcode -https://lnkd.in/gKeSMPmW2. Learn Python basics -📌 Python Tutorial : https://lnkd.in/gPBDBhpA📌 Python for Beginners : https://lnkd.in/gHWyQfQX3. Big Data Concepts -📌 Big Data Fundamentalshttps://lnkd.in/fWZPWKP📌 HDFS Architecturehttps://lnkd.in/fNP7bf7📌 Mapreduce Fundamentalshttps://lnkd.in/g457Wmv📌 Hive tutorial for Beginnershttps://lnkd.in/gJpDMTfD📌 Introduction to Apache Sparkhttps://lnkd.in/gFRpe3-D📌 Spark Accumulator &... Continue Reading →
Data Scientist Roadmap
How I would relearn Data Science In 2024 to get a job: Getting Started: ⬇️ - Data Science Intro: DataCamp- Anaconda Setup: Anaconda Documentation Programming: - Python Basics: Real Python- R Basics: R-bloggers- SQL Fundamentals: SQLZoo- 六 Java for Data Science: Udemy - Java Programming and Software Engineering Fundamentals Mathematics:... Continue Reading →
Big Data Learning Resources
Complete Plan to learn Big Data Step by Step (All Free resources Included) by Sumit Sir.1. Learn SQL Basics - https://lnkd.in/g9NEJMVESQL will be used at a lot of places - Hive/Spark SQL/RDBMS queriesJoins & windowing functions are very important2. Learn Programming/Python for Data Engineering - https://lnkd.in/gr6fFPdULearn Python to an extent required for Data Engineers.3. Learn... Continue Reading →
Cloud Services in one line
If you are an aspiring Data Engineer then you must know these cloud services w.r.t AWS or AZURE or GCP 👇 Save this post for future reference ...1️⃣ Amazon Web Services (AWS)🛠 AWS Data Pipeline: For creating complex data processing workloads.📊 AWS Glue: Our favourite fully managed ETL service.💾 Amazon S3: An object storage service... Continue Reading →
Google Cloud Platform Services Summary
The complete list of services that form Google Cloud Platform is shown below. While Google offers many other services and APIs, only the services below are covered by the Google Cloud Platform terms of service, service level agreements (if applicable), and support offerings. Offerings identified below as Software or Premium Software are not Services under... Continue Reading →
AWS Certification
FREE AWS Certificate by Amazon that you can't miss in 20231. Getting Started with Data Analytics on AWS🔗https://lnkd.in/dwRhRAzM2. Practical Data Science on the AWS Cloud Specialization🔗https://lnkd.in/d3-3GZbG3. Getting Started with AWS Machine Learning🔗https://lnkd.in/dhAp-Vjh4. Introduction to Machine Learning on AWS🔗https://lnkd.in/detfDCWA5. Hands-on Machine Learning with AWS and NVIDIA🔗https://lnkd.in/dgGvATq26. AWS Fundamentals Specialization🔗https://lnkd.in/dSV9jhRz7. Building Modern Python Applications on AWS🔗https://lnkd.in/dQAinFGy8. AWS... Continue Reading →
System Design Blogs
30 Blogs to learn 30 System Design Concepts:1) Content Delivery Network (CDN): https://lnkd.in/gjJrEJeH2) Caching: https://lnkd.in/gC9piQbJ3) Distributed Caching: https://lnkd.in/g7WKydNg4) Latency vs Throughput: https://lnkd.in/g_amhAtN5) CAP Theorem: https://lnkd.in/g3hmVamx6) Load Balancing: https://lnkd.in/gQaa8sXK7) ACID Transactions: https://lnkd.in/gMe2JqaF8) SQL vs NoSQL: https://lnkd.in/g3WC_yxn9) Consistent Hashing: https://lnkd.in/gd3eAQKA10) Database Index: https://lnkd.in/gCeshYVt11) Rate Limiting: https://lnkd.in/gWsTDR3m12) Microservices Architecture: https://lnkd.in/gFXUrz_T13) Strong vs Eventual Consistency: https://lnkd.in/gJ-uXQXZ14) REST vs RPC:... Continue Reading →
Insert, Update and Delete in PySpark
Here's the scenario: We had two data tables, Table_A and Table_B, each containing a "Name" and "Age" column. 📋💡Table_A:Name | Age------------S1 | 20S2 | 23-------------------------Table_B:Name | Age------------S1 | 22S4 | 27Our mission was to determine the differences between these tables and generate a Action between Update, Delete, Insert🚀 and here's the solution we came up... Continue Reading →
CODEBOX 