๐๐ง๐ => ๐๐ ๐๐ฟ๐ฎ๐ฐ๐ | ๐ง๐ฟ๐ฎ๐ป๐๐ณ๐ผ๐ฟ๐บ | ๐๐ผ๐ฎ๐ฑEvent-Driven Serverless ETL Pipelines is a data processing architecture that is used to process large amounts of data in real-time.Here data is processed as soon as it is generated, rather than being stored and processed later.This allows for faster processing times and more efficient use of resources.Here are the... Continue Reading →
FREE DATA ENGINEERING COURSES ON CLOUD
Data engineering is the backbone of the modern data-driven world. Itโs the meticulous process of designing and building systems for collecting, storing, and analyzing data at scale. However, finding comprehensive projects and courses that are also free can be a challenge. To bridge this gap, Iโve created a list of five end-to-end data engineering courses... Continue Reading →
Pyspark UDF
#PySpark_UDF_with_the_help_of_an_example๐ ๐ ๐ The most important aspect of Spark SQL & DataFrame is PySpark UDF (i.e., User Defined Function), which is used to expand PySpark's built-in capabilities. UDFs in PySpark work similarly to UDFs in conventional databases.โ We write a Python function and wrap it in PySpark SQL udf() or register it as udf and... Continue Reading →
Delete Duplicates in Pyspark Dataframe
#ScenarioThere are two ways to handle row duplication in PySpark dataframes. The distinct() function in PySpark is used to drop/remove duplicate rows (all columns) from a DataFrame, while dropDuplicates() is used to drop rows based on one or more columns. Hereโs an example showing how to utilize the distinct() and dropDuplicates() methods- First, we need... Continue Reading →
Covid-19 Data Analysis | End-To-End Data Engineering Project
Description:In this project, I undertook a comprehensive data engineering journey focused on COVID-19 data, leveraging AWS services to create a powerful data infrastructure. My goal was to make the COVID-19 data accessible, understandable, and valuable for analysis.Key Steps:Data Collection and Storage: I started by downloading COVID-19 datasets from Registry of Open Data on AWS and... Continue Reading →
Big Data Pro Resources
#Resources Referred by me for Big data Technologies These resources are available for free in YouTube, which helped me to crack CISCO.. and for you to crack product based companies also..1.Hadoop ,sqoop and Hive concepts by Saif shaik:https://lnkd.in/ewyYweTJ2.pyspark concepts in depth by karunakar goud:https://lnkd.in/eNtFkxmd3.Another spark playlist which useful Raja's Data Engineering channel.https://lnkd.in/eqiy7dBS4. Hadoop and Kafka... Continue Reading →
Crack The Spark
๐Data Engineer Interview Experience๐ขApache SparkโHow "Executor Out Of Memory" can be explained in step by step manner๐๐ฝhttps://lnkd.in/gPsrw9Wp How "Salting" can be explained in step by step manner๐๐ฝhttps://lnkd.in/gUQUPj8x How "Data Locality in Spark" can be explained in step by step manner๐๐ฝhttps://lnkd.in/gcQ_CJZs How "Garbage Collection (GC) Tuning" can be explained in step by step manner๐๐ฝhttps://lnkd.in/gY5CQM9c How "Predicate... Continue Reading →
Top Github Repositories
Top Github repositories which would be really helpful for job preparation, upskilling and much more ๐ซ - Free programming books : https://lnkd.in/gbSk9NRr- System Design : https://lnkd.in/graSZG3Phttps://lnkd.in/gykTqH6k- Project Based Learning : https://lnkd.in/gjewtywD- Coding Interview : https://lnkd.in/ge7e7gyh- Resources for Preparation of Placements : https://lnkd.in/d6zpHj4P- Data Science : https://lnkd.in/gbnGnGRD- Projects : https://lnkd.in/gNvjU9jr- For Roadmaps : https://lnkd.in/gYNSH-dc- JavaScript :... Continue Reading →
AWS Training
AWS just launched a new free training, along with a digital badge "Migrations Foundations". This means you can now earn up to 12 AWS digital badges at no cost!To secure this badge, simply enroll in the free course and score 80% or higher on the final assessment. It's a fantastic opportunity to demonstrate your cloud... Continue Reading →
Types of Dimensions in DWH
Types of Dimensions in Dimensional Data Modelling๐ There are 9 types of Dimensions/metrics when dealing with Dimensional Data Modelling. They are given below:๐นConformed Dimension๐นOutrigger Dimension๐นShrunken Dimension๐นRole-Playing Dimension๐นDimension to Dimension Table๐นJunk Dimension๐นDegenerate Dimension๐นSwappable Dimension๐นStep Dimensionโ Conformed DimensionA Conformed Dimension is a type of Dimension that has the same meaning to all the Facts it relates to.... Continue Reading →