In the world of data and task automation, managing workflows efficiently is crucial. This is where Apache Airflow comes into play. Imagine having a tool that can help you automate and schedule tasks, coordinate data flows, and handle complex workflows seamlessly. This is exactly what Airflow does, making it an essential tool for modern data engineers and developers. In this article, we’ll take a beginner-friendly journey into the world of Airflow and explore its core concepts.
Tag: Big data
DataBricks | How to Create a Free account on Databricks?
DataBricks is a cloud-based data engineering platform that allows you to collaborate with other data scientists, analysts, and engineers to build and deploy data-driven applications. In this article, we will guide you through the process of creating a free account on DataBricks for the community edition. Community Edition is a limited Databricks environment for personal use and training.
Apache Airflow | Write your first DAG in Apache Airflow
Apache Airflow is an open-source platform that allows developers to programmatically create, schedule, and monitor workflows as directed acyclic graphs (DAGs). With Airflow, you can define complex workflows with dependencies and execute them automatically or manually. In this article, we will guide you through the process of setting up Airflow and creating your first DAG.
BigData | Difference between ELT and ETL
As a data professional, one of the most important aspects of our job is to ensure that data is accurate, timely, and accessible for analysis. Two common approaches to data integration are ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform).
Why Do We Need Bigdata Technology?
Why Big Data?
- To process huge amounts of data which traditional systems (like your pc/ laptop) are not capable of processing.
- To process huge amounts of data we need to store it first.
Example: Suppose we need to store 150 TBs of data, can our traditional system/ laptop which have 1 TB capacity store these huge amounts of data? No Right.
Introduction To Big Data
FORMAL DEFINATION GIVEN BY IBM IS:
Any data which is characterized by 3v’s is termed as “BIGDATA”.
These are:
1) Volume
2) Variety
3) Velocity
End to End Data Engineering Roadmap
End to End Data Engineering Roadmap:
Prerequisites:
—————-
1. Basic Linux commands.
2. Programming fundamentals.
3. SQL is very important.
How to prepare for Databricks Certified Associate Developer for Apache Spark Exam ?
In this post we will see the preparation strategy for Databricks Certified Associate Developer for Apache Spark Exam.
This certification exam assesses the understanding of the Spark DataFrame/SQL API and the ability to apply the Spark DataFrame/SQL API to complete basic data manipulation tasks within a Spark session.
This certification exam assesses the understanding of the Spark DataFrame/SQL API and the ability to apply the Spark DataFrame/SQL API to complete basic data manipulation tasks within a Spark session.
Common Data Engineer Theoretical Interview Questions
In this post, we will see the common Data Engineer Theoretical Interview Questions asked in Companies. Let’ s see the questions: