Archana GoyalNavigating a Career Transition into Data EngineeringThe rise of big data has transformed the way businesses operate, driving a surge in demand for data professionals. Among the most…3d ago3d ago
Archana GoyalComparative study of Logging FrameworkChoosing the right logging framework for Java application depends on several factors, including your specific needs, performance…Aug 21Aug 21
Archana GoyalData Engineering Series 7: Real time Stream Processing with Spark and KafkaThis is part 7 of Data Engineering series. And in this part, we will discuss about Stream Processing with SPark and Kafka.Stream processing…Jul 6Jul 6
Archana GoyalData Engineering Series 6: Batch Processing with Apache SparkWelcome to Part 6 of my Data Engineering Series. In this part, we will discuss about Batch processing with Spark. Batch processing is a…Jul 6Jul 6
Archana GoyalHow to Choose the Perfect Data Orchestration Tool: A Comparative GuideIn the era of big data, efficient data orchestration is crucial for managing complex workflows, automating data pipelines, and ensuring…Jun 30Jun 30
Archana GoyalImplementing Data Orchestration: A Step-by-Step ScenarioLet’s walk through a scenario to illustrate each step in implementing data orchestration for a data pipeline designed to process customer…Jun 30Jun 30
Archana GoyalData Engineering Series 5— Data OrchestrationWelcome to Part 5 of our 10-part series on Data Engineering concepts. In this installment, we delve into the world of Data Orchestration…Jun 30Jun 30
Archana GoyalData Engineering Series 4 — Data PipelinesWelcome to Part 4 of our 10-part series on Data Engineering concepts. In this installment, we will dive into the world of Data Pipelines…Jun 30Jun 30
Archana GoyalData Pipeline Types, Usecase and Technology with ToolsThis is a continued blog forJun 30Jun 30
Archana GoyalData Engineering Series 3— Data Quality and GovernanceWelcome to Part 3 of our 10-part series on Data Engineering concepts. In this part, we will delve into two critical aspects of data…Jun 29Jun 29