PinnedComparing Spark and MapReduce: The Pros and Cons of Two Popular Big Data Processing Frameworks on…Spark and MapReduce are both popular big data processing frameworks that run on the Hadoop ecosystem. Both have their own unique features…Jan 9, 2023Jan 9, 2023
PinnedUnlocking the Power of Big Data Processing with Resilient Distributed DatasetsA resilient distributed dataset (RDD) is a fundamental data structure in the Apache Spark framework for distributed computing. It is a…Jan 10, 2023Jan 10, 2023
Boosting R Performance with Parallel Processing pacakge snowUnderstanding Parallel ComputingSep 3Sep 3
Exploring Outliers, Leverage, and InfluenceUnveiling Hidden Insights in Data AnalysisJul 6, 2023Jul 6, 2023
Building a Data Pipeline for Blockchain Data with Apache Kafka and Apache FlinkThe rise of blockchain technology has brought about an explosion in the amount of data being generated and consumed by blockchain networks…Mar 16, 2023Mar 16, 2023
Introduction to Streamlit for Data EngineeringData engineering is a critical aspect of any data-driven organization, where data scientists and analysts work with large amounts of data…Mar 12, 2023Mar 12, 2023
Published inTowards Data EngineeringBuilding a Real-time Fraud Detection System with Apache Kafka and Apache Storm — A Step-by-Step…IntroductionJan 31, 2023Jan 31, 2023
Building a data pipeline for natural language processing with Apache Kafka and Apache Spark.Are you tired of slow and clunky data pipelines for your natural language processing (NLP) projects? Well, buckle up because we have the…Jan 31, 20232Jan 31, 20232
Published inTowards Data EngineeringBuilding a Scalable and Real-time Data Pipeline for Social Media Analytics with Apache Kafka and…IntroductionJan 16, 20231Jan 16, 20231
Mastering Missing Data: A Comprehensive Guide with Code Examples and Illustrations on How to Handle…Handling missing data in a data pipeline can be a tricky task, but with the right approach, it can be effectively managed. In this article…Jan 13, 2023Jan 13, 2023
