Tag: Data

All the articles with the tag "Data".

• Summary: Teaching HDFS Concepts to New Learners

  6 May, 2025

  Introducing Hadoop Distributed File System (HDFS) to newcomers can be both exciting and challenging. To make the learning experience structured and impactful, it’s helpful to break down the core

• Is S3 the New HDFS? Comparisons and Use Cases in Big Data

  29 Apr, 2025

  Over the past decade, the way organizations store and manage big data has shifted dramatically. Once dominated by the Hadoop Distributed File System (HDFS) , the field is now led by Amazon S3 and

• Optimizing Joins in PostgreSQL: Practical Cases

  11 Apr, 2025

  Joins are essential for querying relational databases, but they can significantly impact performance if not optimized correctly. PostgreSQL provides several ways to improve join efficiency, from

• Benchmarking OLTP vs. OLAP: Measuring Performance Effectively

  8 Apr, 2025

  Understanding the performance differences between OLTP (Online Transaction Processing) and OLAP (Online Analytical Processing) is crucial for designing efficient database systems. This post outlines a

• Comparison Between Star Schema and Snowflake Schema in PostgreSQL

  6 Apr, 2025

  Comparison Between Star Schema and Snowflake Schema in PostgreSQL When designing a database for analytical workloads, choosing the right schema can significantly impact performance and query

• Running PySpark on Google Colab: Do You Still Need findspark?

  5 Apr, 2025

  Introduction For a long time, using Apache Spark in Google Colab required manual setup, including installing Spark and configuring Python to recognize it. This was often done using the findspark

• Generating a Calendar Table in Power Query (M Language)

  2 Apr, 2025

  When working with Power BI or other Power Query-supported tools, having a well-structured calendar table is essential for time-based analysis. In this blog post, we will walk through an M Language

• Handling Schema Changes in a Data Warehouse

  31 Mar, 2025

  When building and maintaining a Data Warehouse (DWH) , handling schema changes without breaking existing processes is a crucial challenge for data engineers. As new requirements emerge, we often need