Tag: #pyspark
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UDF vs Inbuilt Functions in PySpark — The Simple Guide
If you’re working with PySpark, you’ve probably asked yourself this at some point: “Should I use a built-in function or just write my own?” Great question — and one that can have a huge impact on your Spark application’s performance. In PySpark, there are two main ways to transform or manipulate your data: Using Inbuilt…
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Unleashing the Power of Explode in PySpark: A Comprehensive Guide
Efficiently transforming nested data into individual rows form helps ensure accurate processing and analysis in PySpark. This guide shows you how to harness explode to streamline your data preparation process. Modern data pipelines increasingly deal with nested, semi-structured data — like JSON arrays, structs, or lists of values inside a single column.This is especially common…
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Data Migration 2025: What It Is & Why It’s Important?
Data serves as the essential support structure across all industries today. Organizations seeking to modernize systems require efficient data migration to improve operational efficiency through improved data access. Partnering with the best data migration services company could make this transformation seamless and more secure. As businesses continue to grow, what is a data migration? Simply…
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![Difference between Data Science and Machine Learning [2025]](https://diggibyte.com/wp-content/uploads/2025/07/lY6meKzT.jpg)
Difference between Data Science and Machine Learning [2025]
Knowing the difference between data science and machine learning is important for businesses and professionals. This knowledge helps them stay ahead in the AI-driven world. Data science focuses on extracting meaningful insights from structured and unstructured data. Machine learning enables systems to learn from data and make predictions using algorithms without explicit programming. Data science…
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Delta Lake Speed-Up: Z-Order on Single vs. Multiple Columns
Introduction As organizations ingest massive volumes of data into Delta Lake, query performance becomes critical, especially for dashboards, ad-hoc analysis, and downstream ETL jobs. One powerful technique to reduce query latency and improve data skipping is Z-Order Optimization. In this article, let’s cover: What Z-Ordering is How to apply it to single vs. multiple columns…
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Data Visualization 2025: What It Is & Why It’s Important
Data visualization enables complex information to become graphical representations such as infographics, maps, graphs and charts amid the global exponential increase of data. This change allows business people and researchers to show data better. It helps improve communication, decision-making and understanding. Data visualization tools enable companies and data analysts to identify patterns and correlations hidden…
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The Power of Timezone Conversion in PySpark: Boost Business Efficiency and Insights by Localizing Timestamps
In today’s increasingly globalized business landscape, data doesn’t operate within a single timezone. Whether you’re tracking e-commerce transactions, customer service interactions, or website activity, timestamps are often recorded in UTC (Coordinated Universal Time). While UTC ensures consistency, businesses need local time zones for accurate, actionable insights. Converting UTC timestamps to local time based on a country’s specific…