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What is a Prime Attribute in DBMS? Explanation with Examples

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  In the world of relational databases, understanding how data is structured and accessed is critical for effective database design. One important concept that often appears in database theory, especially during normalization, is the Prime Attribute in DBMS . This blog explains what a prime attribute is, why it matters, and how it fits into key concepts such as functional dependencies and normal forms. What is a Prime Attribute? A prime attribute is an attribute (or column) that is part of any candidate key of a relation (table) in a database. In simpler terms, if an attribute helps uniquely identify a row in a table — either on its own or in combination with others — it is considered a prime attribute. Related Concepts Before diving deeper, it's helpful to understand some related terms: Candidate Key : A minimal set of attributes that can uniquely identify each tuple (row) in a relation. Primary Key : A candidate key selected by the database designer to uniquely iden...
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Optimizing React Apps with the Latest Webpack & Vite Features

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 In the world of React development, performance and developer experience are critical. Build tools like Webpack and Vite play a central role in optimizing applications for both development speed and production performance. As React 19 gains traction, it’s equally important to understand how these modern bundlers have evolved to support faster, leaner, and more scalable React apps. In this article, we’ll explore the latest features of Webpack and Vite and how to use them to optimize React applications—whether you're building a small project or a large-scale full stack application. Why Optimization Matters in React Apps React is a powerful library, but without efficient tooling, your application can: Load slowly on mobile or poor networks Suffer from large bundle sizes Experience delayed interactions and layout shifts Modern bundlers like Webpack 5+ and Vite 5+ help eliminate these issues through smart optimizations, better build strategies, and faster dev environ...
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Real-World Use Cases of AWS in 2025: From Startups to Enterprises

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  In 2025, Amazon Web Services ( AWS) is more than just a cloud platform — it’s the foundation of digital transformation across startups, mid- sized businesses, and global enterprises. From launching mobile apps to managing big data, AWS empowers organizations of all sizes to build, scale, and innovate faster than ever. At TechnoGeeks Training Institute , we believe the best way to understand AWS is through real- world use cases. Whether you're an aspiring cloud engineer or a business leader looking to modernize infrastructure, these practical examples show why AWS is the platform of choice across industries. 1. Startups: Rapid Product Development and Scaling Use Case: Building a Scalable SaaS Platform Startups often need to launch fast, iterate rapidly, and scale on demand. AWS services like EC2 , Lambda , API Gateway , and DynamoDB allow startups to run serverless, low- cost applications with minimal infrastructure overhead. Example: A fintech startup used AWS Lambda t...
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Weak References and Memory Leaks: What Garbage Collection Can’t Solve

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 Garbage collection is a cornerstone of modern programming languages. It frees developers from the burden of manual memory management and reduces the risk of common bugs like dangling pointers or use-after-free errors. However, despite its advantages, garbage collection isn’t perfect. Memory leaks can and do still occur, even in languages that offer automatic memory management. In this article, we’ll explore the limitations of garbage collection, the role of weak references, and why understanding Garbage Collection in Data Structure is still essential for writing efficient, leak-free applications. The Role of Garbage Collection At a basic level, garbage collection automatically reclaims memory occupied by objects that are no longer in use. When nothing in your program refers to an object anymore, it becomes “unreachable” and is eligible for cleanup by the garbage collector. This process works well for straightforward object lifecycles, but things get more complicated when ref...
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Magic Tables and Performance: What You Need to Know

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  Magic Tables in SQL —the INSERTED and DELETED virtual tables used in triggers—are powerful tools for tracking data changes. They let you write custom logic that reacts instantly to INSERT , UPDATE , and DELETE operations. But while they’re incredibly useful, they’re also not without cost. In this post, we’ll explore how Magic Tables affect performance, when to use them wisely, and alternatives for high-scale scenarios. Quick Refresher: What Are Magic Tables? Magic Tables are temporary, in-memory tables that SQL Server creates automatically when a DML trigger is fired. Their purpose is to hold the before and/or after state of the data being modified: INSERTED : Contains new rows (used in INSERT and UPDATE ) DELETED : Contains old rows (used in DELETE and UPDATE ) These tables enable powerful use cases like: Custom audit logs Data validation Change tracking Cascading business logic But What’s the Catch?  Triggers Add Overhead Every time...
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Advanced Career Paths in Data Science: From Research Scientist to ML Architect

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  As data becomes the fuel of modern decision-making, the demand for skilled data professionals continues to grow— not just for entry-level roles, but for advanced, strategic positions that drive innovation and business value for Data Science . While many begin their journey as data analysts or junior data scientists, the road ahead opens into diverse, high-impact roles such as Machine Learning Architect, AI Research Scientist, and Data Science Manager . These roles require deep technical knowledge, domain expertise, and strong cross-functional collaboration skills. In this blog, we’ll explore the most exciting advanced career paths in data science, the skills they demand, and how TechnoGeeks Training Institute prepares you to reach those levels. Why Consider an Advanced Role in Data Science? As organizations mature in their use of data, they need experts who can: Architect scalable AI systems Conduct cutting-edge research Lead data science teams Translate busine...
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