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How to Normalize Relational Databases With SQL Code?

Analytics Vidhya

The database is the major element of a data science project. To generate actionable insights, the database must be centralized and organized efficiently. If a corrupted, unorganized, or redundant database is used, the results of the analysis may become inconsistent and highly misleading. appeared first on Analytics Vidhya.

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SQL Injection: The Cyber Attack Hiding in Your Database

Analytics Vidhya

Introduction SQL injection is an attack in which a malicious user can insert arbitrary SQL code into a web application’s query, allowing them to gain unauthorized access to a database. We can use this to steal sensitive information or make unauthorized changes to the data stored in the database.

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Mirroring SQL Server Database to Microsoft Fabric

Striim

SQL2Fabric Mirroring is a new fully managed service offered by Striim to mirror on premise SQL Databases. It’s a collaborative service between Striim and Microsoft based on Fabric Open Mirroring that enables real-time data replication from on-premise SQL Server databases to Azure Fabric OneLake.

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5 Free University Courses to Learn Databases and SQL

KDnuggets

Looking to learn SQL and databases to level up your data science skills? Learn SQL, database internals, and much more with these free university courses.

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Introduction to Databases with SQL: Free Harvard Course

KDnuggets

Want to learn SQL the Harvard way? Start learning today with CS50 SQL, a free course on databases with SQL from Harvard.

SQL 140
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MSSQL vs MySQL: Comparing Powerhouses of Databases

Analytics Vidhya

Introduction In the bustling arena of database management systems, two heavyweight contenders emerge, each carrying its arsenal of features and capabilities. In one corner, we have the suave and sophisticated Microsoft SQL Server (MSSQL), donned in the elegance of enterprise-level prowess.

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Surveying The Market Of Database Products

Data Engineering Podcast

Summary Databases are the core of most applications, whether transactional or analytical. In recent years the selection of database products has exploded, making the critical decision of which engine(s) to use even more difficult. What are the aspects of the database market that keep you interested as a VP of product?

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