Luthfa Rasha’s Post

Day 20: 💪 Are You Utilizing SQL's Data Types Effectively? Enhance Your Data Integrity! Choosing the right data types in SQL is vital for performance and data integrity! Selecting appropriate data types can impact the storage efficiency and performance of your database. Key Considerations for Data Types: - Use Appropriate Sizes: Avoid oversizing data types, as it can lead to wasted space and slower performance. - Choose the Right Type: Understand the differences between VARCHAR, NVARCHAR, INT, FLOAT, and more. By leveraging the right data types, you can enhance data integrity and query performance. What data types do you find most useful? Let’s share tips! 📏 #SQL #DataTypes #DataIntegrity #DataEngineering #DatabaseOptimization

Blog: Data observability vs Database observability 🔍 In this blog we explore what they are and why you need them and clear up any confusion about these similar sounding terms. Read more: https://lnkd.in/erDysWNT #DBmarlin #ApplicationPerformance #Database #Blog

Blog: Data observability vs Database observability🔍 In this blog we explore what they are and why you need them and clear up any confusion about these similar sounding terms. Read more: https://lnkd.in/erDysWNT #DBmarlin #ApplicationPerformance #Database

Understanding How Columnar Data Improves I/O Performance in Analytical Queries To grasp how columnar data enhances I/O performance in analytical queries, it's essential to first understand how databases are traditionally stored and retrieved from disk. This foundation helps clarify the key differences in storage methods and what specific issues columnar databases address. This article covers the following topics: - The structure of disks and how tables are stored on them - An example of read and write operations in a traditional database - The implications of traditional row-based storage - How columnar databases differ and the problems they solve - Common use cases for columnar databases references: 1. https://lnkd.in/dyw8eJ2e 2. https://lnkd.in/dKQTiXrg 3. https://lnkd.in/dFpwp6bM

Blog: Data observability vs Database observability 🔍 In this blog we explore what they are and why you need them and clear up any confusion about these similar sounding terms. Read more: https://lnkd.in/erDysWNT #DBmarlin #ApplicationPerformance #Database #Blog

There are 4 ways you can approach data isolation in Modular Monoliths: 1) Separate table 2) Separate schema 3) Separate database 4) Different persistence Data isolation ensures that modules are independent and loosely coupled. A modular monolith has strict rules for data integrity: - Each module can only access its own tables - No sharing of tables or objects between modules - Joins are only allowed between tables of the same module Do you want to learn more about Modular Monoliths? You can start here: https://lnkd.in/enZ54BuZ

New Article 📢 Has someone told you that adding indexes, especially nonclustered ones, makes deletes take longer? As with most things in life, the dose makes the poison. 💀 My latest article shows how helpful indexes are when deleting data. Indexes cause a huge impact when deleting larger amounts of data. This impact can mean the difference between exclusive object-level locks held for minutes versus seconds. ⌚ 👉Add Indexes to Improve SQL DELETE Performance 🔗https://lnkd.in/gEDxakWS Please let me know your experiences in the comment below. 👇 #sqlserver #mssql #mssqlserver #sql Jeremy Kadlec

The QuickScan Touch Plus includes a more powerful SQL database format and optional server for enhanced data management. Data from multiple Helena systems, including gel and CE, can be electronically paired for interpreting, reviewing and tracking of results. Historic data from competitive systems can be imported. https://lnkd.in/gmupvudp

TUESDAY MOTIVATION Did you know that using indexes can significantly speed up your query performance? Indexes help databases quickly locate specific data, making your queries faster and more efficient. Take your data analysis to the next level and optimize your queries with indexes! #SQL #DataAnalysis #DatabaseManagement #ProductivityHacks

Quick Tip for Data Analysts: When working with large datasets in SQL, using INDEX on frequently queried columns can significantly improve query performance. Optimizing your database can cut down response times and make your analytics more efficient. What indexing techniques do you use? #SQL #DataOptimization #DataAnalytics