1 - Indexing:
Check the query patterns of your application and create the right indexes.
2 - Materialized Views:
Pre-compute complex query results and store them for faster access.
3 - Denormalization:
Reduce complex joins to improve query performance.
4 - Vertical Scaling
Boost your database server by adding more CPU, RAM, or storage.
5 - Caching
Store frequently accessed data in a faster storage layer to reduce database load.
6 - Replication
Create replicas of your primary database on different servers for scaling the reads.
7 - Sharding
Split your database tables into smaller pieces and spread them across servers. Used for scaling the writes as well as the reads.
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🔅 Learning Data Science
🌐 Author: Doug Rose
🔰 Level: Intermediate
⏰ Duration: 2h 45m
📗 Topics: Data Visualization, Data Literacy, Big Data Analytics
📤 Join Data Analysis for more courses
🌀 Get an introduction to data science in this course designed for aspiring professionals in project management and leadership.
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Many people who work on data science teams will become something other than data scientists. That said, many will become managers and associates who want to gain real business value from your organization's data. These team members need to understand the language of data science so they can ask better questions, understand processes, and help effectively lead their teams and organizations to making better data-driven decisions. In this course, get an introduction to data science for people who aren't planning on working as full-time data scientists. Explore big data concepts, tools, and techniques, including gathering and sorting data, working with databases, understanding structured and unstructured data types, applying statistical analysis, asking critical questions, and telling stories about data. Business coach and author Doug Rose helps you speak the language of data science so that you can guide your organization through the opportunities and limitations in this dramatically growing field.
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