Fast Track to Efficient Data Retrieval: Mastering Key Strategies in Software Engineering
Tags: database, systemdesign, softwareengineering, webdev
Published: 2024-01-13 07:52:46

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title: Fast Track to Efficient Data Retrieval: Mastering Key Strategies in Software Engineering
published: true
tags: database,systemdesign,softwareengineering,webdev
description: "Photo by Microsoft Bing Chat"
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Data retrieval is a crucial step in software engineering. The speed at which we can access data significantly impacts the quality of our product. In today's fast-paced world, even a millisecond optimization in data retrieval can lead to substantial cost savings. Let's explore some commonly used techniques to optimize data retrieval.

### Indexing
Indexing is a fundamental technique in which we create indexes on frequently used columns. The index kind of acts as a pathway that improves query retrieval speed at the cost of write time. We can create a composite index if there are multiple columns for indexes. We should carefully analyze the query and usage pattern and decide on our indexes to improve the overall data retrieval time. We should also not blindly use any index because creating indexes increases write query time, so we should carefully select the indexes.

### Denormalization
While creating a database schema, we are often advised to normalize our data. However, excessive normalization can sometimes impact our data retrieval time. The process of removing normalization and introducing redundancy in the database schema for faster retrieval is called denormalization. Denormalization reduces the number of joins in our queries, which significantly improves data retrieval time. Like any technique, it has its drawbacks. Denormalization can complicate updates and introduce data inconsistency. It's crucial to carefully assess the specific needs of your application before opting for denormalization.

### Table View
Sometimes, we can't denormalize our database for various reasons, and the increasing number of joins is affecting our read time. In such cases, creating a view table for a specific query can be a solution. A view table is more like a temporary table that stores the data of the query. When retrieving data, we can directly use that view table, significantly improving read time compared to the query itself. Creating views for complex queries can be beneficial, especially when dealing with frequently used or intricate query patterns. Views encapsulate complex logic, making querying more straightforward for application developers. If we are using the view mechanism, it's crucial to update the view table regularly. If the view is not updated, users will see only old data, potentially impacting the business more than a delay in the query.



The above techniques are not the only ones that can improve data retrieval. There are several additional strategies such as caching, database sharding, and more, each with its own merits and applications. In future articles, we will explore these techniques to provide you with a comprehensive understanding of optimizing data retrieval. Feel free to ask any question you have!!!