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Introduction to SQL for Data Science

SQL(Structured Query Language) is a powerful tool that enables data science professionals to interact with and retrieve structured data from relational databases. As such, it is an essential tool for data scientists. To work with and analyze datasets effectively, data scientists must master RDBMS, data cleaning processes, and SQL commands.

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Introduction to Databases for Data Science

In data science, databases play a crucial role in storing, managing, and scaling large amounts of data. This data is then analyzed to gain meaningful insights. In this blog, we will delve into the concept of databases and understand how data science relies on them, as well as their advantages.

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Introduction to Graph Database in System Design

In system design, graph databases help us to efficiently traverse complex hierarchies, identify hidden connections, and uncover inter-relationships between elements. That’s why they are used in various applications, where things are interconnected.

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Caching in System Design

Caching is the process of storing the results of a request in a cache or a temporary storage location so they can be accessed more quickly. In system design, a cache is a high-speed data storage that stores a subset of data so that future requests for that data are served up faster. In other words, caching allows us to reuse previously retrieved data efficiently.

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Key Value Database in System Design

A key value database is a non relational database (NoSQL) that stores data using a simple key-value mechanism. The structure of key value store is similar to maps or dictionaries, where each key is associated with one value only. The simplicity of this model makes key-value databases fast, easy to use, scalable, portable, and flexible.

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How to Choose the Right Database?

Have you ever been in a dilemma while choosing the most appropriate database for your application? What could be the most viable storage type that could meet the business expectations and offer efficient services? For selecting the database, we should have an understanding of the structure and the functionalities of each kind of database.

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CAP Theorem in System Design

CAP Theorem is an essential concept in system design for designing networked shared data systems. It states that a distributed database system can only provide two of these three properties : consistency, availability, and partition tolerance. We can make trade-offs between three available properties based on use cases for our dbms system.

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SQL vs NoSQL Database

Databases are a critical component of the most complex systems, and how they are used has a significant impact on their performance, scalability, and consistency. Because this is an essential topic with many components, we have outlined the most crucial database topics that you’ll need to know during a system design interview.

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