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Top 10 MongoDB Career Options in 2024 [Job Opportunities]

Knowledge Hut

Versatility: The versatile nature of MongoDB enables it to easily deal with a broad spectrum of data types , structured and unstructured, and therefore, it is perfect for modern applications that need flexible data schemas. Good Hold on MongoDB and data modeling. Experience with ETL tools and data integration techniques.

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Comparing Performance of Big Data File Formats: A Practical Guide

Towards Data Science

Parquet vs ORC vs Avro vs Delta Lake Photo by Viktor Talashuk on Unsplash The big data world is full of various storage systems, heavily influenced by different file formats. These are key in nearly all data pipelines, allowing for efficient data storage and easier querying and information extraction.

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Introduction to MongoDB for Data Science

Knowledge Hut

The need for efficient and agile data management products is higher than ever before, given the ongoing landscape of data science changes. MongoDB is a NoSQL database that’s been making rounds in the data science community. Why Use MongoDB for Data Science? Quickly pull (fetch), filter, and reduce data.

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Data Mesh Architecture: Revolutionizing Event Streaming with Striim

Striim

This allows for two-way integration so that information can flow from one system to another in real-time. Striim is a cloud-native Data Mesh platform that offers features such as automated data mapping, real-time data integration, streaming analytics, and more.

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The Pros and Cons of Leading Data Management and Storage Solutions

The Modern Data Company

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing.

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The Pros and Cons of Leading Data Management and Storage Solutions

The Modern Data Company

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing.

article thumbnail

The Pros and Cons of Leading Data Management and Storage Solutions

The Modern Data Company

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing.