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Financial Data Engineering in SAS

DZone

Financial data engineering in SAS involves the management, processing, and analysis of financial data using the various tools and techniques provided by the SAS software suite. Here are some key aspects of financial data engineering in SAS: 1.

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Data Engineers of Netflix?—?Interview with Kevin Wylie

The Netflix TechBlog

Data Engineers of Netflix?—?Interview Interview with Kevin Wylie This post is part of our “Data Engineers of Netflix” series, where our very own data engineers talk about their journeys to Data Engineering @ Netflix. Kevin, what drew you to data engineering?

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Leveraging Infrastructure as Code for Data Engineering Projects: A Comprehensive Guide

DZone

Data engineering projects often require the setup and management of complex infrastructures that support data processing, storage, and analysis. In this article, we will explore the benefits of leveraging IaC for data engineering projects and provide detailed implementation steps to get started.

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Presentation: LIquid: A Large-Scale Relational Graph Database

InfoQ

Scott Meyer discusses LIquid, the graph database built to host LinkedIn, serving a ~15Tb graph at ~2M QPS. By Scott Meyer

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Presentation: Why a Hedge Fund Built Its Own Database

InfoQ

James Munro discusses ArcticDB and the practicalities of building a performant time-series datastore and why transactions, particularly the Isolation in ACID is just not worth it. By James Munro

Database 110
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SQL Extensions for Time-Series Data in QuestDB

DZone

Using some sample data sets, you will learn how designated timestamps work and how to use extended SQL syntax to write queries on time-series data. Introduction Traditionally, SQL has been used for relational databases and data warehouses.

IoT 176
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Zendesk Moves from DynamoDB to MySQL and S3 to Save over 80% in Costs

InfoQ

Zendesk reduced its data storage costs by over 80% by migrating from DynamoDB to a tiered storage solution using MySQL and S3. The company considered different storage technologies and decided to combine the relational database and the object store to strike a balance between querybility and scalability while keeping the costs down.

Storage 136