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5 Helpful Extract & Load Practices for High-Quality Raw Data

Meltano

Setting the Stage: We need E&L practices, because “copying raw data” is more complex than it sounds. For instance, how would you know which orders got “canceled”, an operation that usually takes place in the same data record and just “modifies” it in place. But not at the ingestion level.

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Data Preparation and Raw Data in Machine Learning

KDnuggets

In this article, I will describe the data preparation techniques for machine learning.

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Why SQL on Raw Data?

Rockset

With an abundance of inexpensive storage, we can afford to build new types of indexes that allow us to ingest raw data in multiple formats. Fortunately, storage and compute substrates are changing quickly, leading to new opportunities in the form of optimized schemaless SQL processing systems. Specifically: Storage.

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Enable stakeholder data access with Text-to-SQL RAGs

Start Data Engineering

Enabling Stakeholder data access with RAGs 3.1. Loading: Read raw data and convert them into LlamaIndex data structures 3.2.1. Read data from structured and unstructured sources 3.2.2. Transform data into LlamaIndex data structures 3.3. Introduction 2. Set up 3.1.1. Pre-requisite 3.1.2. Demo 3.1.3.

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Using Data & Analytics for Improving Healthcare Innovation and Outcomes

Our platform empowers you to seamlessly integrate advanced data analytics, generative AI, data visualization, and pixel-perfect reporting into your applications, transforming raw data into actionable insights. With Logi Symphony, you’re not just overcoming obstacles, you’re driving innovation in healthcare.

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From Schemaless Ingest to Smart Schema: Enabling SQL on Raw Data

Rockset

The application you're implementing needs to analyze this data, combining it with other datasets, to return live metrics and recommended actions. But how can you interrogate the data and frame your questions correctly if you don't understand the shape of your data? This enables Rockset to generate a Smart Schema on the data.

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The Journey of a Senior Data Scientist and Machine Learning Engineer at Spice Money

Analytics Vidhya

Introduction Meet Tajinder, a seasoned Senior Data Scientist and ML Engineer who has excelled in the rapidly evolving field of data science. Tajinder’s passion for unraveling hidden patterns in complex datasets has driven impactful outcomes, transforming raw data into actionable intelligence.

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Provide Real Value in Your Applications with Data and Analytics

Our platform empowers you to seamlessly integrate advanced data analytics, generative AI, data visualization, and pixel-perfect reporting into your applications, transforming raw data into actionable insights. Together, we can overcome these hurdles and empower your users with the data they need to drive success.