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Complete Guide to Data Ingestion: Types, Process, and Best Practices

Databand.ai

Complete Guide to Data Ingestion: Types, Process, and Best Practices Helen Soloveichik July 19, 2023 What Is Data Ingestion? Data Ingestion is the process of obtaining, importing, and processing data for later use or storage in a database. In this article: Why Is Data Ingestion Important?

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What is Real-time Data Ingestion? Use cases, Tools, Infrastructure

Knowledge Hut

This is where real-time data ingestion comes into the picture. Data is collected from various sources such as social media feeds, website interactions, log files and processing. This refers to Real-time data ingestion. To achieve this goal, pursuing Data Engineer certification can be highly beneficial.

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DataOps Architecture: 5 Key Components and How to Get Started

Databand.ai

DataOps is a collaborative approach to data management that combines the agility of DevOps with the power of data analytics. It aims to streamline data ingestion, processing, and analytics by automating and integrating various data workflows.

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Data Engineering Weekly #163

Data Engineering Weekly

The author explores the evolving landscape of data product standards, highlighting the necessity for unified standards to ensure interoperability and manage the data economy effectively. It discusses the significance of data governance, sharing history, and generative AI's impact on data economy standards.

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Data Warehouse vs Big Data

Knowledge Hut

It encompasses data from diverse sources such as social media, sensors, logs, and multimedia content. The key characteristics of big data are commonly described as the three V's: volume (large datasets), velocity (high-speed data ingestion), and variety (data in different formats).

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New Snowflake Features Released in February 2023

Snowflake

In February, Snowflake launched new features around streaming data ingestion and data governance and improved SQL experience and performance, with enhancements to Search Optimization Service and more. Check out Felipe Hoffa’s video on how to use Snowsight to get from data to decision faster.

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The Data Integration Solution Checklist: Top 10 Considerations

Precisely

A true enterprise-grade integration solution calls for source and target connectors that can accommodate: VSAM files COBOL copybooks open standards like JSON modern platforms like Amazon Web Services ( AWS ), Confluent , Databricks , or Snowflake Questions to ask each vendor: Which enterprise data sources and targets do you support?