Snowflake

AUGUST 21, 2023

In this blog post, we’ll review the core data mesh principles, highlight how both organizations and modern data platforms are putting those principles into action, and demonstrate just how achievable a secure and efficient data mesh architecture can be. How, then, are modern data teams finding success with the data mesh?

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Pipeline-centric Architecture Government Data Architect 52

Knowledge Hut

JANUARY 30, 2024

Log Data: Extracting log files from systems or applications is crucial for monitoring, troubleshooting, and security analysis. Log data can reveal system performance, user activity, and potential issues. Customer Interaction Data: In customer-centric industries, extracting data from customer interactions (e.g.,

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ETL Tools Database-centric Data Mining Data Cleanse 52

Knowledge Hut

JULY 3, 2023

This process consists of feeding data from various sources and building it to be available for analysis, storage, or next processing. Real-time ingestion is crucial in various industries like finance, e-commerce, logistics, and healthcare. To achieve this goal, pursuing Data Engineer certification can be highly beneficial.

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Data Ingestion Pipeline-centric Google Cloud Media 52

Ascend.io

MAY 7, 2024

to bring its cutting-edge automation platform that revolutionizes modern data engineering. .” This partnership establishes a data efficiency center of excellence focused on AI & Automation tooling alongside best practices to ensure organizations maximize their data ROI. . “Our collaboration with Ascend.io

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Databand.ai

DECEMBER 29, 2022

Follow Ravit on LinkedIn 5) Priya Krishnan Head of Product Management, Data and AI at IBM Priya is an innovative, customer-focused, data-driven product executive with over 16 years of experience in global product management, strategy, and GTM roles to commercialize and monetize in-demand enterprise solutions.

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BI Consulting Data Science Data Governance 52

Databand.ai

DECEMBER 20, 2022

Follow Eric on LinkedIn 10) Brian Femiano Senior Data Engineer at Apple Brian is a senior data engineer with nearly two decades of experience at companies like Booz Allen Hamilton, Magnetic, Pandora, and, most recently, Apple. Wannes is skilled in R, Python, data analysis, and data mining and regularly writes and speaks at events.

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Data Analytics Google Cloud Data Science Data Mining 52

Monte Carlo

JULY 15, 2021

As data pipelines become increasingly complex, investing in a data quality solution is becoming an increasingly important priority for modern data teams. There are 4 key challenges, opportunities, and trade-offs when considering building or buying a data observability or data quality solution.

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