Remove Data Architecture Remove Data Pipeline Remove Data Warehouse Remove High Quality Data
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How HomeToGo Is Building a Robust Clickstream Data Architecture with Snowflake, Snowplow and dbt

Snowflake

Over the course of this journey, HomeToGo’s data needs have evolved considerably. It also came with other advantages such as independence of cloud infrastructure providers, data recovery features such as Time Travel , and zero copy cloning which made setting up several environments — such as dev, stage or production — way more efficient.

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[O’Reilly Book] Chapter 1: Why Data Quality Deserves Attention Now

Monte Carlo

As the data analyst or engineer responsible for managing this data and making it usable, accessible, and trustworthy, rarely a day goes by without having to field some request from your stakeholders. But what happens when the data is wrong? In our opinion, data quality frequently gets a bad rep.

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The Symbiotic Relationship Between AI and Data Engineering

Ascend.io

While data engineering and Artificial Intelligence (AI) may seem like distinct fields at first glance, their symbiosis is undeniable. The foundation of any AI system is high-quality data. Here lies the critical role of data engineering: preparing and managing data to feed AI models.

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Data Quality Engineer: Skills, Salary, & Tools Required

Monte Carlo

These specialists are also commonly referred to as data reliability engineers. To be successful in their role, data quality engineers will need to gather data quality requirements (mentioned in 65% of job postings) from relevant stakeholders.

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Centralize Your Data Processes With a DataOps Process Hub

DataKitchen

Data organizations often have a mix of centralized and decentralized activity. DataOps concerns itself with the complex flow of data across teams, data centers and organizational boundaries. It expands beyond tools and data architecture and views the data organization from the perspective of its processes and workflows.

Process 98
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Celebrating the New Pioneers of Data Reliability

Monte Carlo

Data informs every business decision, from customer support to feature development, and most recently, how to support pricing plans for organizations most affected during COVID-19. When migrating to Snowflake, PagerDuty wanted to understand the health of their data pipelines through fully automated data observability.

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DataOps For Business Analytics Teams

DataKitchen

They need high-quality data in an answer-ready format to address many scenarios with minimal keyboarding. What they are getting from IT and other data sources is, in reality, poor-quality data in a format that requires manual customization. DataOps Process Hub.