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6 Pillars of Data Quality and How to Improve Your Data

Databand.ai

Data quality refers to the degree of accuracy, consistency, completeness, reliability, and relevance of the data collected, stored, and used within an organization or a specific context. High-quality data is essential for making well-informed decisions, performing accurate analyses, and developing effective strategies.

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Data Engineering Weekly #161

Data Engineering Weekly

Here is the agenda, 1) Data Application Lifecycle Management - Harish Kumar( Paypal) Hear from the team in PayPal on how they build the data product lifecycle management (DPLM) systems. Part 1: Why did we need to build our own SIEM?

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Building a Winning Data Quality Strategy: Step by Step

Databand.ai

This includes defining roles and responsibilities related to managing datasets and setting guidelines for metadata management. Benefits of a Data Quality Strategy Implementing a robust data quality strategy offers numerous benefits that directly impact your business’s bottom line and overall success.

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Unlocking the Power of Data: Key Aspects of Effective Data Products

The Modern Data Company

Data Products Data products encompass several key aspects that contribute to their effectiveness and value in addressing data challenges and delivering actionable insights. These aspects ensure that data products are well-designed, user-centric, and aligned with business goals.

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Designing A Non-Relational Database Engine

Data Engineering Podcast

In this episode Oren Eini, CEO and creator of RavenDB, explores the nuances of relational vs. non-relational engines, and the strategies for designing a non-relational database. Data lakes are notoriously complex. How have the evolution in data formats (e.g. Go to dataengineeringpodcast.com/dagster today to get started.

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Intrinsic Data Quality: 6 Essential Tactics Every Data Engineer Needs to Know

Monte Carlo

On the other hand, “Can the marketing team easily segment the customer data for targeted communications?” usability) would be about extrinsic data quality. In this article, we present six intrinsic data quality techniques that serve as both compass and map in the quest to refine the inner beauty of your data.

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Unlocking the Power of Data: Key Aspects of Effective Data Products

The Modern Data Company

Data Products Data products encompass several key aspects that contribute to their effectiveness and value in addressing data challenges and delivering actionable insights. These aspects ensure that data products are well-designed, user-centric, and aligned with business goals.