DataKitchen

NOVEMBER 18, 2022

Question: What is the difference between Data Quality and Observability in DataOps? Data Quality is static. It is the measure of data sets at any point in time. A financial analogy: Data Quality is your Balance Sheet, Data Observability is your Cash Flow Statement.

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AWS Big Data

JUNE 6, 2023

AWS Glue Data Quality allows you to measure and monitor the quality of data in your data repositories. It’s important for business users to be able to see quality scores and metrics to make confident business decisions and debug data quality issues. An AWS Glue crawler crawls the results.

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AWS Big Data

JUNE 6, 2023

Alerts and notifications play a crucial role in maintaining data quality because they facilitate prompt and efficient responses to any data quality issues that may arise within a dataset. This proactive approach helps mitigate the risk of making decisions based on inaccurate information.

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Dataiku

AUGUST 15, 2023

Let's face the reality: Data quality , despite its paramount importance, is often unloved and undervalued in many organizations. It is seen as excessively technical, demands a great deal of tedious effort and time to manage and, ultimately, leads to a lack of enthusiasm for taking up this crucial responsibility.

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IBM Big Data Hub

JULY 13, 2023

When we talk about data integrity, we’re referring to the overarching completeness, accuracy, consistency, accessibility, and security of an organization’s data. Together, these factors determine the reliability of the organization’s data. Data quality Data quality is essentially the measure of data integrity.

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TDAN

MAY 4, 2022

Getting to great data quality need not be a blood sport! This article aims to provide some practical insights gained from enterprise master data quality projects undertaken within the past […].

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KDnuggets

JANUARY 12, 2023

Bad data costs organizations money, reputation, and time. Hence it is very important to monitor and validate data quality continuously.

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DataKitchen

JANUARY 4, 2023

Why do 78% of data engineers wish their job came with a therapist to help manage work-related stress? The post ON-DEMAND WEBINAR: Managing Stress in Data Engineering: Data Quality and Testing Techniques for Data Observability first appeared on DataKitchen. THEY DO NOT TEST.

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Alation

MAY 24, 2022

generally available on May 24, Alation introduces the Open Data Quality Initiative for the modern data stack, giving customers the freedom to choose the data quality vendor that’s best for them with the added confidence that those tools will integrate seamlessly with Alation’s Data Catalog and Data Governance application.

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TDAN

MARCH 15, 2022

1 In this article, I will apply it to the topic of data quality. I will do so by comparing two butterflies, each that represent a common use of data quality: firstly and most commonly in situ for existing systems, and secondly for use […]. We know the phrase, “Beauty is in the eye of the beholder.”1

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KDnuggets

OCTOBER 6, 2022

Join Lior Gavish, co-author and Monte Carlo co-founder, Oct 12 @ 1 PM ET, as he explores the latest in data quality techniques with a panel of some of the foremost experts.

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IBM Big Data Hub

JANUARY 5, 2023

Poor data quality is one of the top barriers faced by organizations aspiring to be more data-driven. Ill-timed business decisions and misinformed business processes, missed revenue opportunities, failed business initiatives and complex data systems can all stem from data quality issues.

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Corinium

JANUARY 21, 2020

We are pleased to be working with our media partner, IQ International on our Chief Data & Analytics Officer Brisbane event, where they will be sharing some of their work in developing best practice data quality metrics for every industry. We will be joined by Dan Myers (USA), President at IQ International.

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KDnuggets

NOVEMBER 22, 2022

Ensuring data quality guarantees more data-informed decisions. Hence, this article highlights the common data quality issues and ways to overcome them.

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AWS Big Data

JUNE 6, 2023

Data consumers lose trust in data if it isn’t accurate and recent, making data quality essential for undertaking optimal and correct decisions. Evaluation of the accuracy and freshness of data is a common task for engineers. Currently, various tools are available to evaluate data quality.

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KDnuggets

JANUARY 17, 2022

Incorrect or unclean data leads to false conclusions. The time you take to understand and clean the data is vital to the outcome and quality of the results. Data Quality always takes the win against complex fancy algorithms.

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Corinium

JANUARY 13, 2020

In the last decade regulatory requirements in financial services increased significantly.

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Dataiku

APRIL 19, 2021

In a recent Egg On Air Episode , Jeff McMillan, Chief Analytics and Data Officer for Morgan Stanley Wealth Management, outlined the significance of data quality to an organization’s success and offered some insight on how Morgan Stanley approaches data quality.

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KDnuggets

MARCH 23, 2023

This article highlights the significance of ensuring high-quality data and presents six key dimensions for measuring it. These dimensions include Completeness, Consistency, Integrity, Timelessness, Uniqueness, and Validity.

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TDAN

OCTOBER 18, 2022

Last week, we presented a webinar in our Data Governance — Best Practices series on data quality. Obviously, we’re a […].

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Smart Data Collective

APRIL 20, 2022

Companies with an in-depth understanding of data analytics will have more successful Amazon PPC marketing strategies. However, it is important to make sure the data is reliable. However, data quality is again going to be very important. You must make sure the right sales page versions are stored in your database.

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IBM Big Data Hub

AUGUST 2, 2023

However, analytics are only as good as the quality of the data, which aims to be error-free, trustworthy, and transparent. According to a Gartner report , poor data quality costs organizations an average of USD $12.9 What is data quality? Data quality is critical for data governance.

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AWS Big Data

JUNE 6, 2023

Poor-quality data can lead to incorrect insights, bad decisions, and lost opportunities. AWS Glue Data Quality measures and monitors the quality of your dataset. It supports both data quality at rest and data quality in AWS Glue extract, transform, and load (ETL) pipelines.

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IBM Big Data Hub

JUNE 12, 2023

Companies rely heavily on data and analytics to find and retain talent, drive engagement, improve productivity and more across enterprise talent management. However, analytics are only as good as the quality of the data, which must be error-free, trustworthy and transparent. What is data quality? million each year.

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Corinium

FEBRUARY 3, 2020

Using data to inform business decisions only works when the data is correct. Unfortunately for the insurance industry’s data leaders, many data sources are riddled with inaccuracies. Data is the lifeblood of the insurance industry.

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Dataiku

SEPTEMBER 13, 2023

In this blog , David Talaga (Product Marketing at Dataiku) explains that shopping in a supermarket could be similar to searching for the best data product for your use case. As a data analyst, the same mechanism applies to the data products you are looking for: Can I trust it?

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Dataiku

SEPTEMBER 28, 2021

Today, more than 90% of AI practitioners experience significant cascading data errors , and poor data quality is estimated to cost companies 20% of revenue. The bottom line: bad data is ubiquitous and costly, and it also reduces organizations’ overall AI productivity.

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Smart Data Collective

SEPTEMBER 29, 2022

The post Data-Driven Companies Leverage OCR for Optimal Data Quality appeared first on SmartData Collective. No more wasted time, employee frustration, or manual input errors: OCR is the solution you need to better process and manage your documents.

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Alation

MAY 24, 2022

In a sea of questionable data, how do you know what to trust? Data quality tells you the answer. It signals what data is trustworthy, reliable, and safe to use. It empowers engineers to oversee data pipelines that deliver trusted data to the wider organization. Today, as part of its 2022.2

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Octopai

JULY 11, 2022

And when business users don’t complain, but you know the data isn’t good enough to make these types of calls wisely, that’s an even bigger problem. How are you, as a data quality evangelist (if you’re reading this post, that must describe you at least somewhat, right?), Tie data quality directly to business objectives.

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