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.

Data Quality 74

Data Quality Metrics Visualization Dashboards 74

AWS Big Data

JUNE 6, 2023

We are excited to announce the General Availability of AWS Glue Data Quality. Our journey started by working backward from our customers who create, manage, and operate data lakes and data warehouses for analytics and machine learning. It takes days for data engineers to identify and implement data quality rules.

Data Quality 96

Data Quality Statistics Data Lake Visualization 96

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.

Data Quality 99

Data Quality Measurement IT 99

CIO Business Intelligence

MAY 23, 2024

There’s been good progress but, admittedly, there’s still a lot of work to do, says Nilsson, since it’s difficult to take ownership in a large organization and streamline data management. In the long run, we envisage new services such as being able to handle predictive maintenance based on what we know about the products,” he says.

Digital Transformation 93

Digital Transformation Measurement Cost-Benefit Data Warehouse 93

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.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

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.

Data Quality 79

Data Quality Strategy Business Objectives Sales 79

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.

Data Quality 78

Data Quality Data Lake Data-driven Metrics 78

Jim Harris

APRIL 20, 2021

OCDQ Radio is an audio podcast about data quality and its related disciplines, produced and hosted by Jim Harris. Why does no one care about poor data quality? tolerance for poor data quality). tolerance for poor data quality).

Data Quality 59

Data Quality Data Governance Data Processing Metrics 59

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.

Data Quality 66

Data Quality Data Governance People Analytics Data-driven 66

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.

Data Quality 63

Data Quality Snapshot Data Governance Data-driven 63

Alation

JANUARY 20, 2022

Several weeks ago (prior to the Omicron wave), I got to attend my first conference in roughly two years: Dataversity’s Data Quality and Information Quality Conference. Ryan Doupe, Chief Data Officer of American Fidelity, held a thought-provoking session that resonated with me. Step 2: Data Definitions.

Data Quality 94

Data Quality Data Governance Metrics Statistics 94

Anmut

JULY 12, 2021

Data without context is just meaningless noise, and any effort to improve or extract value from your data without considering the larger business context is doomed to fall short.? Unfortunately, traditional approaches to data remediation often focus on technical data quality in isolation from the broader data and business ecosystem.

Data Quality 52

Data Quality Measurement Metrics Dashboards 52

The Unofficial Google Data Science Blog

JULY 18, 2023

E ven after we account for disagreement, human ratings may not measure exactly what we want to measure. How do we think about the quality of human ratings, and how do we quantify our understanding is the subject of this post. While human-labeled data is critical to many important applications, it also brings many challenges.

Measurement 52

Measurement Metrics Uncertainty Slice and Dice 52

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.

Data Quality 71

Data Quality Data Lake Visualization Data-driven 71

Anmut

MARCH 22, 2023

This ultimately allows for more effective goal-setting, with targets determined according to both your data maturity right now and the desired stage you want to attain in the future. Why do we need data maturity models? A data maturity model helps your company measure its data and business health.

Measurement 52

Measurement Modeling Data Quality Data Governance 52

Andrew White

AUGUST 26, 2020

I spoke to a client recently who had this question: “I need help to develop a survey to ask our employees around the company how they regard the various subjective metrics tied to data quality.” I went on: What if the subjective measures all get scored or rated at 100%? What was the point of the data quality work?

Data Quality 52

Data Quality Data Governance Metrics Measurement 52

KDnuggets

SEPTEMBER 24, 2019

Of all data quality characteristics, we consider consistency and accuracy to be the most difficult ones to measure. Here, we describe the challenges that you may encounter and the ways to overcome them.

Data Quality 72

Data Quality Measurement 72

DataKitchen

MAY 10, 2024

The Second of Five Use Cases in Data Observability Data Evaluation: This involves evaluating and cleansing new datasets before being added to production. This process is critical as it ensures data quality from the onset. Examples include regular loading of CRM data and anomaly detection.

Data Quality 130

Data Quality Testing Software Dashboards 130

Ontotext

MAY 26, 2021

Originally, the Gold Standard was a monetary system that required countries to fix the value of their currencies to a certain amount of gold, aiming to replace the unreliable human control with a fixed measurement that could be used by everyone. Simply put, we need to be able to measure and evaluate our results against clearly set criteria.

Data Quality 87

Data Quality Machine Learning Measurement Metadata 87

DataKitchen

MARCH 5, 2024

Stakeholders, from internal teams to external clients, seek confidence in the data they use and depend on. This confidence can only be built through transparency, proactive error detection, and a robust data quality and observability framework. It’s just a matter of time.

Data Quality 146

Data Quality Measurement Testing Data-driven 146

Jim Harris

DECEMBER 24, 2015

Have you ever experienced that sinking feeling, where you sense if you don’t find data quality, then data quality will find you? These discussions are a critical prerequisite for determining data usage, standards, and the business relevant metrics for measuring and improving data quality.

Data Quality 56

Data Quality Enterprise Business Intelligence Data Governance 56

DataKitchen

FEBRUARY 27, 2024

Your LLM Needs a Data Journey: A Comprehensive Guide for Data Engineers The rise of Large Language Models (LLMs) such as GPT-4 marks a transformative era in artificial intelligence, heralding new possibilities and challenges in equal measure.

Data Quality 117

Data Quality Unstructured Data Testing Modeling 117

TDAN

JANUARY 18, 2022

Data Accuracy is one of the so-called “dimensions” of Data Quality. The goal for these dimensions, and it is a noble one, is so we can measure each of them, and should deficiencies be found then there should be a uniform set of best practices that we can implement.

Data Quality 98

Data Quality Measurement IT Data Strategy 98

DataKitchen

MARCH 12, 2024

I used to be very, very careful when changing anything data-related, but I think you’re starting to see that it’s not that big a deal anymore because [if something goes wrong] we can now figure out what happened pretty quickly, and we can adjust it.“ Global Pharma Company Related Benefits Improve time to remediation.

Metrics 117

Metrics Software Cost-Benefit Testing 117

DataKitchen

MARCH 16, 2023

How to measure your data analytics team? So it’s Monday, and you lead a data analytics team of perhaps 30 people. Like most leaders of data analytic teams, you have been doing very little to quantify your team’s success. The Active Data Ratio metric determines the percentage of datasets that deliver value.

Metrics 130

Metrics Data Analytics Analytics Measurement 130

erwin

APRIL 16, 2024

In this blog, we’ll delve into the critical role of governance and data modeling tools in supporting a seamless data mesh implementation and explore how erwin tools can be used in that role. erwin also provides data governance, metadata management and data lineage software called erwin Data Intelligence by Quest.

Metadata 52

Metadata Data Quality Data Governance Modeling 52

CIO Business Intelligence

JANUARY 23, 2024

Regardless of where organizations are in their digital transformation, CIOs must provide their board of directors, executive committees, and employees definitions of successful outcomes and measurable key performance indicators (KPIs). He suggests, “Choose what you measure carefully to achieve the desired results.

Measurement 135

Measurement Digital Transformation KPI Metrics 135

InsightOut

FEBRUARY 16, 2024

In today's data-driven world, mid-sized companies are increasingly recognizing the pivotal role that clean, accurate, and organized data plays in driving strategic decisions, enhancing operational efficiency, and fostering growth. This bespoke approach ensures that every company maximizes the value of its data.

Data Quality 52

Data Quality Data-driven Data Governance Measurement 52

InsightOut

FEBRUARY 16, 2024

In today's data-driven world, mid-sized companies are increasingly recognizing the pivotal role that clean, accurate, and organized data plays in driving strategic decisions, enhancing operational efficiency, and fostering growth. This bespoke approach ensures that every company maximizes the value of its data.

Data Quality 52

Data Quality Data-driven Data Governance Measurement 52

CIO Business Intelligence

MAY 8, 2024

According to a recent report by InformationWeek , enterprises with a strong AI strategy are 3 times more likely to report above-average data integration success. Additionally, a study by McKinsey found that organisations leveraging AI in data integration can achieve an average improvement of 20% in data quality.

Data Integration 79

Data Integration IoT Cost-Benefit Data Quality 79

datapine

JANUARY 24, 2021

This can include a multitude of processes, like data profiling, data quality management, or data cleaning, but we will focus on tips and questions to ask when analyzing data to gain the most cost-effective solution for an effective business strategy. 3) Where will your data come from?

IT 317

IT Statistics KPI Data-driven 317

O'Reilly on Data

JULY 28, 2020

These measures are commonly referred to as guardrail metrics , and they ensure that the product analytics aren’t giving decision-makers the wrong signal about what’s actually important to the business. When a measure becomes a target, it ceases to be a good measure ( Goodhart’s Law ). Data Wrangling and Feature Engineering.

Marketing 361

Marketing Experimentation Metrics Testing 361

CIO Business Intelligence

JUNE 9, 2023

A few years ago, Gartner found that “organizations estimate the average cost of poor data quality at $12.8 million per year.’” Beyond lost revenue, data quality issues can also result in wasted resources and a damaged reputation. Without it, organizations incur a significant opportunity cost.

Strategy 112

Strategy Management Key Performance Indicator ROI 112

Smart Data Collective

APRIL 5, 2022

While drones are valued for the images and video footage they collect, they are increasingly able to store other types of information, including radio signals, soil moisture, factory emissions, and geodetic data, which includes precision measurements for land surveys.” Do an Overcast Survey to Ensure You Get Reliable Data.

Data Collection 107

Data Collection Data Quality Big Data Data-driven 107

AWS Big Data

FEBRUARY 29, 2024

Implement data privacy policies. Implement data quality by data type and source. Let’s look at some of the key changes in the data pipelines namely, data cataloging, data quality, and vector embedding security in more detail. Link structured and unstructured datasets.

Data Governance 98

Data Governance Unstructured Data Metadata Data Lake 98

IBM Big Data Hub

FEBRUARY 9, 2023

Technology and data architecture play a crucial role in enabling data governance and achieving these objectives. Focus and prioritize what you’re delivering to the business, determine what you need, deliver and measure results, refine, expand, and deliver against the next priority objectives. Don’t try to do everything at once!

Data Governance 80

Data Governance Business Objectives Strategy Data Quality 80

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.

Data Quality 66

Data Quality Data Integration Metadata Cost-Benefit 66