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.

Data Quality 71

Data Quality Metrics Data-driven Visualization 71

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.

Data Quality 195

Data Quality Metrics Analytics 195

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 92

Data Quality Statistics Data Lake Visualization 92

DataKitchen

MARCH 16, 2023

So it’s Monday, and you lead a data analytics team of perhaps 30 people. But wait, she asks you for your team metrics. Like most leaders of data analytic teams, you have been doing very little to quantify your team’s success. Where is your metrics report? What should be in that report about your data team?

Metrics 130

Metrics Data Analytics Analytics Measurement 130

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

AWS Big Data

OCTOBER 10, 2023

Due to the volume, velocity, and variety of data being ingested in data lakes, it can get challenging to develop and maintain policies and procedures to ensure data governance at scale for your data lake. Data confidentiality and data quality are the two essential themes for data governance.

Data Quality 87

Data Quality Data Governance Data Lake Testing 87

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

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

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

Data Quality 52

Data Quality Metadata Reporting Metrics 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 66

Data Quality Data Lake Visualization Data-driven 66

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

Andrew White

APRIL 5, 2019

An oft heard inquiry from clients is, “What is the right metric to use?” The context might be for: Defining data quality. Reporting the business impact of a data governance initiative. Monitoring the progress of a digital or data-driven transformation. Yet here we are, being asked by clients for the right metric.

Metrics 80

Metrics Key Performance Indicator KPI Marketing 80

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 noted: If these metrics were all at 100%, what happens to their importance if the outcome of the business fails?

Data Quality 52

Data Quality Data Governance Metrics Measurement 52

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 23, 2024

Webinar: Beyond Data Observability: Personalization DataKitchen DataOps Observability Problem Statement White Paper: ‘Taming Chaos’ Technical Product Overview Four-minute online demo Detailed Product: Documentation Webinar: Data Observability Demo Day DataKitchen DataOps TestGen Problem Statement White Paper: ‘Mystery Box Full Of Data Errors’ (..)

Testing 120

Testing Data-driven Metrics Data Quality 120

Octopai

OCTOBER 26, 2022

DataOps is an approach to best practices for data management that increases the quantity of data analytics products a data team can develop and deploy in a given time while drastically improving the level of data quality. SPC tests can do the same thing for the data flowing through your pipelines.

Data Quality 52

Data Quality Data Analytics Analytics Manufacturing 52

DataKitchen

NOVEMBER 10, 2023

Extrinsic Control Deficit: Many of these changes stem from tools and processes beyond the immediate control of the data team. Unregulated ETL/ELT Processes: The absence of stringent data quality tests in ETL (Extract, Transform, Load) or ELT (Extract, Load, Transform) processes further exacerbates the problem.

Data Quality 141

Data Quality Testing Data Lake Data Integration 141

O'Reilly on Data

JULY 28, 2020

The first step in building an AI solution is identifying the problem you want to solve, which includes defining the metrics that will demonstrate whether you’ve succeeded. It sounds simplistic to state that AI product managers should develop and ship products that improve metrics the business cares about. Agreeing on metrics.

Marketing 362

Marketing Experimentation Metrics Testing 362

CIO Business Intelligence

APRIL 25, 2024

Without automated evaluation, LinkedIn reports that “engineers are left eye-balling results and testing on a limited set of examples and having a more than a 1+ day delay to know metrics.” User experience When dealing with such a large member base, accuracy and relevancy metrics can “give a false sense of comfort,” Bottaro said.

IT 138

IT Experimentation Cost-Benefit Metrics 138

DataKitchen

JUNE 19, 2023

Another way to look at the five pillars is to see them in the context of a typical complex data estate. Monitoring is another pillar of Data Journeys, extending down the stack. Moreover, cost monitoring ensures that your data operations stay within budget and that resources are used efficiently. Donkey: Oh, they have layers.

Testing 130

Testing Cost-Benefit Metrics Data Quality 130

CIO Business Intelligence

MAY 2, 2023

But there are common pitfalls , such as selecting the wrong KPIs , monitoring too many metrics, or not addressing poor data quality. Consider how it looks to nontechnical executives when every digital transformation initiative has customized dashboards, different KPIs, and metrics with underlying data quality issues.

Digital Transformation 138

Digital Transformation IT Data-driven Metrics 138

CIO Business Intelligence

MARCH 15, 2024

Strategic data initiatives During Martell’s tenure, the CDAO created the foundation for AI-based defense systems, by establishing five strategic initiatives to enable AI use at the DOD in fiscal year 2023, according to the DOD.

Big Data 122

Big Data Metrics Data Quality Machine Learning 122

IBM Big Data Hub

NOVEMBER 29, 2023

It automatically identifies vulnerable individual data points and introduces “noise” to obscure their specific information. Although adding noise slightly reduces output accuracy (this is the “cost” of differential privacy), it does not compromise utility or data quality compared to traditional data masking techniques.

Metrics 86

Metrics Machine Learning Risk Statistics 86

Smart Data Collective

AUGUST 11, 2022

How Artificial Intelligence is Impacting Data Quality. Artificial intelligence has the potential to combat human error by taking up the tasking responsibilities associated with the analysis, drilling, and dissection of large volumes of data. Data quality is crucial in the age of artificial intelligence.

Data Quality 129

Data Quality Machine Learning Digital Transformation Big Data 129

CIO Business Intelligence

APRIL 8, 2024

Jamie Capel-Davies, head of science and technical for ITF, says metrics don’t mean much if you can’t communicate them effectively in time to make use of them. One of the key things we were looking at was what were the most important metrics and how can they be communicated effectively,” he says.

Analytics 104

Analytics Broadcasting Predictive Analytics Metrics 104

TDAN

JANUARY 17, 2024

Eric Siegel’s “The AI Playbook” serves as a crucial guide, offering important insights for data professionals and their internal customers on effectively leveraging AI within business operations.

Metrics 122

Metrics Data Quality IT Data Governance 122

DataKitchen

OCTOBER 2, 2023

Data Journeys track and monitor all levels of the data stack, from data to tools to code to tests across all critical dimensions. A Data Journey supplies real-time statuses and alerts on start times, processing durations, test results, and infrastructure events, among other metrics.

Data Quality 100

Data Quality Testing Uncertainty Data Enablement 100

Cloudera

DECEMBER 1, 2022

Data observability provides insight into the condition and evolution of the data resources from source through the delivery of the data products. Barr Moses of Monte Carlo presents it as a combination of data flow, data quality, data governance, and data lineage.

Metrics 80

Metrics Data Quality Data Lake Statistics 80

Juice Analytics

APRIL 6, 2021

At Juice, we are working everyday to create these habits and we wanted to share how we are building a data-first mindset and where we look for inspiration. Habit 1: Define shared metrics Data fluency requires getting everyone on the same page as to what matters most.

Metrics 119

Metrics Dashboards Data-driven Data Quality 119

Jen Stirrup

FEBRUARY 23, 2024

Data observability solutions empower organizations to gain clear visibility into their data pipelines, rising to meet the growing requirement that data is correct, timely, and dependable. Data observability includes several concepts, and here are some examples: Data Freshness : How up-to-date is the data?

Data-driven 73

Data-driven Data Governance Data Quality Cost-Benefit 73

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 91

Data Governance Unstructured Data Metadata Data Lake 91

Alation

FEBRUARY 14, 2023

From rebranding data governance in your organization to demonstrating real business impacts, there’s a lot you can do to bring everyone in your business on board. The role of monitoring, measuring, and metrics So, you’ve got the first step done; you’ve implemented data governance and everyone in your organization is on board.

Data Governance 52

Data Governance ROI Metrics Cost-Benefit 52

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.

Data Quality 98

Data Quality Data Governance Metadata Metrics 98

InsightOut

FEBRUARY 2, 2024

This is where InsightOut steps in, offering e-commerce companies the tools they need to clean, analyze, and report on key data metrics. Let's explore how InsightOut is leading the way and revolutionizing the way e-commerce businesses leverage data. Pristine Data Cleansing For e-commerce, data quality is non-negotiable.

Key Performance Indicator 40

Key Performance Indicator Metrics Dashboards Reporting 40

Alation

OCTOBER 5, 2021

These divergences of focus can lead to consumers feeling bogged down by overly complicated processes or leadership teams being unable to see initiative investments reap the desired rewards of their predictive business success metrics. (1). Incomplete data. Lack of commitment.

Data Governance 96

Data Governance Strategy Data Quality Metrics 96

Cloudera

MARCH 22, 2023

Cloudera Data Platform (CDP) is no different: it’s a hybrid data platform that meets organizations’ needs to get to grips with complex data anywhere, turning it into actionable insight quickly and easily. There are many logs and metrics, and they are all over the place.

Metrics 84

Metrics Data Governance Cost-Benefit Dashboards 84

Andrew White

JULY 5, 2023

One of the points of confusion is with catalogs – or data catalogs – or analytics catalogs or metrics stores. Here I repeat what I wrote in the original blog: Use cases for a data catalog Analytics use cases are quite different to governance use cases. The fact that there are different names is one thing.

Metrics 52

Metrics Metadata Modeling Data Quality 52