DataKitchen

MARCH 20, 2025

We’ve identified two distinct types of data teams: process-centric and data-centric. Understanding this framework offers valuable insights into team efficiency, operational excellence, and data quality. Process-centric data teams focus their energies predominantly on orchestrating and automating workflows.

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CIO Business Intelligence

DECEMBER 10, 2024

Specify metrics that align with key business objectives Every department has operating metrics that are key to increasing revenue, improving customer satisfaction, and delivering other strategic objectives. Successful selling has always been about volume and quality, says Jonathan Lister, COO of Vidyard.

Sales 143

Sales Metrics Data-driven Measurement 143

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.

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AWS Big Data

AUGUST 8, 2024

They establish data quality rules to ensure the extracted data is of high quality for accurate business decisions. These rules commonly assess the data based on fixed criteria reflecting the current business state. In this post, we demonstrate how this feature works with an example.

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AWS Big Data

APRIL 3, 2024

Today, we are pleased to announce that Amazon DataZone is now able to present data quality information for data assets. Other organizations monitor the quality of their data through third-party solutions. Additionally, Amazon DataZone now offers APIs for importing data quality scores from external systems.

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Data Quality Visualization Metadata Metrics 118

AWS Big Data

MAY 23, 2024

They establish data quality rules to ensure the extracted data is of high quality for accurate business decisions. These rules assess the data based on fixed criteria reflecting current business states. We are excited to talk about how to use dynamic rules , a new capability of AWS Glue Data Quality.

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DataKitchen

JUNE 21, 2024

Navigating the Storm: How Data Engineering Teams Can Overcome a Data Quality Crisis Ah, the data quality crisis. It’s that moment when your carefully crafted data pipelines start spewing out numbers that make as much sense as a cat trying to bark. You’ve got yourself a recipe for data disaster.

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CIO Business Intelligence

NOVEMBER 27, 2024

Once the province of the data warehouse team, data management has increasingly become a C-suite priority, with data quality seen as key for both customer experience and business performance. But along with siloed data and compliance concerns , poor data quality is holding back enterprise AI projects.

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AWS Big Data

AUGUST 15, 2024

Data quality is crucial in data pipelines because it directly impacts the validity of the business insights derived from the data. Today, many organizations use AWS Glue Data Quality to define and enforce data quality rules on their data at rest and in transit.

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Data Quality Visualization Metadata Key Performance Indicator 111

CIO Business Intelligence

APRIL 8, 2025

As technology and business leaders, your strategic initiatives, from AI-powered decision-making to predictive insights and personalized experiences, are all fueled by data. Yet, despite growing investments in advanced analytics and AI, organizations continue to grapple with a persistent and often underestimated challenge: poor data quality.

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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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AWS Big Data

MARCH 12, 2024

In recent years, data lakes have become a mainstream architecture, and data quality validation is a critical factor to improve the reusability and consistency of the data. In this post, we provide benchmark results of running increasingly complex data quality rulesets over a predefined test dataset.

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AWS Big Data

OCTOBER 9, 2024

Some customers build custom in-house data parity frameworks to validate data during migration. Others use open source data quality products for data parity use cases. This takes away important person hours from the actual migration effort into building and maintaining a data parity framework.

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Data Quality Data Lake Data Warehouse Metrics 114

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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Data Quality Data Governance Metadata Metrics 98

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.

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Data Quality Statistics Data Lake Visualization 98

DataKitchen

MARCH 12, 2024

Key Success Metrics, Benefits, and Results for Data Observability Using DataKitchen Software Lowering Serious Production Errors Key Benefit Errors in production can come from many sources – poor data, problems in the production process, being late, or infrastructure problems. Data errors can cause compliance risks.

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Metrics Software Cost-Benefit Testing 118

CIO Business Intelligence

MARCH 25, 2025

Data debt that undermines decision-making In Digital Trailblazer , I share a story of a private company that reported a profitable year to the board, only to return after the holiday to find that data quality issues and calculation mistakes turned it into an unprofitable one.

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Risk Cost-Benefit Data-driven Digital Transformation 140

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.

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Data Quality Data Governance Metrics Statistics 94

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?

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Metrics Data Analytics Analytics Measurement 130

datapine

NOVEMBER 27, 2019

Companies are no longer wondering if data visualizations improve analyses but what is the best way to tell each data-story. 2020 will be the year of data quality management and data discovery: clean and secure data combined with a simple and powerful presentation. 1) Data Quality Management (DQM).

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Business Intelligence Analytics Prescriptive Analytics Data Quality 361

DataKitchen

APRIL 13, 2021

RightData – A self-service suite of applications that help you achieve Data Quality Assurance, Data Integrity Audit and Continuous Data Quality Control with automated validation and reconciliation capabilities. QuerySurge – Continuously detect data issues in your delivery pipelines. Data breaks.

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Testing Machine Learning Consulting Data Science 304

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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Data Quality Data-driven Data Lake Metrics 98

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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Data Quality Strategy Business Objectives Sales 98

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.

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Data Quality Data Governance Data Lake Testing 111

O'Reilly on Data

OCTOBER 13, 2020

Ideally, AI PMs would steer development teams to incorporate I/O validation into the initial build of the production system, along with the instrumentation needed to monitor model accuracy and other technical performance metrics. But in practice, it is common for model I/O validation steps to be added later, when scaling an AI product.

Management 317

Management Machine Learning Metrics Modeling 317

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.

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Metrics Key Performance Indicator KPI Marketing 80

O'Reilly on Data

NOVEMBER 19, 2024

While RAG leverages nearest neighbor metrics based on the relative similarity of texts, graphs allow for better recall of less intuitive connections. A generalized, unbundled workflow A more accountable approach to GraphRAG is to unbundle the process of knowledge graph construction, paying special attention to data quality.

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Unstructured Data Structured Data Statistics Modeling 321

O'Reilly on Data

JUNE 19, 2019

In a previous post , we noted some key attributes that distinguish a machine learning project: Unlike traditional software where the goal is to meet a functional specification, in ML the goal is to optimize a metric. Quality depends not just on code, but also on data, tuning, regular updates, and retraining.

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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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datapine

JANUARY 21, 2020

The balance sheet gives an overview of the main metrics which can easily define trends and the way company assets are being managed. Our procurement dashboard above is not only visually balanced but also offers a clear-cut snapshot of every vital metric you need to improve your procurement processes at a glance. Enhanced data quality.

Business Intelligence 259

Business Intelligence Reporting Cost-Benefit Dashboards 259

DataKitchen

MAY 7, 2024

DataKitchen Training And Certification Offerings For Individual contributors with a background in Data Analytics/Science/Engineering Overall Ideas and Principles of DataOps DataOps Cookbook (200 page book over 30,000 readers, free): DataOps Certificatio n (3 hours, online, free, signup online): DataOps Manifesto (over 30,000 signatures) One (..)

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Data Quality Testing Metrics Consulting 164

O'Reilly on Data

MARCH 31, 2020

Otherwise, you will burn money paying external services for labeled data, and that up-front cost–before you can do your first demo–can easily be the most expensive part of the project. Without large amounts of good raw and labeled training data, solving most AI problems is not possible. Is the product something that customers need?

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Management Machine Learning Experimentation Metrics 363

CIO Business Intelligence

JANUARY 30, 2025

Metrics should include system downtime and reliability, security incidents, incident response times, data quality issues and system performance. Set goals and report metrics to determine if you are achieving the goals set out by the organization or the AI governance committee. Pull in the same direction Dont wait.

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Testing Metrics Cost-Benefit Modeling 93

DataKitchen

SEPTEMBER 21, 2023

These layers help teams delineate different stages of data processing, storage, and access, offering a structured approach to data management. In the context of Data in Place, validating data quality automatically with Business Domain Tests is imperative for ensuring the trustworthiness of your data assets.

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Testing Data Quality Predictive Modeling Metrics 173

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.

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Data Quality Enterprise Business Intelligence Data Governance 56

DataKitchen

APRIL 26, 2021

At Workiva, they recognized that they are only as good as their data, so they centered their initial DataOps efforts around lowering errors. Hodges commented, “Our first focus was to up our game around data quality and lowering errors in production. Multiple Metrics for Success. At GSK, success is all about adoption.

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DataKitchen

MAY 10, 2024

The Third 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.

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