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 141

Measurement Digital Transformation KPI Metrics 141

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.

Data Quality 133

Data Quality Measurement Metrics Data Collection 133

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.

Data Quality 116

Data Quality Statistics Visualization Metrics 116

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.

Data Quality 120

Data Quality Metrics Data Lake Sales 120

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.

Data Quality 118

Data Quality Visualization Metadata Metrics 118

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. 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?

Metrics 130

Metrics Data Analytics Analytics Measurement 130

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.

Risk 140

Risk Cost-Benefit Data-driven Digital Transformation 140

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. presented the TRACE framework for measuring results, which showed how GraphRAG achieves an average performance improvement of up to 14.03%.

Unstructured Data 318

Unstructured Data Structured Data Statistics Modeling 318

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.

Data Quality 114

Data Quality Data Lake Data Warehouse Metrics 114

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.

Metrics 118

Metrics Software Cost-Benefit Testing 118

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.

Modeling 256

Modeling Machine Learning Testing Metrics 256

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 98

Data Quality Statistics Data Lake Visualization 98

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).

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

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.

Measurement 246

Measurement Metrics Data-driven Dashboards 246

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 314

Management Machine Learning Metrics Modeling 314

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.

Testing 304

Testing Machine Learning Consulting Data Science 304

O'Reilly on Data

MARCH 31, 2020

Measurement, tracking, and logging is less of a priority in enterprise software. Consumer product management is typically more bottom-up, driven by large volumes of user feedback and usage tracking data. It turns out that type of data infrastructure is also the foundation needed for building AI products.

Management 363

Management Machine Learning Experimentation Metrics 363

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

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 98

Data Quality Strategy Business Objectives Sales 98

datapine

APRIL 16, 2019

By implementing the right reporting tools and understanding how to analyze as well as to measure your data accurately, you will be able to make the kind of data driven decisions that will drive your business forward. Exclusive Bonus Content: How to be data driven in decision making? What Is Data Driven Decision Making?

Data-driven 287

Data-driven Dashboards Visualization Cost-Benefit 287

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 98

Data Quality Data-driven Data Lake Metrics 98

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. Every serious business uses key performance indicators to measure and evaluate success. Enhanced data quality. It doesn’t stop here. Operational optimization and forecasting.

Business Intelligence 259

Business Intelligence Reporting Cost-Benefit Dashboards 259

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.

Testing 173

Testing Data Quality Predictive Modeling Metrics 173

CIO Business Intelligence

JANUARY 30, 2025

This is the process that ensures the effective and efficient use of IT resources and ensures the effective evaluation, selection, prioritization and funding of competing IT investments to get measurable business benefits. You can also measure user AI skills, adoption rates and even the maturity level of the governance model itself.

Testing 93

Testing Metrics Cost-Benefit Modeling 93

CIO Business Intelligence

NOVEMBER 14, 2024

“Like all companies, we depend on data provided by big tech, but for specific activities, DaaS is an important solution to combat activities that can damage our business,” he says. An innovation for CIOs: measuring IT with KPIs CIOs discuss sales targets with CEOs and the board, cementing the IT and business bond.

ROI 119

ROI B2B Business Objectives Digital Transformation 119

CIO Business Intelligence

NOVEMBER 13, 2024

Managers tend to incentivize activity metrics and measure inputs versus outputs,” she adds. At least 30% of gen AI projects will be abandoned by the end of 2025, the research firm predicts, due to unclear business value — as well as poor data quality, inadequate risk controls, and escalating costs.

IT 141

IT Consulting ROI Cost-Benefit 141

CIO Business Intelligence

FEBRUARY 20, 2025

However, it is often unclear where the data needed for reporting is stored and what quality it is in. Often the data quality is insufficient to make reliable statements. Insufficient or incorrect data can even lead to wrong decisions, says Kastrati. Big data and analytics provide valuable support in this regard.

Big Data 84

Big Data Measurement Visualization Machine Learning 84

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 95

Data Quality Data Lake Visualization Data-driven 95

CIO Business Intelligence

JULY 18, 2022

While this may seem like an odd question, understanding organizational change levers can help uncover opportunities for improving your data supply-chain processes. A key challenge with organizational alignment is communicating across all departments the goals, metrics, and benefits of a process or function.

Data Quality 105

Data Quality Metrics Measurement Cost-Benefit 105

DataKitchen

MAY 10, 2021

Some will argue that observability is nothing more than testing and monitoring applications using tests, metrics, logs, and other artifacts. That’s a fair point, and it places emphasis on what is most important – what best practices should data teams employ to apply observability to data analytics. It’s not about data quality

Testing 214

Testing Manufacturing Data Quality Statistics 214

Jet Global

MARCH 4, 2020

A manufacturing Key Performance Indicator (KPI) or metric is a well defined and quantifiable measure that the manufacturing industry uses to gauge its performance over time. The only way to stay ahead in this fiercely competitive industry is through the implementation of manufacturing KPIs and metrics. View Guide Now.

Manufacturing 80

Manufacturing Metrics Reporting KPI 80

DataKitchen

JUNE 24, 2021

GE formed its Digital League to create a data culture. One of the keys for our success was really focusing that effort on what our key business initiatives were and what sorts of metrics mattered most to our customers. So we really prioritized the data that we thought had the biggest chance of delivering success in the end.

Metrics 211

Metrics ROI Measurement Cost-Benefit 211

O'Reilly on Data

DECEMBER 12, 2019

Residuals are a numeric measurement of model errors, essentially the difference between the model’s prediction and the known true outcome. Residual plots place input data and predictions into a two-dimensional visualization where influential outliers, data-quality problems, and other types of bugs often become plainly visible.

Machine Learning 282

Machine Learning Modeling Testing Risk Management 282

TDAN

MARCH 6, 2024

Data quality is measured across dimensions, but why? Data quality metrics exist to support the business. The value of a data quality program resides in the ability to take action to improve data to make it more correct and therefore more valuable.

Data Quality 52

Data Quality Metrics Measurement IT 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

datapine

DECEMBER 17, 2019

The purpose is not to track every statistic possible, as you risk being drowned in data and losing focus. Inclusivity: Expanding on decision-making, as these kinds of dashboards and reports serve up digestible data visualizations, members of your IT department will be able to use these reporting tools with ease, even under pressure.

Reporting 173

Reporting IT Key Performance Indicator Dashboards 173

Occam's Razor

AUGUST 13, 2012

The questions reveal a bunch of things we used to worry about, and continue to, like data quality and creating data driven cultures. Yehoshua Coren: Best ways to measure user behavior in a multi-touch, multi-device digital world. What's possible to measure. What's not possible to measure.

Modeling 125

Modeling Metrics Data Quality Data-driven 125