DataKitchen

SEPTEMBER 21, 2023

Bridging the Gap: How ‘Data in Place’ and ‘Data in Use’ Define Complete Data Observability In a world where 97% of data engineers report burnout and crisis mode seems to be the default setting for data teams, a Zen-like calm feels like an unattainable dream. What is Data in Use?

Testing 169

Testing Data Quality Predictive Modeling Metrics 169

O'Reilly on Data

OCTOBER 13, 2020

It is entirely possible for an AI product’s output to be absolutely correct from the perspective of accuracy and data quality, but too slow to be even remotely useful. Continuous retraining : a data-driven approach that employs constant monitoring of the model’s key performance indicators and data quality thresholds.

Management 308

Management Machine Learning Metrics Modeling 308

CIO Business Intelligence

FEBRUARY 20, 2025

Most use master data to make daily processes more efficient and to optimize the use of existing resources. This is due, on the one hand, to the uncertainty associated with handling confidential, sensitive data and, on the other hand, to a number of structural problems.

Big Data 84

Big Data Measurement Visualization Machine Learning 84

DataKitchen

OCTOBER 2, 2023

One of the most pressing issues is the ownership of databases by multiple data teams, each with its governance protocols, leading to a volatile data environment rife with inconsistencies and errors. The Hub Data Journey provides the raw data and adds value through a ‘contract.

Data Quality 100

Data Quality Testing Uncertainty Data Enablement 100

erwin

MAY 6, 2020

In these times of great uncertainty and massive disruption, is your enterprise data helping you drive better business outcomes? Demand trusted insights based on data truths (Drive innovation and assure veracity). Ensure accurate business context and classification of data.

Cost-Benefit 94

Cost-Benefit Data Governance Uncertainty Data-driven 94

Timo Elliott

JANUARY 4, 2021

First, because uncertainty exploded. As I’ve said, data storytelling isn’t fundamentally about technology. You can find a blog post version of my commentary below, and a draft video of my section: What’s new with analytics and storytelling for finance teams? Dashboards and analytics have been around for a long, long time.

Dashboards 139

Dashboards Visualization Data-driven Forecasting 139

datapine

MAY 31, 2022

This has increased the difficulty for IT to provide the governance, compliance, risks, and data quality management required. To mitigate the various risks and uncertainties in transitioning to the cloud, IT must adapt its traditional IT control processes to include the cloud.

Risk 237

Risk Cost-Benefit Business Intelligence Data-driven 237

CIO Business Intelligence

APRIL 28, 2022

However, many financial services companies still prefer to build their own data centers rather than leverage cloud solutions. Much of this reluctance stems from the regulatory environment, arising from lengthy reviews and approvals processes, or even simple near-term regulatory uncertainty. .

Analytics 98

Analytics Insurance Big Data Uncertainty 98

DataRobot

JULY 16, 2021

They all serve to answer the question, “How well can my model make predictions based on data?” In performance, the trust dimensions are the following: Data quality — the performance of any machine learning model is intimately tied to the data it was trained on and validated against.

Machine Learning 98

Machine Learning Uncertainty Modeling Measurement 98

Cloudera

JULY 15, 2021

In this session we explored what firms are doing to approach the uncertainty with more predictability. One participant emphasized their firm’s focus on the foundational aspects of data first before applying AI recognizing if data quality is not good the application of AI/ML won’t be applied with accuracy.

Risk 100

Risk Optimization Management Insurance 100

Jen Stirrup

NOVEMBER 15, 2022

The foundation should be well structured and have essential data quality measures, monitoring and good data engineering practices. Systems thinking helps the organization frame the problems in a way that provides actionable insights by considering the overall design, not just the data on its own.

Data Science 145

Data Science Digital Transformation Data-driven Measurement 145

Cloudera

OCTOBER 8, 2020

Businesses are now faced with more data, and from more sources, than ever before. But knowing what to do with that data, and how to do it, is another thing entirely. . Poor data quality costs upwards of $3.1 Ninety-five percent of businesses cite the need to manage unstructured data as a real problem.

Digital Transformation 106

Digital Transformation Unstructured Data Experimentation Uncertainty 106

CIO Business Intelligence

JULY 10, 2024

Then there’s the broader stuff like economic uncertainty, which means really interesting choices about where you invest in technology, and the short- and long-term trade offs, hybrid workplaces, global workplaces, mobility, and how to get new tech like AI, gen AI, IoT, and quantum right and humming.

Strategy 118

Strategy Cost-Benefit Uncertainty Technology 118

IBM Big Data Hub

JUNE 22, 2023

Technology-enabled business process operations, the new BPO, can significantly create new value, improve data quality, free precious employee resources, and deliver higher customer satisfaction, but it requires a holistic approach. “Modern BPO is a creator of growth, differentiation and competitive advantage,” Manik says.

Consulting 77

Consulting Insurance Finance Uncertainty 77

IBM Big Data Hub

SEPTEMBER 11, 2023

Government executives face several uncertainties as they embark on their journeys of modernization. and quality (how does this impact service delivery, business process and data quality?). frequency (how many occurrences?), time (how much time is lost?)

Data-driven 85

Data-driven IT Measurement Cost-Benefit 85

DataRobot

JUNE 1, 2021

In an earlier post, I shared the four foundations of trusted performance in AI : data quality, accuracy, robustness and stability, and speed. Recognizing and admitting uncertainty is a major step in establishing trust. That might mean a piece of data is an outlier. Knowing When to Trust a Model. Is rain 40% likely?

Uncertainty 52

Uncertainty Machine Learning Advertising Risk 52

Octopai

APRIL 16, 2020

Some data teams working remotely are making the most of the situation with advanced metadata management tools that help them deliver faster and more accurately, ensuring business as usual, even during coronavirus. Smarter Business Intelligence is an Asset During Uncertainty.

Metadata 59

Metadata Business Intelligence Uncertainty Data Quality 59

Jet Global

APRIL 9, 2023

From Data Literacy to Fluency: Strategies for Becoming a Data-Driven Organization Download Now Four Steps to Achieving Data Fluency Another recent insightsoftware study , this time on building data fluency, highlights some key steps that organizations can take to shore up data processes and reduce time spent waiting for IT.

Finance 52

Finance Forecasting Predictive Analytics Data-driven 52

Jet Global

MARCH 13, 2020

In a Deloitte survey, 67 percent of the 1,048 executives who participated said they were uncomfortable accessing data using the tools they have available. They prefer to ask an accountant or someone from IT to retrieve data for them. If your financial intelligence needs an IQ upgrade, partner with insightsoftware.

Finance 64

Finance Snapshot Reporting Advertising 64

Jet Global

JULY 5, 2023

The Impact of Market Uncertainty This year, Finance decision-makers are feeling pressure from both internal and external sources. And on the other, internal pressures like the need for more frequent, accurate forecasting force CFOs to re-evaluate their existing tools and processes.

Finance 52

Finance Uncertainty Reporting Marketing 52

CIO Business Intelligence

MARCH 29, 2022

And the problem is not just a matter of too many copies of data. Approximately duplicated data sets may introduce uncertainty about data quality. Near duplicates immediately raise the question of which is authoritative and why there are differences, and that leads to mistrust about data quality. .

Cost-Benefit 52

Cost-Benefit Machine Learning Metadata Data Quality 52

Peter James Thomas

AUGUST 12, 2018

However, often the biggest stumbling block is a human one, getting people to buy in to the idea that the care and attention they pay to data capture will pay dividends later in the process. These and other areas are covered in greater detail in an older article, Using BI to drive improvements in data quality.

Metrics 49

Metrics Statistics Data Quality Measurement 49

CIO Business Intelligence

JANUARY 4, 2023

Modern data analytics spans a range of technologies, from dedicated analytics platforms and databases to deep learning and artificial intelligence (AI). Ready to evolve your analytics strategy or improve your data quality? Just starting out with analytics? There’s always room to grow, and Intel is ready to help.

Cost-Benefit 59

Cost-Benefit Machine Learning Uncertainty Modeling 59

Domino Data Lab

JUNE 23, 2019

If you have a user facing product, the data that you had when you prototype the model may be very different from what you actually have in production. This really rewards companies with an experimental culture where they can take intelligent risks and they’re comfortable with those uncertainties.

Management 110

Management Machine Learning Experimentation Metrics 110

bridgei2i

MAY 18, 2020

The current COVID-19 pandemic has spread waves of uncertainty across businesses and their customer base. Integrated Customer Engagement: The Need of the Hour! As the crisis continues to unfold, it is paramount that B2B companies keep their customers engaged through the economic situation. Connect with our experts here to know more.

B2B 52

B2B Sales ROI Marketing 52

Darkhorse

AUGUST 26, 2016

You have devised a number of time-tested shortcuts to deal with uncertainty. But he has a hard time explaining why it says so.When you question him about the data quality, he waves it away and mumbles something about sample size.Whenever he submits a report, it reminds you of that 4th year econ course you almost failed.

Uncertainty 40

Uncertainty Data Quality Modeling Visualization 40

CIO Business Intelligence

APRIL 1, 2024

However such fear, uncertainty, and doubt (FUD) can make it harder for IT to secure the necessary budget and resources to build services. Ensure that data is cleansed, consistent, and centrally stored, ideally in a data lake. Data preparation, including anonymizing, labeling, and normalizing data across sources, is key.

Data Lake 142

Data Lake Uncertainty Consulting Risk 142

Depict Data Studio

MAY 12, 2020

Amanda went through some of the top considerations, from data quality, to data collection, to remembering the people behind the data, to color choices. COVID-19 Data Quality Issues. Remember that there’s a lot of uncertainty in the data and it’s not uncertainty that we can represent visually well.

Visualization 52

Visualization Uncertainty Data Collection Data Quality 52

Domino Data Lab

JULY 22, 2019

One is data quality, cleaning up data, the lack of labelled data. They learned about a lot of process that requires that you get rid of uncertainty. They’re being told they have to embrace uncertainty. They’re years away from being up to that point. You know what? How could that make sense?

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

The Unofficial Google Data Science Blog

JULY 18, 2023

Editor's note : The relationship between reliability and validity are somewhat analogous to that between the notions of statistical uncertainty and representational uncertainty introduced in an earlier post. But for more complicated metrics like xRR, our preference is to bootstrap when measuring uncertainty.

Measurement 52

Measurement Metrics Uncertainty Slice and Dice 52

Anmut

OCTOBER 29, 2020

As a result, concerns of data governance and data quality were ignored. The direct consequence of bad quality data is misinformed decision making based on inaccurate information; the quality of the solutions is driven by the quality of the data. COVID-19 exposes shortcomings in data management.

Data Governance 52

Data Governance Data Collection Data-driven Statistics 52

CIO Business Intelligence

FEBRUARY 25, 2025

Typically, election years bring fear, uncertainty, and doubt, causing a slowdown in hiring, Doyle says. Still, many organizations arent yet ready to fully take advantage of AI because they lack the foundational building blocks around data quality and governance. High interest rates discouraged corporate restructuring.

Uncertainty 126

Uncertainty Cost-Benefit Data-driven Marketing 126

Anmut

APRIL 14, 2025

Condition Complexity : Unlike physical assets, data condition issues are often intangible. Missing context, ambiguity in business requirements, and a lack of accessibility makes tackling data issues complex. Lack of Predictability : Data deterioration can be hard to track systematically, especially without robust governance frameworks.

Uncertainty 52

Uncertainty Data Quality Business Objectives Measurement 52

Jet Global

APRIL 18, 2025

Here, we discuss how you can empower your SAP operations teams through times of economic uncertainty. Increasing Business Agility With Better Data Quality In the face of macroeconomic uncertainty and regulatory complexity, the real competitive edge lies in the quality of your data.

Finance 52

Finance Reporting Operational Reporting Uncertainty 52