Domino Data Lab

MARCH 3, 2021

It’s often stated that nothing changes inside an enterprise because you’ve built a model. In some cases, data science does generate models directly to revenue, such as a contextual deal engine that targets people with offers that they can instantly redeem. But what about good decisions?

Metrics 93

Metrics Modeling Sales Data Science 93

Cloudera

OCTOBER 20, 2021

As part of these efforts, disclosure requirements will mandate that firms provide “the impact of a company’s activities on the environment and society, as well as the business and financial risks faced by a company due to its sustainability exposures.” What are the key climate risk measurements and impacts? Generate Scenarios.

Risk 79

Risk Modeling Risk Management Measurement 79

CIO Business Intelligence

MARCH 25, 2024

Modern digital organisations tend to use an agile approach to delivery, with cross-functional teams, product-based operating models , and persistent funding. But to deliver transformative initiatives, CIOs need to embrace the agile, product-based approach, and that means convincing the CFO to switch to a persistent funding model.

Modeling 124

Modeling Cost-Benefit IT ROI 124

O'Reilly on Data

NOVEMBER 13, 2018

Considerations for a world where ML models are becoming mission critical. As the data community begins to deploy more machine learning (ML) models, I wanted to review some important considerations. Before I continue, it’s important to emphasize that machine learning is much more than building models. Model lifecycle management.

Machine Learning 220

Machine Learning Risk Management Statistics 220

Anmut

MARCH 22, 2023

Data maturity models are a crucial step for any organisation looking to improve their data, informing if your current data practices are helping, or holding back, your business. ? Click the links below to navigate to different sections What are data maturity models? Why do we need data maturity models? It’s like driving a car.

Measurement 52

Measurement Modeling Data Quality Data Governance 52

O'Reilly on Data

JUNE 15, 2023

The world changed on November 30, 2022 as surely as it did on August 12, 1908 when the first Model T left the Ford assembly line. Should we risk loss of control of our civilization?” The creators of generative AI systems and Large Language Models already have tools for monitoring, modifying, and optimizing them.

Metrics 284

Metrics Reporting Measurement Finance 284

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

Smart Data Collective

SEPTEMBER 21, 2021

A growing number of businesses are starting to look for new data-driven approaches to streamline their business models. However, your data-driven business model won’t be very helpful if you don’t focus on the right metrics. Targeting the Right Variables for Your Data-Driven Retail Business Model.

Data-driven 107

Data-driven Metrics Sales Big Data 107

Domino Data Lab

OCTOBER 16, 2019

This article covers a couple of key Machine Learning (ML) vital signs to consider when tracking ML models in production to ensure model reliability, consistency and performance in the future. Machine learning models: running wild. They may also experience relief when the model “works” in production.

Metrics 49

Metrics Modeling Machine Learning Measurement 49

O'Reilly on Data

DECEMBER 12, 2019

Not least is the broadening realization that ML models can fail. And that’s why model debugging, the art and science of understanding and fixing problems in ML models, is so critical to the future of ML. Because all ML models make mistakes, everyone who cares about ML should also care about model debugging. [1]

Machine Learning 191

Machine Learning Modeling Testing Risk Management 191

IBM Big Data Hub

APRIL 15, 2024

The average employee works on autopilot, and to ensure that cybersecurity issues and risks are ingrained in their day-to-day decisions, we need to design and build programs that truly understand their intuitive way of working. This needs to be coupled with effective metrics to measure progress and demonstrate the value.

Metrics 90

Metrics Measurement Risk Data Processing 90

IBM Big Data Hub

APRIL 19, 2024

Asset performance management (APM) processes, such as risk-based and predictive maintenance and asset investment planning (AIP), enable health monitoring technologies. Cybersecurity reduces risk exposure for cyberattacks on digitally connected assets. Risk-based asset strategies align maintenance efforts to balance costs and risks.

Management 89

Management Internet of Things Risk IoT 89

IBM Big Data Hub

NOVEMBER 29, 2023

With the emergence of new advances and applications in machine learning models and artificial intelligence, including generative AI, generative adversarial networks, computer vision and transformers, many businesses are seeking to address their most pressing real-world data challenges using both types of synthetic data: structured and unstructured.

Metrics 83

Metrics Machine Learning Risk Statistics 83

CIO Business Intelligence

FEBRUARY 7, 2024

Key AI companies have told the UK government to speed up its safety testing for their systems, raising questions about future government initiatives that too may hinge on technology providers opening up generative AI models to tests before new releases hit the public.

Testing 124

Testing Reporting Risk Modeling 124

O'Reilly on Data

APRIL 23, 2024

Some of those innovations, like Amazon’s cloud computing business, represented enormous new markets and a new business model. Google, for example, invented the Large Language model architecture that underlies today’s disruptive AI startups. These companies did continue to innovate. I think not.

Advertising 270

Advertising Cost-Benefit Marketing Risk 270

CIO Business Intelligence

APRIL 8, 2024

Working with partner Amazon Web Services (AWS), the NFL has developed Digital Athlete, a platform that uses computer vision and ML to predict which players are at the highest risk of injury based on plays and their body positions. Souza’s advice: Cultivate curiosity. Capel-Davies’ advice: Focus on communication.

Analytics 112

Analytics Broadcasting Predictive Analytics Metrics 112

Occam's Razor

SEPTEMBER 29, 2009

One of the ultimate excuses for not measuring impact of Marketing campaigns is: "Oh, that's just a branding campaign." It is criminal not to measure your direct response campaigns online. I also believe that a massively under appreciated opportunity exists to truly measure impact of branding campaigns online.

Measurement 128

Measurement Metrics Analytics Marketing 128

DataKitchen

SEPTEMBER 20, 2021

For example, data cleansing, ETL, running a model, or even provisioning cloud infrastructure. Minimize Deployment Risk. Measurement DataOps. Once you’ve made progress with your production and development processes, it’s time to start measuring and improving your processes with Measurement DataOps.

Testing 246

Testing Metrics Measurement Dashboards 246

CIO Business Intelligence

DECEMBER 13, 2022

Recently, chief information officers, chief data officers, and other leaders got together to discuss how data analytics programs can help organizations achieve transformation, as well as how to measure that value contribution. business, IT, data management, security, risk and compliance etc.)

Data Analytics 104

Data Analytics Strategy Analytics Metrics 104

IBM Big Data Hub

APRIL 9, 2024

Preparing and annotating data IBM watsonx.data helps organizations put their data to work, curating and preparing data for use in AI models and applications. “For the Masters we use 290 traditional AI models to project where golf balls will land,” says Baughman. ” Watsonx.ai ” Watsonx.ai

Management 82

Management IT Machine Learning Metrics 82

DataRobot Blog

SEPTEMBER 1, 2022

For example, a recent IDC study 1 shows that it takes about 290 days on average to deploy a model into production from start to finish. Once you move your model into production, you need to monitor and manage your models to ensure that you can trust predictions and turn them into the right business decisions.

Metrics 145

Metrics Statistics Modeling Data Science 145

CIO Business Intelligence

AUGUST 18, 2023

For organizations seeking a collaborative win-win approach to outsourcing, the Vested sourcing business model is worth consideration. For example, a buying organization might want “outcomes,” but the contract spells out dozens or even hundreds of service level agreement metrics instead.

Measurement 97

Measurement Modeling Risk Management 97

erwin

MARCH 24, 2020

Technical teams charged with maintaining and executing these processes require detailed tasks, and business process modeling is integral to their documentation. erwin’s Evolve software is integral to modeling process flow requirements, but what about the technology side of the equation?

Modeling 97

Modeling Data Processing Software Finance 97

O'Reilly on Data

MARCH 31, 2020

Instead of writing code with hard-coded algorithms and rules that always behave in a predictable manner, ML engineers collect a large number of examples of input and output pairs and use them as training data for their models. The model is produced by code, but it isn’t code; it’s an artifact of the code and the training data.

Management 332

Management Machine Learning Experimentation Metrics 332

CIO Business Intelligence

MARCH 16, 2022

and ‘What is the risk of not changing?’”. To that end, his technology organization is hyper-focused on measuring and reporting on its performance. Clarity in measuring promise-and-delivery gaps is key,” he says. Metrics are mandatory. “If If you don’t measure it, it doesn’t matter,” says Mead of SPR Consulting.

Management 143

Management Measurement Metrics Consulting 143

IBM Big Data Hub

MARCH 4, 2024

While many organizations have implemented AI, the need to keep a competitive edge and foster business growth demands new approaches: simultaneously evolving AI strategies, showcasing their value, enhancing risk postures and adopting new engineering capabilities. Consider the following: Do you need a public foundation model?

Enterprise 101

Enterprise ROI Risk Strategy 101

IBM Big Data Hub

DECEMBER 13, 2023

By assessing and proactively managing risks inherent in the supply chain , organizations can shield themselves from disruptions and strengthen the resilience of their operations. This enables an effective and adaptive approach to sourcing that creates value and minimizes risk.

Strategy 68

Strategy Cost-Benefit Key Performance Indicator Consulting 68

Cloudera

DECEMBER 3, 2021

Surely there are ways to comb through the data to minimise the risks from spiralling out of control. This involves identifying, quantifying and being able to measure ethical considerations while balancing these with performance objectives. As discussed in this article , model design can also be a source of bias too. Model Drift.

Uncertainty 97

Uncertainty Measurement Metrics Risk 97

Alation

SEPTEMBER 7, 2021

In this blog we will discuss how Alation helps minimize risk with active data governance. Now that you have empowered data scientists and analysts to access the Snowflake Data Cloud and speed their modeling and analysis, you need to bolster the effectiveness of your governance models. Find Trusted Data. In Summary.

Data Governance 59

Data Governance Risk Data Quality Dashboards 59

DataKitchen

NOVEMBER 18, 2022

In addition to the tracking of relationships and quality metrics, DataOps Observability journeys allow users to establish baselines?concrete Observability users are then able to see and measure the variance between expectations and reality during and after each run. Your data team manager needs to measure her team’s progress.

Testing 130

Testing Statistics Measurement Metrics 130

IBM Big Data Hub

JANUARY 25, 2024

” Read the “Presidio AI Framework” paper to learn how to address generative AI risks with guardrails across the expanded AI life cycle As generative AI continues to go mainstream, organizations are excited about the potential to transform processes, reduce costs and increase business value.

Strategy 99

Strategy Risk Cost-Benefit Business Objectives 99

Alation

AUGUST 17, 2022

The Risks of Early Data Governance Programs. The biggest risk was a lack of ownership. Too often, organizations don’t educate their users about data governance, security, and business risk,” claims analyst Jack Gold. If your definitions are bad, so is your governance/risk/security. It’s not just an IT problem.

Data Governance 92

Data Governance Risk Data-driven Measurement 92

IBM Big Data Hub

JANUARY 16, 2024

Typically, these measures should be undertaken by a dedicated development team or through a product development partnership with an experienced and specialized consultancy. Depending on the product, this phase may also involve wire-framing and modeling as well as costing the price of materials or server space.

Strategy 78

Strategy Cost-Benefit Testing Manufacturing 78

CIO Business Intelligence

NOVEMBER 6, 2023

As you face challenges in this model, first consider how to protect the current business, then act to embrace emerging opportunities, with the end goal of creating an entirely new business: “Incubating new business models powered by emerging tech should be a strategic priority,” he says.

IT 139

IT Risk Technology Measurement 139

DataKitchen

JUNE 19, 2023

Our customers start looking at the data in dashboards and models and then find many issues. It involves tracking key metrics such as system health indicators, performance measures, and error rates and closely scrutinizing system logs to identify anomalies or errors.

Testing 130

Testing Cost-Benefit Metrics Data Quality 130

Alation

FEBRUARY 14, 2023

And a data breach poses more than just a PR risk — by violating regulations like GDPR , a data leak can impact your bottom line, too. 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. How can Alation help you?

Data Governance 52

Data Governance ROI Metrics Cost-Benefit 52

CIO Business Intelligence

APRIL 12, 2023

Most current data architectures were designed for batch processing with analytics and machine learning models running on data warehouses and data lakes. How is data, process, and model drift managed for reliability? What metrics are used to understand the business impact of real-time AI? It isn’t easy.

Machine Learning 143

Machine Learning Cost-Benefit Data-driven Strategy 143