CIO Business Intelligence

MARCH 18, 2024

There are a lot of risks and a lot of land mines to navigate,” says the analyst. Coming to grips with risk The first step in making any bet — or investment — is to understand your ability to withstand risk. We have been developing our own internal AI capability over the last few years using open-source models.

Risk 126

Risk Cost-Benefit Data Processing Testing 126

datapine

OCTOBER 7, 2020

By establishing clear operational metrics and evaluate performance, companies have the advantage of using what is crucial to stay competitive in the market, and that’s data. Your Chance: Want to visualize & track operational metrics with ease? What Are Metrics And Why Are They Important?

KPI 269

KPI Metrics Sales Visualization 269

Occam's Razor

AUGUST 9, 2021

Almost all metrics you currently use have one common thread: They are almost all backward-looking. If you want to deepen the influence of data in your organization – and your personal influence – 30% of your analytics efforts should be centered around the use of forward-looking metrics. Predictive metrics!

Metrics 142

Metrics Analytics Key Performance Indicator Predictive Modeling 142

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

DataKitchen

MARCH 16, 2023

But wait, she asks you for your team metrics. Where is your metrics report? What are the metrics that matter? Gartner attempted to list every metric under the sun in their recent report , “T oolkit: Delivery Metrics for DataOps, Self-Service Analytics, ModelOps, and MLOps, ” published February 7, 2023.

Metrics 130

Metrics Data Analytics Analytics Measurement 130

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? They need to understand;

Risk 80

Risk Modeling Risk Management Measurement 80

datapine

SEPTEMBER 29, 2022

6) Data Quality Metrics Examples. Reporting being part of an effective DQM, we will also go through some data quality metrics examples you can use to assess your efforts in the matter. These needs are then quantified into data models for acquisition and delivery. Table of Contents. 1) What Is Data Quality Management?

Data Quality 241

Data Quality Metrics Data-driven Management 241

O'Reilly on Data

OCTOBER 30, 2023

While I am heartened to hear that the Executive Order on AI uses the Defense Production Act to compel disclosure of various data from the development of large AI models, these disclosures do not go far enough. These include: What data sources the model is trained on. Operational Metrics.

Measurement 293

Measurement Risk Modeling Metrics 293

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 217

Machine Learning Risk Management Statistics 217

Cloudera

JUNE 29, 2023

To ensure the stability of the US financial system, the implementation of advanced liquidity risk models and stress testing using (MI/AI) could potentially serve as a protective measure. To improve the way they model and manage risk, institutions must modernize their data management and data governance practices.

Data Architecture 84

Data Architecture Risk Management Risk Management 84

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 117

Modeling Cost-Benefit IT ROI 117

O'Reilly on Data

JUNE 19, 2019

A look at the landscape of tools for building and deploying robust, production-ready machine learning models. We are also beginning to see researchers share sample code written in popular open source libraries, and some even share pre-trained models. Model development. Model governance. Source: Ben Lorica.

Modeling 193

Modeling Machine Learning Testing Metrics 193

DataKitchen

JUNE 1, 2022

What are my pass/fail metrics over time in production? T ools/Models/Dashboards. Is my model still accurate? How many models and dashboards were deployed? How do other organizations solve this risk problem? The biggest risk of all is space flight. How do SpaceX and NASA manage risk? Root Cause.

Risk 130

Risk Management Testing Dashboards 130

O'Reilly on Data

MAY 11, 2020

Not all models are created equal, however: they operate on different principles, and impact us as individuals and communities in different ways. To understand the menagerie of models that are fundamentally altering our individual and shared realities, we need to build a typology, a classification of their effects and impacts.

Modeling 188

Modeling Advertising Recreation/Entertainment Metrics 188

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 Big Data Sales 107

O'Reilly on Data

OCTOBER 18, 2022

When we use AI in security applications, the risks become even more direct. What if a named entity recognition (NER) system, based on a cutting-edge large language model (LLM), fails for Chinese, Cyrillic, or Arabic text? applies external authoritative standards from laws, regulations, and AI risk management frameworks.

Risk Management 287

Risk Management Risk Testing Measurement 287

AWS Big Data

JUNE 27, 2023

Our previous solution offered visualization of key metrics, but point-in-time snapshots produced only in PDF format. In this post, we discuss how we built a solution using QuickSight that delivers real-time visibility of key metrics to public sector recruiters.

Metrics 98

Metrics Dashboards Interactive Visualization 98

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 187

Machine Learning Modeling Testing Risk Management 187

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

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 280

Metrics Reporting Measurement Finance 280

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 361

Marketing Experimentation Metrics Testing 361

CIO Business Intelligence

JANUARY 23, 2024

For example, McKinsey suggests five metrics for digital CEOs , including the financial return on digital investments, the percentage of leaders’ incentives linked to digital, and the percentage of the annual tech budget spent on bold digital initiatives. As a result, outcome-based metrics should be your guide.

Measurement 129

Measurement Digital Transformation KPI Metrics 129

CIO Business Intelligence

MAY 24, 2024

Adopting a Managed Device Services model significantly reduces many of these end-of-life headaches and helps ensure compliance. A key element for governance goals will be a well-informed IT life-cycle management strategy that includes a comprehensive decommissioning policy, which reduces security risks and improves sustainability metrics.

Management 90

Management IT Cost-Benefit Metrics 90

CIO Business Intelligence

MAY 13, 2024

IBM is betting big on its toolkit for monitoring generative AI and machine learning models, dubbed watsonx.governance , to take on rivals and position the offering as a top AI governance product, according to a senior executive at IBM. watsonx.governance is a toolkit for governing generative AI and machine learning models.

Risk 108

Risk Machine Learning Modeling Enterprise 108

CIO Business Intelligence

JULY 11, 2023

In recent years, we have witnessed a tidal wave of progress and excitement around large language models (LLMs) such as ChatGPT and GPT-4. By deploying the LLM within their own VPC, the company can benefit from the AI’s insights without risking the exposure of their valuable data.

Modeling 71

Modeling Testing Experimentation Risk Management 71

bridgei2i

NOVEMBER 20, 2020

Episode 2: AI enabled Risk Management for FS powered by BRIDGEi2i Watchtower. AI enabled Risk Management for FS powered by BRIDGEi2i Watchtower. Today the Chief Risk Officers(CROs) struggle with the critical task of monitoring and assessing key risks in real time and firefight to mitigate any critical issues that arise.

Risk Management 92

Risk Management Risk Management Metrics 92

DataRobot Blog

SEPTEMBER 30, 2022

How do you track the integrity of a machine learning model in production? Model Observability can help. By tracking service, drift, prediction data, training data, and custom metrics, you can keep your models and predictions relevant in a fast-changing world. Model Observability Features.

Slice and Dice 52

Slice and Dice Modeling Metrics Experimentation 52

Jet Global

APRIL 5, 2021

Enterprises actively use financial modeling to guide their financial planning and strategic decision-making. Financial models offer data-driven, quantitative analysis that tells you where your company stands and where it’s heading. That being said, one model can’t do it all. What Is Financial Modeling? Risk management.

Modeling 98

Modeling Forecasting Metrics Finance 98

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 82

Metrics Machine Learning Risk Statistics 82

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 265

Advertising Cost-Benefit Marketing Risk 265

Jet Global

MAY 15, 2020

A financial Key Performance Indicator (KPI) or metric is a quantifiable measure that a company uses to gauge its financial performance over time. These three statements are data rich and full of financial metrics. The Fundamental Finance KPIs and Metrics – Cash Flow. What is a Financial KPI? Current Ratio. View Guide Now.

Metrics 98

Metrics Finance Reporting KPI 98

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 87

Management Internet of Things Risk IoT 87

Insight

FEBRUARY 19, 2020

Using variability in machine learning predictions as a proxy for risk can help studio executives and producers decide whether or not to green light a film project Photo by Kyle Smith on Unsplash Originally posted on Toward Data Science. Hollywood is a $10 billion-a-year industry, and movies range from huge hits to box office bombs.

Risk 67

Risk ROI Modeling Metrics 67

Cloudera

MAY 18, 2021

In this article, we will be using synthetic market data generated by an agent-based model (ABM) developed by Simudyne. Rather than a top-down approach, ABMs model autonomous actors (or agents) within a complex system — for example, different kinds of buyers and sellers in financial markets. Intraday VaR. Image Source: [link].

Risk 96

Risk Marketing Risk Management Data-driven 96

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 88

Metrics Measurement Risk Data Processing 88

Domino Data Lab

AUGUST 10, 2021

Models are the central output of data science, and they have tremendous power to transform companies, industries, and society. At the center of every machine learning or artificial intelligence application is the ML/AI model that is built with data, algorithms and code. The process of creating models is called modeling.

Modeling 64

Modeling IT Risk Management Deep Learning 64

Jet Global

NOVEMBER 2, 2021

KPIs are a select few metrics that provide insight on the operation of all entities contributing to the supply chain. Metrics help supply chain management track its progress in achieving its goals and respond quickly if needed. Measurable: Is your metric quantifiable? That’s where KPI monitoring comes into play.

Metrics 52

Metrics Reporting KPI Key Performance Indicator 52