Cloudera

JULY 15, 2021

We recently hosted a roundtable focused on o ptimizing risk and exposure management with data insights. For financial institutions and insurers, risk and exposure management has always been a fundamental tenet of the business. Now, risk management has become exponentially complicated in multiple dimensions. .

Risk 103

Risk Optimization Management Insurance 103

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 199

Machine Learning Modeling Testing Risk Management 199

CIO Business Intelligence

OCTOBER 29, 2024

Data is the engine that powers the corporate decisions we make; from the personalized customer experiences we create to the internal processes we activate and the AI-powered breakthroughs we innovate. Reliance on this invaluable currency brings substantial risks that could severely impact an enterprise.

Enterprise 70

Enterprise Broadcasting Risk Sales 70

CIO Business Intelligence

APRIL 16, 2024

While warp speed is a fictional concept, it’s an apt way to describe what generative AI (GenAI) and large language models (LLMs) are doing to exponentially accelerate Industry 4.0. By leveraging a GenAI-fueled edge with small language models (SLMs), this lengthy work will be streamlined and simplified. Data privacy and security.

Manufacturing 142

Manufacturing Digital Transformation Risk Dashboards 142

DataKitchen

MAY 10, 2024

This blog post delves into the third critical use case for Data Observation and Data Quality Validation: development and Deployment. It highlights how DataKitchen’s Data Observation solutions equip organizations to enhance their development practices, reduce deployment risks, and increase overall productivity.

Testing 126

Testing Cost-Benefit Data Quality Dashboards 126

CIO Business Intelligence

SEPTEMBER 11, 2024

AI systems make lightning-fast decisions whether the data they are using is good data or flawed. And the risk is not just about lost revenue – it’s about eroded customer trust, compliance nightmares, and missed opportunities that could set your business back for years. Remember the old adage “garbage in, garbage out?”

Data Quality 116

Data Quality Unstructured Data Metadata Data Governance 116

DataKitchen

FEBRUARY 27, 2024

Your LLM Needs a Data Journey: A Comprehensive Guide for Data Engineers The rise of Large Language Models (LLMs) such as GPT-4 marks a transformative era in artificial intelligence, heralding new possibilities and challenges in equal measure.

Data Quality 118

Data Quality Unstructured Data Testing Interactive 118

CIO Business Intelligence

OCTOBER 2, 2024

Companies need to establish clear guidelines for how its data is collected, stored and used, and ensure compliance with data protection regulations like GDPR in the EU, CCPA in California, LGPD in Brazil, PIPL in China and AI regulations such as EU AI Act. Identify gaps related to ethics, transparency, risk and compliance.

Gap analysis 117

Gap analysis Risk Manufacturing Data Governance 117

CIO Business Intelligence

APRIL 1, 2024

Deloitte 2 meanwhile found that 41% of business and technology leaders said a lack of talent, governance, and risks are barriers to broader GenAI adoption. Data preparation, including anonymizing, labeling, and normalizing data across sources, is key. Right-size your model(s). Choose a workload location.

Uncertainty 142

Uncertainty Data Lake Consulting Risk 142

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?

Measurement 52

Measurement Modeling Data Quality Data Governance 52

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.

Data Governance 59

Data Governance Risk Data Quality Dashboards 59

CIO Business Intelligence

SEPTEMBER 30, 2024

-based research firm is proud of its mission to deliver accurate data to ensure goods and services are distributed with equity and precision in a socially just manner. Once we get more data from across a couple of areas into Mquiry, I would love to see the insights it might show us and do some training against that data.

Data Quality 113

Data Quality Experimentation Insurance Statistics 113

CIO Business Intelligence

DECEMBER 8, 2023

But as the numbers of new gen AI-powered chatbots grow, so do the risks of their occasional glitches—nonsensical or inaccurate outputs or answers that are not easily screened out of the large language models (LLMs) that the tools are trained on. Minimizing risk Many companies are starting to invest in mitigating risk.

Risk 120

Risk Finance Data Quality Modeling 120

CIO Business Intelligence

SEPTEMBER 17, 2024

All this while CIOs are under increased pressure to deliver more competitive capabilities, reduce security risks, connect AI with enterprise data, and automate more workflows — all areas where architecture disciplines have a direct role in influencing outcomes.

Enterprise 145

Enterprise Digital Transformation Cost-Benefit Risk 145

CIO Business Intelligence

AUGUST 9, 2024

Privacy protection The first step in AI and gen AI projects is always to get the right data. “In In cases where privacy is essential, we try to anonymize as much as possible and then move on to training the model,” says University of Florence technologist Vincenzo Laveglia. “A A balance between privacy and utility is needed.

Risk 138

Risk Measurement Modeling Data Lake 138

DataKitchen

MARCH 12, 2024

Our vision was to create a flexible, state-of-the-art data infrastructure that would allow our analysts to transform the data rapidly with a very low risk of error. After working with DataKitchen for a while, we noticed almost an absolute absence of data errors we didn’t catch earlier. That was amazing for the team.”

Metrics 118

Metrics Software Cost-Benefit Testing 118

CIO Business Intelligence

AUGUST 15, 2024

Many of those gen AI projects will fail because of poor data quality, inadequate risk controls, unclear business value , or escalating costs , Gartner predicts. When we do planning sessions with our clients, two thirds of the solutions they need don’t necessarily fit the generative AI model.

ROI 143

ROI Cost-Benefit Experimentation Deep Learning 143

O'Reilly on Data

APRIL 19, 2021

Relatively few respondents are using version control for data and models. Tools for versioning data and models are still immature, but they’re critical for making AI results reproducible and reliable. It’s gratifying to note that organizations starting to realize the importance of data quality (18%).

Enterprise 360

Enterprise Risk Modeling Manufacturing 360

CIO Business Intelligence

OCTOBER 16, 2024

Edge computing can reduce latency, lower cost, and lower data exposure risks.” There are numerous ways AI models at the edge could help beyond simply controlling traffic lights, he says, such as citizen safety, autonomous transportation, smart grids, and self-healing infrastructures.

Cost-Benefit 143

Cost-Benefit Manufacturing Data-driven Optimization 143

Laminar Security

DECEMBER 1, 2023

Cloud data security is one of the most critical, yet most challenging aspects of doing business in the age of cloud. As more organizations migrate their data to the cloud, they face an increasing range of risks and threats, including data breaches, data leakage, data loss, data misuse, data compliance violations, shadow data and more.

Modeling 52

Modeling Cost-Benefit Risk Data-driven 52

CIO Business Intelligence

MAY 15, 2024

It seems anyone can make an AI model these days. Even if you don’t have the training data or programming chops, you can take your favorite open source model, tweak it, and release it under a new name. And these models, though they lag behind the big commercial ones, are improving quickly.

Modeling 136

Modeling Risk Software Enterprise 136

Rocket-Powered Data Science

FEBRUARY 15, 2023

While generative AI has been around for several years , the arrival of ChatGPT (a conversational AI tool for all business occasions, built and trained from large language models) has been like a brilliant torch brought into a dark room, illuminating many previously unseen opportunities.

Strategy 290

Strategy Experimentation Uncertainty Machine Learning 290

CIO Business Intelligence

OCTOBER 2, 2024

According to Kari Briski, VP of AI models, software, and services at Nvidia, successfully implementing gen AI hinges on effective data management and evaluating how different models work together to serve a specific use case. But some IT leaders are getting it right because they focus on three key aspects.

Management 141

Management Data Governance Cost-Benefit Structured Data 141

O'Reilly on Data

OCTOBER 22, 2020

Taking the time to work this out is like building a mathematical model: if you understand what a company truly does, you don’t just get a better understanding of the present, but you can also predict the future. Since I work in the AI space, people sometimes have a preconceived notion that I’ll only talk about data and models.

Consulting 305

Consulting Risk Cost-Benefit Modeling 305

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 80

Metrics Machine Learning Statistics Risk 80

AWS Big Data

FEBRUARY 29, 2024

Data is your generative AI differentiator, and a successful generative AI implementation depends on a robust data strategy incorporating a comprehensive data governance approach. Data governance is a critical building block across all these approaches, and we see two emerging areas of focus.

Data Governance 107

Data Governance Unstructured Data Metadata Data Lake 107

O'Reilly on Data

JULY 28, 2020

You must detect when the model has become stale, and retrain it as necessary. This isn’t always simple, since it doesn’t just take into account technical risk; it also has to account for social risk and reputational damage. Acquiring data is often difficult, especially in regulated industries.

Marketing 363

Marketing Experimentation Metrics Testing 363

CIO Business Intelligence

JULY 29, 2024

Data quality issues All AI success is dependent on the quality of the data it processes. Unfortunately, in many organizations, identity data tends to be disorganized, outdated, and inaccurate. It consolidates duplicated platform data from various functions such as SecOps and CMDB into a central repository.

Management 80

Management Data Quality Modeling Data Science 80

IBM Big Data Hub

MAY 9, 2023

Data must be laboriously collected, curated, and labeled with task-specific annotations to train AI models. Building a model requires specialized, hard-to-find skills — and each new task requires repeating the process. ” These large models have lowered the cost and labor involved in automation.

Enterprise 128

Enterprise Technology Modeling Cost-Benefit 128

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.

Analytics 116

Analytics Broadcasting Predictive Analytics Metrics 116

CIO Business Intelligence

DECEMBER 19, 2023

Many technology investments are merely transitionary, taking something done today and upgrading it to a better capability without necessarily transforming the business or operating model. Second, CIOs must identify the gaps between the hype of what business leaders expect from IT departments and the realities.

Digital Transformation 143

Digital Transformation Unstructured Data Machine Learning Risk Management 143

Cloudera

SEPTEMBER 10, 2024

However, six months into its implementation, regulators discovered that the AI model had been trained on biased historical data and was inadvertently discriminating against certain demographic groups, leading to unfair lending practices. While these scenarios are hypotheticals, the risk is real.

Risk 52

Risk Testing Reporting Measurement 52

CIO Business Intelligence

MAY 2, 2023

The risk of derailments increases as I hear inconsistent answers or too many conflicting priorities. One recent study shows that only 50% follow a product-centric operating model focusing on customer centricity and delivering delightful customer experiences. Digital Transformation

Digital Transformation 141

Digital Transformation IT Data-driven Metrics 141

DataKitchen

OCTOBER 20, 2023

Deploying a Data Journey Instance unique to each customer’s payload is vital to fill this gap. Such an instance answers the critical question of ‘Dude, Where is my data?’ ’ while maintaining operational efficiency and ensuring data quality—thus preserving customer satisfaction and the team’s credibility.

Insurance 173

Insurance Metadata Data-driven Data Quality 173

IBM Big Data Hub

APRIL 20, 2023

When consumers lose trust in a bank’s ability to manage risk, the system stops working. Banks and their employees place trust in their risk models to help ensure the bank maintains liquidity even in the worst of times. This can ensure that the decisions made are reliable and of high quality.

Risk 68

Risk Risk Management Reporting Metadata 68

CIO Business Intelligence

JULY 3, 2024

Fozard says the act of balancing cost and risk with the potential value add is like a teeter-totter approach. Then the council starts looking at those high priority projects to make sure they can protect everything the university needs to protect, including intellectual property, research aspirations, user privacy, and sensitive data.

Risk 131

Risk Software Management IT 131

CIO Business Intelligence

MARCH 24, 2023

It encompasses the people, processes, and technologies required to manage and protect data assets. The Data Management Association (DAMA) International defines it as the “planning, oversight, and control over management of data and the use of data and data-related sources.”

Data Governance 142

Data Governance Management Metadata Data Quality 142