IBM Big Data Hub

SEPTEMBER 28, 2023

An AI and data platform, such as watsonx, can help empower businesses to leverage foundation models and accelerate the pace of generative AI adoption across their organization. Business-targeted, IBM-developed foundation models built from sound data Business leaders charged with adopting generative AI need model flexibility and choice.

Testing 95

Testing Finance Enterprise Modeling 95

CIO Business Intelligence

SEPTEMBER 13, 2023

Gearing up to build an app that taps the power of highly capable foundation models is not hard for any modern developer. Let them test, learn, and–as the teams individually and collectively build their generative AI knowledge and skills–start playing to win by deploying to prod. CHRO, CMO) as the executive sponsor of one such team.

Uncertainty 98

Uncertainty Interactive Strategy Machine Learning 98

CIO Business Intelligence

JUNE 28, 2023

These circumstances have induced uncertainty across our entire business value chain,” says Venkat Gopalan, chief digital, data and technology officer, Belcorp. “As Belcorp operates under a direct sales model in 14 countries. That, in turn, led to a slew of manual processes to make descriptive analysis of the test results.

Digital Transformation 97

Digital Transformation Cost-Benefit Informatics Data mining 97

Jet Global

JANUARY 12, 2021

With the pace of change and uncertainty facing your business, is your current planning process fit for purpose? Discover: How to get started quickly – by turning your existing spreadsheet models into a robust, scalable, and agile planning solution. Webinar Date: February 18, 2021 at 11 AM Local Time. Register Now. Register Now.

Uncertainty 98

Uncertainty Finance Forecasting Testing 98

Cloudera

DECEMBER 3, 2021

Systems should be designed with bias, causality and uncertainty in mind. For example, training an interview screening model using education data often contains gender information. As discussed in this article , model design can also be a source of bias too. Model Drift. System Design. Human Judgement & Oversight.

Uncertainty 102

Uncertainty Measurement Metrics Risk 102

DataKitchen

OCTOBER 2, 2023

Data Journeys track and monitor all levels of the data stack, from data to tools to code to tests across all critical dimensions. A Data Journey supplies real-time statuses and alerts on start times, processing durations, test results, and infrastructure events, among other metrics. .’ What’s a Data Journey?

Data Quality 100

Data Quality Testing Uncertainty Data Enablement 100

CIO Business Intelligence

SEPTEMBER 22, 2022

Seeing that remote working continues to be a pressing issue still finding its footing after nearly three years in beta testing, the work surrounding feasible solutions seems to compound as time goes on, with some intending a full return to office while others have forged the company future on remote models.

Uncertainty 110

Uncertainty Forecasting Visualization Big Data 110

CIO Business Intelligence

NOVEMBER 7, 2023

Real-time WiFi 7 AP flow test – 12.7Gbps Huawei Huawei’s commitment to propelling high-quality 10 Gbps campus networks into the intelligent future is evident. The expansion of parameters, exemplified by the transition from GPT-3 to GPT-4, necessitates an efficient network infrastructure to support the effective training of these models.

IoT 123

IoT Digital Transformation Sales Uncertainty 123

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. Machine learning adds uncertainty. Models also become stale and outdated over time.

Management 332

Management Machine Learning Experimentation Metrics 332

CIO Business Intelligence

FEBRUARY 23, 2024

The completion of such transformative EV and hydrogen fuel cell engineering — amid uncertainty about which technology will prevail as the industry standard — reflects the one constant American Honda’s VP of IT Bob Brizendine has confronted throughout his 36 years with the company: an ever-changing, winding road that never slows down.

IT 122

IT Manufacturing Unstructured Data Strategy 122

CIO Business Intelligence

NOVEMBER 14, 2022

A DSS supports the management, operations, and planning levels of an organization in making better decisions by assessing the significance of uncertainties and the tradeoffs involved in making one decision over another. According to Gartner, the goal is to design, model, align, execute, monitor, and tune decision models and processes.

Data mining 139

Data mining Data-driven Statistics OLAP 139

CIO Business Intelligence

SEPTEMBER 6, 2023

Since ChatGPT’s release in November of 2022, there have been countless conversations on the impact of similar large language models. The use of AI-generated code is still in an experimental phase for many organizations due to numerous uncertainties such as its impact on security, data privacy, copyright, and more.

Software 119

Software Experimentation Risk Data Lake 119

CIO Business Intelligence

JANUARY 11, 2023

New products and ideas are tested every day, just as new opportunities are ignored. Noteworthy companies like Airbnb, Uber, and Apple innovated through major technology breakthroughs, but innovation doesn’t have to be a completely new business model. Blockbuster thought going digital would be too expensive.

Enterprise 104

Enterprise Uncertainty Consulting Sales 104

The Unofficial Google Data Science Blog

DECEMBER 14, 2021

by AMIR NAJMI & MUKUND SUNDARARAJAN Data science is about decision making under uncertainty. Some of that uncertainty is the result of statistical inference, i.e., using a finite sample of observations for estimation. But there are other kinds of uncertainty, at least as important, that are not statistical in nature.

Uncertainty 56

Uncertainty Statistics Measurement Cost-Benefit 56

Cloudera

JULY 15, 2021

In this session we explored what firms are doing to approach the uncertainty with more predictability. Pandemic “Pressure” Testing. However, through this real-time “pressure test”, they identified areas of weakness, dependencies, and opportunities. Observe what the model has to offer even if not the intended output.

Risk 100

Risk Optimization Management Insurance 100

IBM Big Data Hub

APRIL 18, 2024

While these large language model (LLM) technologies might seem like it sometimes, it’s important to understand that they are not the thinking machines promised by science fiction. Most experts categorize it as a powerful, but narrow AI model. A key trend is the adoption of multiple models in production.

Cost-Benefit 97

Cost-Benefit Modeling Manufacturing Interactive 97

Jedox

SEPTEMBER 3, 2020

The unprecedented uncertainty forced companies to make critical decisions within compressed time frames. Many pre-crisis business assumptions and planning models became outmoded overnight. Using these drivers as an overlay to stress-test models add robustness to forecasting and can identify exposure and risks to long-term stability.

Uncertainty 81

Uncertainty Forecasting Digital Transformation Risk 81

CIO Business Intelligence

JANUARY 17, 2023

Shut down the testing environment when you’re not using it. For instance, a robust FinOps capability can prevent spend commitment mistakes, and help you switch from a “lift-and-shift” approach founded on a datacenter mentality to a true cloud-centric model that realizes cloud’s full potential. That’s a core benefit of cloud.

Cost-Benefit 138

Cost-Benefit IT Uncertainty Optimization 138

DataRobot

JULY 16, 2021

The first is trust in the performance of your AI/machine learning model. They all serve to answer the question, “How well can my model make predictions based on data?” How can identifying gaps or discrepancies in the training data help you build a more trustworthy model? Dimensions of Trust. How large is the data set?

Machine Learning 98

Machine Learning Uncertainty Modeling Measurement 98

Domino Data Lab

MAY 15, 2019

Unfortunately, a common challenge that many industry people face includes battling “ the model myth ,” or the perception that because their work includes code and data, their work “should” be treated like software engineering. This work includes model improvements as well as adding new signals and features into the model.

Machine Learning 111

Machine Learning Management Experimentation Uncertainty 111

Smart Data Collective

FEBRUARY 23, 2022

Many companies are going to have to revamp their entire business models in order to deal with the new technological changes brought on by advances in the IoT. We have many examples of companies that refuse to previous changes in the market and eventually collapse because of their persistent attachment to an old-fashioned business model.

IoT 114

IoT Internet of Things Data-driven Uncertainty 114

DataRobot

APRIL 5, 2021

The uncertainty in her reply piqued my interest. Some claim that fully interpretable models are the solution, that we should constrain the complexity of algorithms so that a layperson can understand them. Some participants were advised of potential model shortcomings due to specific missing inputs.

Uncertainty 96

Uncertainty Machine Learning Modeling Reporting 96

CIO Business Intelligence

JULY 11, 2023

McKinsey partners Lareina Yee, Bryan Hancock, and Bill Schaninger home in on how generative AI could help in a discussion of employee evaluations: But what if I, as the employee, can query, “Who are five success models with my strengths and weaknesses, and what have they gone on to do? What if Bill is someone I should model myself on?

Strategy 74

Strategy Uncertainty Data-driven Consulting 74

Juice Analytics

APRIL 17, 2020

He goes on to clarify by saying that some estimate that 80% of the cases don’t get tested, so we don’t actually know the real number of cases, but it’s likely very much higher. Forecasts are built by experts, using lots of assumptions, based on very complex and specifically applied statistical models.

Forecasting 85

Forecasting Snapshot Dashboards Uncertainty 85

DataRobot

JUNE 1, 2021

Before you put a model into production, you may first need to clear compliance hurdles. You should first identify potential compliance risks, with each additional step again tested against risks. Typically, these areas require the most attention: model development, implementation, and use. Knowing When to Trust a Model.

Uncertainty 52

Uncertainty Machine Learning Advertising Risk 52

Smart Data Collective

AUGUST 18, 2021

Fortunately, recruitment software and tools allow for data-driven decision-making that eliminates human bias and uncertainties, ultimately helping you make better decisions during the hiring process with greater accuracy and peace of mind. Speed up the recruitment process. Top talent is typically hired by recruiters within ten days.

Data Science 137

Data Science Management Big Data Metrics 137

Jet Global

JUNE 8, 2021

In periods of great uncertainty, organizations forecast more frequently in the hope that it will give them a better handle on their trading prospects, levels of activity, and resources needed for the coming months. The table shows the percentage of organizations that satisfied each stress test.

Forecasting 98

Forecasting Uncertainty Cost-Benefit Reporting 98

Cloudera

DECEMBER 11, 2020

Insurance and finance are two industries that rely on measuring risk with historical data models. To facilitate risk modeling in this new normal, agility and flexibility is required. Data Variety. This will only become more important as we move into 2021 and a post-pandemic new normal.

Insurance 95

Insurance Digital Transformation Unstructured Data Machine Learning 95

CIO Business Intelligence

OCTOBER 18, 2023

If anything, 2023 has proved to be a year of reckoning for businesses, and IT leaders in particular, as they attempt to come to grips with the disruptive potential of this technology — just as debates over the best path forward for AI have accelerated and regulatory uncertainty has cast a longer shadow over its outlook in the wake of these events.

Risk 140

Risk Manufacturing Enterprise Technology 140

CIO Business Intelligence

JULY 31, 2023

As vendors add generative AI to their enterprise software offerings, and as employees test out the tech, CIOs must advise their colleagues on the pros and cons of gen AI’s use as well as the potential consequences of banning or limiting it. How has, say, ChatGPT hit your business model?” How is your business impacted by generative AI?

Strategy 98

Strategy Risk Enterprise Risk Management 98

CIO Business Intelligence

JULY 7, 2023

This module validates your ability to measure, assess, and develop the Service Desk practice capability using the ITIL Maturity Model. You’ll be tested on a situation of your choosing, so the material will be personal to your experience.

Cost-Benefit 98

Cost-Benefit Strategy Management Uncertainty 98

Domino Data Lab

FEBRUARY 20, 2019

“The last company I worked for was a very interesting story as well, because I joined the company that had a very good established culture of software development…with tests, with CI/CD, experienced engineers, experienced engineering management, and product management. Unit tests, integration tests, CI/CD, documentation.

Data Science 76

Data Science Testing Software Uncertainty 76

CIO Business Intelligence

JUNE 28, 2022

More importantly, we also have statistical models that draw error bars that delineate the limits of our analysis. Others are philosophical, testing our ability to reason about abstract qualities. Good data scientists can also reduce some of this uncertainty through cleansing.

Management 137

Management Internet of Things Statistics Data-driven 137

Cloudera

MAY 15, 2018

Over the past decade, we have observed open source powered big data and analytics platforms evolve from large data storage containers to massively scalable advanced modeling platforms that seamlessly operate on-premises and in a multi-cloud environment. Probability, Uncertainty and Quantitative Risk (2017) 2:6. Mauro Cesa. “A

Machine Learning 42

Machine Learning Recreation/Entertainment Finance Big Data 42

Cloudera

OCTOBER 21, 2020

Today’s models, norms, and averages are being re-written on the fly, with insurers forced to cope with the inevitable conflict between old standards and the new normal. . Along the way, tried and tested models and processes are proving unreliable, triggering an evolution in the insurance industry.

Insurance 74

Insurance Unstructured Data Digital Transformation Cost-Benefit 74

Jet Global

NOVEMBER 4, 2020

Intangible-asset transactions present a challenge when organizations are quantifying prices and profits to serve their transfer pricing models. Certain authorities may have different preferences or expectations when it comes to adjustments, even in a period of economic uncertainty.

Risk 98

Risk Uncertainty Sales Strategy 98

DataKitchen

SEPTEMBER 21, 2023

The uncertainty of not knowing where data issues will crop up next and the tiresome game of ‘who’s to blame’ when pinpointing the failure. 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 176

Testing Data Quality Predictive Modeling Metrics 176