O'Reilly on Data

MARCH 31, 2020

This means that the AI products you build align with your existing business plans and strategies (or that your products are driving change in those plans and strategies), that they are delivering value to the business, and that they are delivered on time. Machine learning adds uncertainty.

Management 332

Management Machine Learning Experimentation Metrics 332

Cloudera

DECEMBER 3, 2021

This involves identifying, quantifying and being able to measure ethical considerations while balancing these with performance objectives. 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. Governance.

Uncertainty 103

Uncertainty Measurement Metrics Risk 103

CIO Business Intelligence

OCTOBER 4, 2022

By Bryan Kirschner, Vice President, Strategy at DataStax. In the new report, titled “Digital Transformation, Data Architecture, and Legacy Systems,” researchers defined a range of measures of what they summed up as “data architecture coherence.” About Bryan Kirschner : Bryan is Vice President, Strategy at DataStax.

Machine Learning 118

Machine Learning Data Architecture Uncertainty Data-driven 118

IBM Big Data Hub

FEBRUARY 20, 2024

These proactive measures are made possible by evolving technologies designed to help people adapt to the effects of climate change today. Climate models provide answers Human activities precipitated changes to the Earth’s climate in the 20th century and will largely determine the future climate.

Modeling 123

Modeling Forecasting Reporting Risk 123

CIO Business Intelligence

MAY 9, 2023

Like most CIOs you’ve no doubt leaned on ROI, TCO and KPIs to measure the business value of your IT investments. Those Three Big Acronyms are still important for fine-tuning your IT operations, but success today is increasingly measured in business outcomes. Maybe you’ve even surpassed expectations in each of these yardsticks.

ROI 126

ROI Cost-Benefit KPI Uncertainty 126

CIO Business Intelligence

JULY 23, 2023

EY recently found that in current economic and financial uncertainty, 94% of tech executives plan to increase their IT investment over the next year. Optimization also rose to the top of IT leaders’ lists: 67% measure success within their IT organization by better optimizing resources.

Optimization 94

Optimization IT Digital Transformation Uncertainty 94

CIO Business Intelligence

JUNE 23, 2023

Sixty-five percent of respondents cited implementing a hybrid cloud strategy as a top priority. An astounding 93% of respondents noted they strongly agree with the sentence, “I believe my organization needs to embrace a hybrid infrastructure model that spans from mainframe to cloud.”

IT 98

IT Risk Management Risk Optimization 98

Smart Data Collective

JULY 1, 2023

Image annotation is the act of labeling images for AI and machine learning models. This helps train the AI model by assigning classes to different entities in an image. Improving annotation quality is crucial for various tasks, including data labeling for machine learning models, document categorization, sentiment analysis, and more.

Metrics 64

Metrics Machine Learning Uncertainty Deep Learning 64

CIO Business Intelligence

FEBRUARY 23, 2023

By Bryan Kirschner, Vice President, Strategy at DataStax Imagine getting a recommendation for the perfect “rainy Sunday playlist” midway through your third Zoom meeting on Monday. The former rely on batch processing to train machine learning models and generate features (measurable properties of a phenomenon).

Uncertainty 98

Uncertainty Strategy Data-driven Machine Learning 98

CIO Business Intelligence

SEPTEMBER 20, 2023

They are afraid of failure and the uncertainty of knowledge work, and so that’s stressful. Agile is an amazing risk management tool for managing uncertainty, but that’s not always obvious.” The key is recognizing that planning must be an agile discipline, not a standalone activity performed independently of agile teams.

Digital Transformation 135

Digital Transformation Uncertainty Metrics Business Objectives 135

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

IBM Big Data Hub

OCTOBER 18, 2022

Nearly all CEOs say they’re at least taking their first steps in piloting their sustainability strategy. CEOs identify a range of challenges both within and beyond their organizations, and only a quarter report active implementation of their sustainability strategy across their entire enterprise. A rising tide lifts all boats.

Uncertainty 52

Uncertainty Strategy Measurement Digital Transformation 52

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 7, 2023

This module validates your ability to measure, assess, and develop the Service Desk practice capability using the ITIL Maturity Model. This certification focuses on how IT influences and informs business strategy. Careers, Certifications, CIO, IT Leadership, IT Strategy, ITIL, System Management

Cost-Benefit 98

Cost-Benefit Strategy Management Uncertainty 98

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 96

Cost-Benefit Modeling Manufacturing Interactive 96

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 141

Risk Manufacturing Enterprise Technology 141

BizAcuity

MARCH 18, 2019

Credit scoring systems and predictive analytics model attempt to quantify uncertainty and provide guidance for identifying, measuring and monitoring risk. It helps recognize churn patterns and develop profiles of users who have left, to get an insight of why they left and formulate strategies to keep them engaged in future.

Predictive Analytics 83

Predictive Analytics Analytics Cost-Benefit Data mining 83

Jet Global

JULY 23, 2020

Fortunately, the level of uncertainty has fallen considerably, as many businesses are beginning to re-open, albeit with some restrictions and under capacity restrictions. Maintain close relationships with key suppliers and consider taking measures to defend against supply chain interruptions. Continue to Run Lean.

Uncertainty 95

Uncertainty Finance Cost-Benefit Reporting 95

CIO Business Intelligence

JANUARY 4, 2023

Scaling out and developing large-scale systems : To meet demand, the HPC industry is developing and honing strategies to effectively scale and deploy large systems that are both efficient and reliable. Due to the rapid growth in data sizes, there’s an increased need for HPC solutions that can run large training models.

Cost-Benefit 59

Cost-Benefit Machine Learning Modeling Uncertainty 59

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 96

Insurance Digital Transformation Unstructured Data Machine Learning 96

Sisense

MARCH 24, 2020

Now is the time to apply the full force of business intelligence used by analytics teams to help navigate growing uncertainty. With smart dashboards and KPIs , the BraunAbility team is able to tie discount data from marketing platforms to sales results in order to more effectively measure the impact of any discount.

Analytics 94

Analytics Sales Forecasting Business Intelligence 94

CIO Business Intelligence

SEPTEMBER 12, 2022

The team was given time to gather and clean data and experiment with machine learning models,’’ Crowe says. It requires bold bets and a willingness to persevere despite setbacks, criticism, and uncertainty,’’ wrote McKinsey senior partners Laura Furstenthal and Erik Roth in a recent blog post. “By Elixirr Consulting.

Experimentation 133

Experimentation Consulting Technology Machine Learning 133

Sisense

SEPTEMBER 9, 2019

Then we ran Kraken’s machine learning and predictive modeling engine to get the results. Following a few false starts and some great iterative learning with the BigSquid team, we came away with a solid predictive data model of the warranty costs for future periods. Using Sentiment Analytics to Inform New Product Design Decisions.

Predictive Analytics 75

Predictive Analytics Predictive Modeling Forecasting Data-driven 75

The Unofficial Google Data Science Blog

APRIL 23, 2024

the weight given to Likes in our video recommendation algorithm) while $Y$ is a vector of outcome measures such as different metrics of user experience (e.g., Crucially, it takes into account the uncertainty inherent in our experiments. It is also a sound strategy when experimenting with several parameters at the same time.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

Cloudera

NOVEMBER 19, 2018

To achieve success, they must formulate and implement strategies for sustainability that encompass not just environmental (“green”) issues, but also social, economic, and cultural concerns. Companies that fail to embrace this responsibility threaten their own survival.

Digital Transformation 40

Digital Transformation IoT Cost-Benefit Uncertainty 40

Occam's Razor

APRIL 15, 2019

A decade ago, data people delivered a lot less bad news because so little could be measured with any degree of confidence. In 2019, we can measure the crap out of so much. Short-term, this let’s not listen to the negative data strategy sometimes actually works. Sadly still, negative data to the person/team receiving it.

Measurement 79

Measurement Strategy Data Processing Uncertainty 79

bridgei2i

JULY 8, 2020

What are you hearing from clients, and what strategies are they adopting to remain resilient at these hard times? This is probably the first time ever that we are witnessing a demand, a supply, and also a resource uncertainty. Can we model the impact for such structural shocks? What are you seeing as emerging themes?

Digital Transformation 132

Digital Transformation Enterprise Insurance Risk 132

The Unofficial Google Data Science Blog

APRIL 17, 2017

Selection and aggregation of forecasts from an ensemble of models to produce a final forecast. Quantification of forecast uncertainty via simulation-based prediction intervals. Calendaring was therefore an explicit feature of models within our framework, and we made considerable investment in maintaining detailed regional calendars.

Forecasting 83

Forecasting Modeling Statistics Uncertainty 83

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. Running these automated tests as part of your DataOps and Data Observability strategy allows for early detection of discrepancies or errors. One of the primary sources of tension?

Testing 176

Testing Data Quality Predictive Modeling Metrics 176

O'Reilly on Data

SEPTEMBER 15, 2020

In my book, I introduce the Technical Maturity Model: I define technical maturity as a combination of three factors at a given point of time. Technical sophistication: Sophistication measures a team’s ability to use advanced tools and techniques (e.g., Technical competence results in reduced risk and uncertainty.

Cost-Benefit 293

Cost-Benefit Advertising ROI Machine Learning 293

datapine

MAY 31, 2022

More and more CRM, marketing, and finance-related tools use SaaS business intelligence and technology, and even Adobe’s Creative Suite has adopted the model. We discussed already some of these cloud computing challenges when comparing cloud vs on premise BI strategies. Cost management and containment.

Risk 237

Risk Cost-Benefit Business Intelligence Data-driven 237

CIO Business Intelligence

APRIL 28, 2024

Carbon neutrality and carbon peak strategies are driving the adoption of new energy worldwide. However, new energy is restricted by weather and climate, which means extreme weather conditions and unpredictable external environments bring an element of uncertainty to new energy sources.

Interactive 94

Interactive Uncertainty Data Collection IoT 94

CIO Business Intelligence

JUNE 8, 2022

Digital disruption, global pandemic, geopolitical crises, economic uncertainty — volatility has thrown into question time-honored beliefs about how best to lead IT. Thriving amid uncertainty means staying flexible, he argues. . Develop and constantly amend the models for scaling technology.”. IT Leadership, IT Strategy

IT 133

IT Cost-Benefit Uncertainty Digital Transformation 133

The Unofficial Google Data Science Blog

JULY 22, 2020

by ALEXANDER WAKIM Ramp-up and multi-armed bandits (MAB) are common strategies in online controlled experiments (OCE). These strategies involve changing assignment weights during an experiment. The first is a strategy called ramp-up and is advised by many experts in the field [1].

Experimentation 95

Experimentation Statistics Testing Strategy 95

O'Reilly on Data

JULY 20, 2021

When we’re building shared devices with a user model, that model quickly runs into limitations. That model doesn’t fit reality: the identity of a communal device isn’t a single person, but everyone who can interact with it. This measurement of trust and risk is benefited by understanding who could be in front of the device.

Risk 304

Risk Software Interactive Modeling 304

Domino Data Lab

JUNE 23, 2019

These measurement-obsessed companies have an advantage when it comes to AI. Google, Facebook, other leaders, they really have set up a culture of extreme measurement where every part of their product experience is instrumented to optimize clicks and drive user engagement. There’s no substitute for that experience.

Management 110

Management Machine Learning Experimentation Metrics 110

The Unofficial Google Data Science Blog

AUGUST 27, 2019

The measurement may be biased if our samples are generated from a procedure that samples without replacement, such as reservoir sampling , especially if some items have disproportionate weight, i.e., $p(v_i) cdot n$ is large. There are many strategies we can use to estimate this quantity, and we will discuss each option in detail.

Metrics 98

Metrics Statistics Uncertainty Optimization 98