CIO Business Intelligence

FEBRUARY 8, 2024

The global IT services industry is at a significant crossroads, with the explosive growth of generative AI and deepening economic uncertainties reshaping its future. Although there are efforts to boost industries such as semiconductors, there is much uncertainty about when the impact may be seen.

IT 89

IT Uncertainty Consulting Forecasting 89

CIO Business Intelligence

JUNE 23, 2023

Respondents were asked about their current IT stressors, their approach to modernizing their IT infrastructure, and how they plan to become more efficient and optimized in the years ahead. It helps reduce risk, increase efficiency, optimize resources, and improve both the customer and employee experience.

IT 97

IT Risk Management Risk Optimization 97

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. Given this, it’s crucial to have in Place meticulous testing protocols for the results of models, visualizations, data delivery mechanisms, and overall data utilization.

Testing 169

Testing Data Quality Predictive Modeling Metrics 169

The Unofficial Google Data Science Blog

APRIL 19, 2021

by LEE RICHARDSON & TAYLOR POSPISIL Calibrated models make probabilistic predictions that match real world probabilities. While calibration seems like a straightforward and perhaps trivial property, miscalibrated models are actually quite common. Why calibration matters What are the consequences of miscalibrated models?

Modeling 122

Modeling IT Metrics Testing 122

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 Models also become stale and outdated over time.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

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

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 119

ROI Cost-Benefit KPI Uncertainty 119

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 120

Modeling Forecasting Reporting Risk 120

CIO Business Intelligence

OCTOBER 4, 2022

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.” But the urgency and the upside of modernizing and optimizing the data architecture keeps coming into sharper focus. Data architecture coherence.

Machine Learning 106

Machine Learning Data Architecture Uncertainty Data-driven 106

CIO Business Intelligence

APRIL 28, 2024

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. We believe that the wireless private network is the optimal solution when wireless spectrum resources are available.

Interactive 76

Interactive Uncertainty Data Collection IoT 76

CIO Business Intelligence

DECEMBER 18, 2023

A primary fear is that employees, partners, and organizational stakeholders might share everything from private data to source code into public large language models (LLMs), expose proprietary information and intellectual property, or reveal vulnerabilities to exploit. government’s attention.

Enterprise 114

Enterprise Management Risk Uncertainty 114

BI-Survey

FEBRUARY 14, 2022

Overnight, the impact of uncertainty, dynamics and complexity on markets could no longer be ignored. Local events in an increasingly interconnected economy and uncertainties such as the climate crisis will continue to create high volatility and even chaos. The COVID-19 pandemic caught most companies unprepared. BARC Recommendations.

Forecasting 52

Forecasting Uncertainty Measurement Software 52

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 94

Cost-Benefit Modeling Manufacturing Interactive 94

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 137

Risk Manufacturing Enterprise Technology 137

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. That’s why it is important to implement a secure BI cloud tool that can leverage proper security measures. Cost management and containment. Governance/Control.

Risk 237

Risk Cost-Benefit Business Intelligence Data-driven 237

CIO Business Intelligence

JANUARY 4, 2023

Here are the shifts we noted: Delivery Models : Moving from an almost strictly on-premises systems approach (with some remote access services), HPC is embracing remote delivery models. 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

The Unofficial Google Data Science Blog

DECEMBER 4, 2019

by THOMAS OLAVSON Thomas leads a team at Google called "Operations Data Science" that helps Google scale its infrastructure capacity optimally. Others argue that there will still be a unique role for the data scientist to deal with ambiguous objectives, messy data, and knowing the limits of any given model.

Forecasting 113

Forecasting Data Science Statistics Uncertainty 113

Perceptual Edge

APRIL 21, 2019

Every choice that we make when creating a data visualization seeks to optimize the signal-to-noise ratio. Seeing the actual data as well helps us keep in mind that statistical models are estimates, built on assumptions, which are never entirely true.

Visualization 76

Visualization Statistics Uncertainty Modeling 76

CIO Business Intelligence

SEPTEMBER 12, 2022

One instance of how that exploration led to real business benefits was with the application of machine learning to predict optimal product formulation using a set of desired consumer benefits. The team was given time to gather and clean data and experiment with machine learning models,’’ Crowe says. Elixirr Consulting.

Experimentation 131

Experimentation Consulting Technology Machine Learning 131

Occam's Razor

APRIL 8, 2013

Sometimes, we escape the clutches of this sub optimal existence and do pick good metrics or engage in simple A/B testing. Let's listen in as Alistair discusses the lean analytics model… The Lean Analytics Cycle is a simple, four-step process that shows you how to improve a part of your business. But it is not routine.

Metrics 156

Metrics KPI Analytics Key Performance Indicator 156

Sisense

OCTOBER 6, 2020

Smart use of your data can be the key to optimizing processes, identifying new opportunities, and gaining or keeping a competitive edge. Most commonly, we think of data as numbers that show information such as sales figures, marketing data, payroll totals, financial statistics, and other data that can be counted and measured objectively.

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

Jet Global

MAY 10, 2021

At a time of great uncertainty, the role of finance professionals has, of necessity, evolved into an ever more strategic one. The viability of new revenue models or investment opportunities. Improving and optimizing supplier management. Optimizing accounts payable. Automating processes when possible.

Finance 98

Finance Recreation/Entertainment Reporting Uncertainty 98

bridgei2i

JUNE 3, 2020

Consumers feel threatened by the prolonged uncertainty, not having had to deal with anything like it, in their lives. Difficulties in forecasting & planning: Pre-COVID forecasts are no longer valid as the pandemic has entirely disrupted the market and enterprises would need to work on new models to predict KPIs.

Manufacturing 52

Manufacturing Forecasting Uncertainty Digital Transformation 52

bridgei2i

JULY 8, 2020

This is probably the first time ever that we are witnessing a demand, a supply, and also a resource uncertainty. And if you’re a banker or an insurer, you’re probably busy figuring out how to measure these risks, mobilize these resources, and fund capital that’s going to provide strong growth. These are strange times.

Digital Transformation 132

Digital Transformation Enterprise Insurance Risk 132

Cloudera

NOVEMBER 19, 2018

One of Cloudera’s partners offers “Sustainability Services” with a goal of assisting organizations in turning costs and risks associated with changing regulatory and workforce environments, as well as supply chain uncertainties and volatile markets, into business opportunities. Maximizing efficiencies in aquaponics.

Digital Transformation 40

Digital Transformation IoT Cost-Benefit Uncertainty 40

The Unofficial Google Data Science Blog

APRIL 16, 2019

Modern products often don't start with set-in-stone business models because starting and scaling costs are low. The metrics to measure the impact of the change might not yet be established. It can provide a post hoc measure of eventual impact, and hence insight into what the product might try next.

Experimentation 68

Experimentation Sales Metrics Measurement 68

The Unofficial Google Data Science Blog

JULY 22, 2020

For this reason we don’t report uncertainty measures or statistical significance in the results of the simulation. In practice, one may want to use more complex models to make these estimates. For example, one may want to use a model that can pool the epoch estimates with each other via hierarchical modeling (a.k.a.

Experimentation 95

Experimentation Statistics Testing Strategy 95

bridgei2i

MAY 4, 2020

So the COVID-19 crisis response has hence been centrifugal, and it has varied across countries with respect to infections, control, and lockdown measures. While customer confidence also takes time to recover from rising unemployment, the economic uncertainty, and anxiousness. So the focus here is also to protect lives and livelihoods.

Enterprise 91

Enterprise Digital Transformation Sales Recreation/Entertainment 91

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

This problem can be phrased as an optimization problem — given some fixed review capacity how should we sample videos? 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.

Metrics 98

Metrics Statistics Uncertainty Optimization 98

The Unofficial Google Data Science Blog

APRIL 17, 2017

For us, demand for forecasts emerged from a determination to better understand business growth and health, more efficiently conduct day-to-day operations, and optimize longer-term resource planning and allocation decisions. Selection and aggregation of forecasts from an ensemble of models to produce a final forecast.

Forecasting 83

Forecasting Modeling Statistics Uncertainty 83

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. To create enough uncertainty to fuzzy up any negative – or remotely negative – data. Sadly still, negative data to the person/team receiving it.

Measurement 79

Measurement Strategy Data Processing Uncertainty 79

Smart Data Collective

APRIL 18, 2019

While the shared security model is taking some security pressure off the SOC, enterprises who have migrated infrastructure, platforms, and apps do not shed all security responsibilities. Uncertainties are a major roadblock in automating cybersecurity. Cloud Technologies: The cloud can also be overhyped. That’s the best approach.

Behavioral Analytics 77

Behavioral Analytics Advertising Uncertainty Machine Learning 77