CIO Business Intelligence

SEPTEMBER 2, 2022

The approach we use is to develop analytical models based on use cases, with a clear definition of business problems and value. So far, we have deployed roughly 71 models with a clear operating income and impact on the business. I imagine these models have a direct impact on the customer experience. Khare: Yes, they do.

Uncertainty 98

Uncertainty Manufacturing Data-driven Business Intelligence 98

The Unofficial Google Data Science Blog

DECEMBER 4, 2019

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. This classification is based on the purpose, horizon, update frequency and uncertainty of the forecast.

Forecasting 115

Forecasting Data Science Statistics Uncertainty 115

BizAcuity

MARCH 18, 2019

Credit scoring systems and predictive analytics model attempt to quantify uncertainty and provide guidance for identifying, measuring and monitoring risk. Benefits of Predictive Analytics in Unsecured Consumer Loan Industry. The consumer lending business is centered on the notion of managing the risk of borrower default.

Predictive Analytics 83

Predictive Analytics Analytics Data mining Cost-Benefit 83

Sisense

SEPTEMBER 9, 2019

We fed Kraken (BigSquid’s predictive analytics engine) information about historical warranty costs, claims, forecasts, historical product attributes, and attributes of the new products on the roadmap. Then we ran Kraken’s machine learning and predictive modeling engine to get the results. It will be iterative.

Predictive Analytics 75

Predictive Analytics Predictive Modeling Data-driven Forecasting 75

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. At RetailZoom , a team of data scientists supplies supermarkets and FMCG companies with predictive models that incorporate transactional and demographic data to determine the size and scope of promotional activities.

Analytics 94

Analytics Sales Forecasting Business Intelligence 94

BI-Survey

MARCH 16, 2021

Markets and competition today are highly dynamic and complex, and the future is characterized by uncertainty – not least because of COVID-19. This uncertainty is currently at the forefront of everyone‘s minds. 75 percent of companies confirm that predictive models provide good forecasts for them, even in volatile markets.

Forecasting 52

Forecasting Management Uncertainty Predictive Modeling 52

BI-Survey

MARCH 16, 2021

Markets and competition today are highly dynamic and complex, and the future is characterized by uncertainty – not least because of COVID-19. This uncertainty is currently at the forefront of everyone‘s minds. 75 percent of companies confirm that predictive models provide good forecasts for them, even in volatile markets.

Forecasting 52

Forecasting Management Uncertainty Predictive Modeling 52

The Unofficial Google Data Science Blog

MARCH 31, 2016

KUEHNEL, and ALI NASIRI AMINI In this post, we give a brief introduction to random effects models, and discuss some of their uses. Through simulation we illustrate issues with model fitting techniques that depend on matrix factorization. Random effects models are a useful tool for both exploratory analyses and prediction problems.

Modeling 40

Modeling Statistics Advertising Testing 40

CIO Business Intelligence

AUGUST 7, 2023

Foundry / State of the CIO That distinct view, coupled with ongoing pressure to accelerate digital business brought on by pandemic-era changes and economic uncertainties , have launched CIOs into the change management hot seat.

IT 98

IT Sales Manufacturing Cost-Benefit 98

CIO Business Intelligence

APRIL 11, 2023

Mistake 1: undisciplined growth Leaders are facing times of uncertainty, magnified recently with the collapse of Silicon Valley Bank and ongoing market turmoil. They have a paradigm called the “continuous learning machine,” where engineers use AI to automate their repetitive work tasks and build predictive models to help with productivity.

Uncertainty 52

Uncertainty Predictive Modeling Risk Technology 52

O'Reilly on Data

SEPTEMBER 11, 2019

2 in frequency in proposal topics; a related term, “models,” is No. An ML-related topic, “models,” was No. For example, even though ML and ML-related concepts —a related term, “ML models,” (No. But the database—or, more precisely, the data model —is no longer the sole or, arguably, the primary focus of data engineering.

IoT 26

IoT Big Data Data Warehouse Uncertainty 26

Insight

FEBRUARY 19, 2020

Arthur de Vany’s Hollywood Economics and Kaggle’s recent box office prediction challenge ) and current attempts are using increasingly sophisticated techniques. Feature Selection and Engineering Most of the inputs to my model were taken either as is from the data source, or with minimal processing.

Risk 67

Risk ROI Modeling Metrics 67