Domino Data Lab

AUGUST 1, 2021

In this article we cover explainability for black-box models and show how to use different methods from the Skater framework to provide insights into the inner workings of a simple credit scoring neural network model. The interest in interpretation of machine learning has been rapidly accelerating in the last decade. See Ribeiro et al.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

CIO Business Intelligence

JULY 5, 2022

Business analytics is the practical application of statistical analysis and technologies on business data to identify and anticipate trends and predict business outcomes. Data analytics is used across disciplines to find trends and solve problems using data mining , data cleansing, data transformation, data modeling, and more.

Business Analytics 125

Business Analytics Prescriptive Analytics Data mining Diagnostic Analytics 125

Rocket-Powered Data Science

JULY 13, 2023

Beyond the early days of data collection, where data was acquired primarily to measure what had happened (descriptive) or why something is happening (diagnostic), data collection now drives predictive models (forecasting the future) and prescriptive models (optimizing for “a better future”).

Analytics 166

Analytics Machine Learning Deep Learning Data Science 166

Smarten

APRIL 25, 2024

Artificial Intelligence (AI) and Machine Learning (ML) elements support Citizen Data Scientists and help users prepare data, achieve automated data insights and create, share and use predictive models. These measures empower them with a deeper understanding of their data like never before.

Data Quality 62

Data Quality Analytics Machine Learning Visualization 62

Smarten

MAY 29, 2023

World-renowned technology analysis firm Gartner defines the role this way, ‘A citizen data scientist is a person who creates or generates models that leverage predictive or prescriptive analytics, but whose primary job function is outside of the field of statistics and analytics. ‘If Automatic generation of models.

Prescriptive Analytics 52

Prescriptive Analytics Predictive Modeling Digital Transformation Business Objectives 52

Smarten

MARCH 13, 2024

Augmented Analytics and Citizen Data Scientists are not meant to replace refined data modeling or the role of Data Scientists, but rather can supplement and support analytics across the enterprise. Nothing could be further from the truth. and then share and collaborate with the team to further analyze and discuss the issues.

Analytics 52

Analytics Predictive Modeling Strategy Enterprise 52

O'Reilly on Data

MAY 18, 2020

This article answers these questions, based on our combined experience as both a lawyer and a data scientist responding to cybersecurity incidents, crafting legal frameworks to manage the risks of AI, and building sophisticated interpretable models to mitigate risk. All predictive models are wrong at times?—just

Risk 359

Risk Modeling Data Processing Software 359

Smarten

APRIL 12, 2023

Smarten Augmented Analytics tools include Assisted Predictive Modeling , Smart Data Visualization , Self-Serve Data Preparation , Sentiment Analysis , and Clickless Analytics with natural language processing (NLP) for search analytics.

Snapshot 52

Snapshot Key Performance Indicator KPI Business Intelligence 52

BizAcuity

APRIL 1, 2023

Predictive modeling for flagging suspicious activity Predictive analytics can be used to analyze past customer behavior and transactions to identify patterns that may indicate potential money laundering activity. Building a predictive model is a continuous process and commitment. This is not the final step.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

FineReport

APRIL 9, 2024

From advanced analytics to predictive modeling, the evolving landscape of business intelligence is revolutionizing how data is processed and leveraged for actionable insights. Proactive Risk Management : BI tools enable organizations to proactively identify potential risks through predictive modeling and trend analysis.

Business Intelligence 52

Business Intelligence Software Data-driven Predictive Modeling 52

Domino Data Lab

NOVEMBER 17, 2020

High throughput screening technologies have been developed to measure all the molecules of interest in a sample in a single experiment (e.g., Predictive models fit to noise approach 100% accuracy. For example, it’s impossible to know if your predictive model is accurate because it is fitting important variables or noise.

Statistics 131

Statistics Measurement Testing Predictive Modeling 131

BizAcuity

JANUARY 18, 2023

Predictive modeling for flagging suspicious activity. Predictive analytics can be used to analyze past customer behavior and transactions to identify patterns that may indicate potential money laundering activity. Steps to building a highly accurate predictive model for AML. These include-.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

DataKitchen

JUNE 19, 2023

Our customers start looking at the data in dashboards and models and then find many issues. It involves tracking key metrics such as system health indicators, performance measures, and error rates and closely scrutinizing system logs to identify anomalies or errors. In our experience, the locus of those problems changes over time.

Testing 130

Testing Cost-Benefit Metrics Data Quality 130

datapine

NOVEMBER 27, 2019

While we work on programs to avoid such inconvenience , AI and machine learning are revolutionizing the way we interact with our analytics and data management while increment in security measures must be taken into account. Any difference between predicted data and real value is used by the moving average (MA) part.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

CIO Business Intelligence

SEPTEMBER 5, 2023

By embracing machine learning and predictive analytics from SAP, it has been able to build predictive models for abnormal events based on sensor data and feed them into user-friendly dashboards and e-mail notifications. These are just two examples of what’s already happening when AI is embedded into cloud solutions.

Technology 84

Technology Predictive Modeling Predictive Analytics Forecasting 84

CIO Business Intelligence

JULY 24, 2023

It has also developed predictive models to detect trends, make predictions, and simulate results. AI takes that data and combines it with historical tracking data from about 2,000 matches to create new insights, such as the Goal Probability model, one of 21 new stats it debuted in 2022.

Broadcasting 84

Broadcasting Recreation/Entertainment Testing Machine Learning 84

Smarten

JUNE 17, 2022

.” The Information Technology Amendment Act of 2009 designated CERT-IN as the national agency to perform functions for cyber security, including the collection, analysis and dissemination of information on cyber incidents, as well as taking emergency measures to handle incidents and coordinating cyber incident response activities.

Analytics 67

Analytics IT Business Intelligence Predictive Modeling 67

O'Reilly on Data

JUNE 18, 2019

There has been a significant increase in our ability to build complex AI models for predictions, classifications, and various analytics tasks, and there’s an abundance of (fairly easy-to-use) tools that allow data scientists and analysts to provision complex models within days. Data integration and cleaning.

Machine Learning 259

Machine Learning Data Quality Statistics Modeling 259

bridgei2i

AUGUST 28, 2020

A leading CPG manufacturer wanted to create a centralized planning system backed by AI-driven predictive modelling to drive consensus across multiple business functions and leverage synergy. Case study: Integrated Business Planning – Provides continuous visibility and drives consensus. Business Context.

Business Driver 52

Business Driver Predictive Modeling Manufacturing Forecasting 52

BI-Survey

JANUARY 29, 2023

In the context of corporate planning, predictive planning and forecasting, it is therefore a major trend to use predictive models based on statistical methods and ML for forecasting and thorough analysis. Nearly every organization that adopts predictive planning is likely to profit from it.

Forecasting 52

Forecasting Predictive Modeling Measurement Finance 52

DataRobot Blog

JUNE 23, 2022

Human intuition is relied on, or an older, hand-build BI/predictive model exists, or perhaps a set of heuristics were documented that more or less predict something. Go Beyond Predictions. Far fewer AI models succeed in creating business value when there is no existing prediction to replace. Learn More.

Predictive Modeling 59

Predictive Modeling Modeling Data Science Measurement 59

CIO Business Intelligence

JUNE 7, 2022

Data analytics draws from a range of disciplines — including computer programming, mathematics, and statistics — to perform analysis on data in an effort to describe, predict, and improve performance. Predictive analytics is often considered a type of “advanced analytics,” and frequently depends on machine learning and/or deep learning.

Data Analytics 128

Data Analytics Diagnostic Analytics Management Analytics 128

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.” Data architecture coherence. more machine learning use casesacross the company.

Machine Learning 97

Machine Learning Data Architecture Uncertainty Data-driven 97

Smarten

NOVEMBER 22, 2019

Augmented analytics and tools like Smart Visualization and Self-Serve Data Preparation , as well as Assisted Predictive Modeling can provide guidance and auto-suggestions and recommendations to make users more comfortable in adopting analytics and achieving positive outcomes.

Predictive Modeling 67

Predictive Modeling Data-driven Forecasting Visualization 67

Smarten

JULY 31, 2019

How does one measure the effectiveness of a new Augmented Data Discovery solution? Once the business has chosen data democratization and implemented a self-serve analytics solution, it must measure ROI & TCO and establish metrics that will compare business results achieved before and after the implementation.

Predictive Modeling 40

Predictive Modeling Metrics Measurement ROI 40

Business Over Broadway

SEPTEMBER 27, 2018

In this paper, I show you how marketers can improve their customer retention efforts by 1) integrating disparate data silos and 2) employing machine learning predictive analytics. Your marketing strategy is only as good as your ability to deliver measurable results. Machine Learning and Predictive Modeling of Customer Churn.

Machine Learning 76

Machine Learning Data Integration Marketing Predictive Modeling 76

FineReport

APRIL 21, 2024

By embracing SaaS BI tools , businesses can unlock enhanced scalability, faster implementation, and robust security measures while empowering users with self-service analytics capabilities. However, SaaS BI tools address this challenge by offering user-friendly interfaces that simplify the process of data preparation, modeling, and analysis.

Business Intelligence 52

Business Intelligence Visualization Dashboards Data-driven 52

CIO Business Intelligence

JUNE 22, 2022

Predictive maintenance applications enable large-scale manufacturers to collect telemetry data and integrate all IoT functions, and these are powered by models driven by real-time data. . Just as important is the dimension of data accuracy or other measures of performance.

IoT 87

IoT IT Manufacturing Internet of Things 87

IBM Big Data Hub

JUNE 29, 2023

First, availability measures the operational capacity of an asset over time. While reliability and availability are both measured in percentages, it’s possible—even likely—that these percentages will differ even when referring to the same piece of equipment.

Cost-Benefit 84

Cost-Benefit Measurement Management Predictive Analytics 84

Domino Data Lab

OCTOBER 7, 2020

The Curse of Dimensionality , or Large P, Small N, ((P >> N)) , problem applies to the latter case of lots of variables measured on a relatively few number of samples. Statistics developed in the last century are based on probability models (distributions). The accuracy of any predictive model approaches 100%.

Statistics 145

Statistics Testing Predictive Modeling Modeling 145

DataRobot

NOVEMBER 29, 2021

We’ll focus on evaluating a model for biased behavior, which can occur during the training process or after it has been deployed in a production environment. . A model is biased when it predicts different outcomes for features in the training dataset. As with model accuracy, there are many metrics one can use to measure bias.

Technology 52

Technology Metrics Predictive Modeling Modeling 52

Paul Blogs on BI

MARCH 25, 2020

We are really missing data and so the metrics are incomplete and, as such, we should ask ourselves the question: “Are we measuring the right things?”. Some universities and institutions have built out predictive models based on this data which are even more likely to be erroneous. Stay healthy.

Business Intelligence 51

Business Intelligence Measurement Metrics Cost-Benefit 51

DataRobot Blog

JULY 28, 2022

Companies are emphasizing the accuracy of machine learning models while at the same time focusing on cost reduction, both of which are important. In addition to the accuracy of the models we built, we had to consider business metrics, cost, interpretability, and suitability for ongoing operations. Sensor Data Analysis Examples.

Data Science 72

Data Science Machine Learning Statistics Modeling 72

CIO Business Intelligence

MAY 26, 2022

Expectedly, advances in artificial intelligence (AI), machine learning (ML), and predictive modeling are giving enterprises – as well as small/medium-sized businesses – a never-before opportunity to automate their recruitment even as they deal with radical changes in workplace practices involving remote and hybrid work.

Advertising 115

Advertising Machine Learning Software Measurement 115

DataRobot Blog

AUGUST 10, 2022

Snowflake provides a state-of the-art data platform for collating and analysing workforce data, and with the combined addition of DataRobot Solution Accelerator models, trusts can have predictive models running with little experimentation — further accelerated by the wide range of supportive datasets available through the Snowflake Marketplace.

Forecasting 52

Forecasting Experimentation Data-driven Risk 52

Smart Data Collective

APRIL 21, 2022

Measuring the total power output of the farm is not the only issue. Since there is enough historical data, the energy companies can apply analytical and predictive models to calculate power generation rates under certain weather conditions. This explains the growing number of solar companies turning to big data.

IoT 100

IoT Internet of Things Forecasting Predictive Modeling 100

DataRobot

MAY 25, 2021

As part of these efforts, we built accurate predictive models to determine the spread of the disease weeks and months in advance of a surge. At the beginning of the pandemic, DataRobot committed to fighting against COVID-19 from a data science perspective.

Testing 52

Testing Predictive Modeling Data-driven Reporting 52