Smarten

MAY 29, 2023

The ability to create, share and use unlimited predictive model objects. Automatic generation of models. Assisted workflow using assisted predictive modeling. The ability to import PMML models created in third-party platforms for use in workflow. Advanced data preparation.

Prescriptive Analytics 52

Prescriptive Analytics Predictive Modeling Digital Transformation Business Objectives 52

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

DataRobot Blog

JULY 22, 2022

At many organizations, the current framework focuses on the validation and testing of new models, but risk managers and regulators are coming to realize that what happens after model deployment is at least as important. Legacy Models. No predictive model — no matter how well-conceived and built — will work forever.

Modeling 105

Modeling Risk Management Testing Risk 105

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

Smarten

MARCH 13, 2024

Self-Serve Data Preparation Assisted Predictive Modeling Smart Data Visualization Machine Learning and Natural Language Processing (NLP) Clickless Search Analytics EXPECTATIONS AND RESULTS Once you have chosen the right augmented analytics solution, you must establish appropriate expectations.

Analytics 52

Analytics Predictive Modeling Strategy Enterprise 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

CIO Business Intelligence

MAY 14, 2024

Private cloud platforms can leverage generative AI for anomaly detection applications in various domains, including cybersecurity, fraud detection, and predictive maintenance,” he says. Still, some IT leaders remain comfortable running all workloads on the public cloud, even with the data privacy concerns generative AI imposes.

IT 136

IT Data Processing Enterprise Modeling 136

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 79

Technology Predictive Modeling Predictive Analytics Forecasting 79

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.

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

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-. REFERENCES. [1]

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

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

O'Reilly on Data

SEPTEMBER 15, 2020

Technical sophistication: Sophistication measures a team’s ability to use advanced tools and techniques (e.g., Technical competence: Competence measures a team’s ability to successfully deliver on initiatives and projects. They’re not new to the field; they’ve solved problems, and have discovered what does and doesn’t work.

Cost-Benefit 290

Cost-Benefit Advertising ROI Machine Learning 290

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

O'Reilly on Data

MARCH 20, 2019

The objective here is to brainstorm on potential security vulnerabilities and defenses in the context of popular, traditional predictive modeling systems, such as linear and tree-based models trained on static data sets. If an attacker can receive many predictions from your model API or other endpoint (website, app, etc.),

Modeling 219

Modeling Machine Learning Predictive Modeling Consulting 219

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

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

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 93

Machine Learning Data Architecture Uncertainty Data-driven 93

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

DataKitchen

JUNE 19, 2023

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. The above image shows an example custom ‘data in use’ test of a predictive model and API. The value here is improved end-user experienc e.

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. The fact is that it is and will affect our lives, whether we like it or not.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

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 111

Advertising Machine Learning Software Measurement 111

CIO Business Intelligence

JULY 24, 2023

It has also developed predictive models to detect trends, make predictions, and simulate results. For example, LaLiga uses AI to engage and retain fans, by recommending content and providing additional insight into the fan experience via sentiment analysis.

Broadcasting 78

Broadcasting Recreation/Entertainment Testing Machine Learning 78

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 81

Cost-Benefit Measurement Management Predictive Analytics 81

Cloudera

OCTOBER 14, 2020

Many companies build machine learning models using libraries, whether they are building perception layers for autonomous vehicles, allowing autonomous vehicle operation, or modeling a complex jet engine. This data will be used to train the model that can predict how many flights a given engine has until failure.

Machine Learning 97

Machine Learning Modeling Cost-Benefit Testing 97

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 99

IoT Internet of Things Forecasting Predictive Modeling 99

CIO Business Intelligence

MAY 28, 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 103

Advertising Machine Learning Software Measurement 103

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

Smart Data Collective

JULY 10, 2019

However, collecting new data is becoming easier, as patient monitoring equipment provides more than 1,000 measurements per second. It is estimated that the number of measurements will rise to 10,000 per second in the near future. With ‘big data’, the idea is to foster a culture of measurement in hospitals.

Big Data 71

Big Data Measurement Predictive Modeling Manufacturing 71

Smart Data Collective

MAY 17, 2021

A mission-critical task like maintenance can be relegated to proactive measures thanks to a steady flow of performance data. What’s more, the same technology can be used for other measures, like monitoring assets and goods, which cuts down on fraud and theft. That’s also where big data can step in and vastly expand ops.

Big Data 100

Big Data Cost-Benefit IoT Machine Learning 100

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

Smart Data Collective

MARCH 28, 2022

There are four main types of data analytics: Predictive data analytics: It is used to identify various trends, causation, and correlations. It can be further classified as statistical and predictive modeling, but the two are closely associated with each other.

Data Analytics 85

Data Analytics Software Analytics Statistics 85

O'Reilly on Data

MAY 18, 2020

All predictive models are wrong at times?—just As the renowned statistician George Box once quipped , “All models are wrong, but some are useful.” If, however, the impact of this type of failure was diminished–by, for example, the model being used as one of several overlapping diagnostic tools–materiality would decrease.

Risk 357

Risk Modeling Data Processing Software 357

John Wheeler

OCTOBER 20, 2020

banking, insurance and securities) measure risk on a quantitative basis. Other quantitative analysis methods are used to develop more precise predictive models to determine the potential for digital risk events, such as product/service liability, fraud or theft.

Risk Management 52

Risk Management Risk Predictive Modeling Insurance 52

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. The accuracy of any predictive model approaches 100%. Property 4: The accuracy of any predictive model approaches 100%.

Statistics 145

Statistics Testing Predictive Modeling Modeling 145

DataRobot Blog

JUNE 23, 2022

Most successful ML and AI projects are replacing an existing prediction with a more accurate and/or faster one. 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.

Predictive Modeling 59

Predictive Modeling Modeling Data Science Measurement 59

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. Tableau’s AI tool, Einstein, can analyze data faster, plucking out useful insights while creating high-quality predictive models.

Business Intelligence 52

Business Intelligence Visualization Dashboards Data-driven 52