CIO Business Intelligence

MARCH 15, 2022

Synthetic data is artificially generated information that can be used in place of real historic data to train AI models when actual data sets are lacking in quality, volume, or variety. Many models will decide that the most successful policy will be to label every transaction as non-fraudulent.”. Synthetic data use cases.

Strategy 145

Strategy Testing Sales Modeling 145

IBM Big Data Hub

AUGUST 9, 2023

A phishing simulation is a cybersecurity exercise that tests an organization’s ability to recognize and respond to a phishing attack. Since 2019, the number of phishing attacks has grown by 150% percent per year— with the Anti-Phishing Working Group (APWG) reporting an all-time high for phishing in 2022 , logging more than 4.7

Testing 77

Testing Measurement Behavioral Analytics Reporting 77

CIO Business Intelligence

MARCH 10, 2022

Fujitsu remains very much interested in the mainframe market, with a new model still on its roadmap for 2024, and a move under way to “shift its mainframes and UNIX servers to the cloud, gradually enhancing its existing business systems to optimize the experience for its end-users.”

Sales 127

Sales Testing Experimentation Data Processing 127

CIO Business Intelligence

JULY 5, 2022

Research firm Gartner defines business analytics as “solutions used to build analysis models and simulations to create scenarios, understand realities, and predict future states.”. 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 131

Business Analytics Prescriptive Analytics Data mining Diagnostic Analytics 131

CIO Business Intelligence

OCTOBER 20, 2023

Allstate began moving to the cloud in 2019 but paused during the pandemic and began the deployment of its curated multicloud blueprint upon Jeevanjee’s return to the company in 2022. As models evolve in the future to become fully multi-modal, they [will be] able to traverse different types of data.”

Digital Transformation 136

Digital Transformation Insurance Recreation/Entertainment Machine Learning 136

O'Reilly on Data

MAY 21, 2019

Companies successfully adopt machine learning either by building on existing data products and services, or by modernizing existing models and algorithms. For example, in a July 2018 survey that drew more than 11,000 respondents, we found strong engagement among companies: 51% stated they already had machine learning models in production.

Machine Learning 234

Machine Learning Technology Deep Learning Data Science 234

Domino Data Lab

JUNE 13, 2019

Recently, Chhavi Yadav (NYU) and Leon Bottou (Facebook AI Research and NYU) indicated in their paper, “ Cold Case: The Lost MNIST Digits ”, how they reconstructed the MNIST (Modified National Institute of Standards and Technology) dataset and added 50,000 samples to the test set for a total of 60,000 samples. Did they overfit the test set?

Testing 83

Testing Data Science Experimentation Metadata 83

DataKitchen

OCTOBER 5, 2022

Observability also validates that your data transformations, models, and reports are performing as expected. A 2019 DataKitchen/Eckerson survey found that 79% of companies have more than three data-related errors in their pipelines per month. This solution sits on top of your existing infrastructure?without

Testing 169

Testing Risk Data Processing Statistics 169

CIO Business Intelligence

MARCH 4, 2024

We do not need to boost young women’s math tests scores or confidence in their math ability as much as we need to entice more women to plan to enter science-related occupations,” the study’s authors wrote. Recruit tech role models Diverse representation will spark a diversity of interest in technology.

Technology 121

Technology Reporting Measurement Testing 121

O'Reilly on Data

JANUARY 25, 2021

Year-over-year (YOY) growth compares January through September 2020 with the same months of 2019. Usage of O’Reilly online learning grew steadily in 2020, with 24% growth since 2019. Models are neither code nor data, and we don’t have adequate tools for versioning models either (though tools like MLflow are a start).

Machine Learning 362

Machine Learning Software Testing Technology 362

CIO Business Intelligence

NOVEMBER 1, 2023

And alongside these major changes, Volvo is also resetting its business model and switching to direct sales in that part of the network of global dealers broadens their roles where instead of just selling Volvo cars, they become distributors. We were going to leave our data centers, and we did,” he says. “In

Software 128

Software Testing Digital Transformation Management 128

CIO Business Intelligence

JANUARY 5, 2024

When I joined the group in June 2019, there were two decision-making centers: Americas and the rest of the world. From an organizational standpoint, we evolved to a nearshore model, attracting the necessary talent that new technologies required. And in just eight months, we were able to put 80% of our platforms on current technologies.

IT 110

IT Finance Cost-Benefit Strategy 110

Smart Data Collective

OCTOBER 13, 2021

Figuring out the best pricing model can be tricky. This is how you can improve a pricing model: Use machine learning to process data and discover services that need a boost. Do an A/B testing and find out. Use automated pricing models to drive up revenue. What can you learn from real-market examples?

Machine Learning 125

Machine Learning Optimization Software Modeling 125

DataKitchen

OCTOBER 5, 2022

Observability also validates that your data transformations, models, and reports are performing as expected. A 2019 DataKitchen/Eckerson survey found that 79% of companies have more than three data-related errors in their pipelines per month. This solution sits on top of your existing infrastructure?without

Testing 130

Testing Risk Data Processing Statistics 130

Corinium

JUNE 6, 2019

Fractal’s recommendation is to take an incremental, test and learn approach to analytics to fully demonstrate the program value before making larger capital investments. It is also important to have a strong test and learn culture to encourage rapid experimentation. What are you most looking forward to about CDAOI Insurance 2019?

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

CIO Business Intelligence

OCTOBER 18, 2023

For instance, the company completed its conversion to a 100% Agile company in 2019, an achievement that reinforced its commitment to clients. The context tests us and it’s necessary to reinvent ourselves every day.”

Digital Transformation 119

Digital Transformation Insurance Interactive Sales 119

CIO Business Intelligence

SEPTEMBER 10, 2022

To supplement the technology, the agency relies on input from thousands of experienced workers, captured passively and actively, to train and refine AI-driven models to ensure the technology delivers expected outcomes. So, emerging tech teams test and adjust concepts with internal customers before, during, and after any launch.

Data-driven 111

Data-driven Machine Learning ROI Modeling 111

DataRobot

JUNE 29, 2021

Well, just imagine a production machine learning model that always stays accurate after it’s deployed—all by itself. Machine learning models trained on 2019 data didn’t know what to do. Continuous AI not only retrains your current production models for you. Why do I think this? Sounds pretty cool, right? Over and over.

Machine Learning 80

Machine Learning Data Processing Forecasting Modeling 80

CIO Business Intelligence

APRIL 15, 2022

MIT Technology Review has chronicled a number of failures, most of which stem from errors in the way the tools were trained or tested. For example, Driggs’ group found that their own model was flawed because it was trained on a data set that included scans of patients that were lying down while scanned and patients that were standing up.

Analytics 145

Analytics Machine Learning Insurance Testing 145

Data Science and Beyond

APRIL 5, 2021

The world has adapted quickly, though it seems like Automattic’s globally-distributed model is still quite unusual. Instead, many companies have switched to a locally-remote model, hiring remotely within the same country or timezone region. Only time will tell. Sustainability.

Experimentation 61

Experimentation Testing Publishing Measurement 61

DataRobot Blog

MAY 31, 2022

For instance, in 2019, the Government Acquisition Office (GAO) researched and identified 35 high-risk hiring areas. In this blog post, the DataRobot team will show how the DataRobot AI Cloud Platform can build models to predict if an employee will depart an organization in the next six months. Example of Feature Lineage in DataRobot.

Management 59

Management Risk Testing Modeling 59

Smart Data Collective

MARCH 23, 2020

According to the SensorTower statistics , in 2019, a simple arcade game Stack Ball reached 100 million installs and only continued to grow. In 2019, this number increased to 2.4 They can even create models that predict what users will do after an update or a patch is released. In 2014, there were about 1.82 billion in 2021.

Big Data 103

Big Data Recreation/Entertainment Data mining Optimization 103

CIO Business Intelligence

MAY 18, 2023

For understanding teams “CTOs and CIOs who work for organizations that are struggling to deliver value sustainably will greatly benefit from reading Team Topologies: Organizing Business and Technology Teams for Fast Flow (IT Revolution Press, 2019) by Manuel Pais and Matt Skelton,” says Peter Kreslins Jr., CTO and co-founder of Digibee.

IT 120

IT Software Recreation/Entertainment Technology 120

Insight

FEBRUARY 19, 2020

My goal here is not to improve upon the current prediction algorithms but rather to describe a model I devised, called ReelRisk , that uses random resampling to generate a range of predictions which can then be used as a risk assessment tool to determine early on whether to fund a movie. The solid line shows the y=x line for comparison.

Risk 67

Risk ROI Modeling Metrics 67

Cloudera

DECEMBER 3, 2021

In 2019, the Gradient institute published a white paper outlining the practical challenges for Ethical AI. For example, training an interview screening model using education data often contains gender information. As discussed in this article , model design can also be a source of bias too. Model Drift. Regulation.

Uncertainty 100

Uncertainty Measurement Metrics Risk 100

CIO Business Intelligence

JANUARY 8, 2024

The optimization strategy will also include modifications to Cathay’s SaaS-based implementations, such as Salesforce CRM, ServiceNow, and SAP, to better align them with the business and maximize Cathay’s return on investment on the model. The cloud has helped us to be more scalable and agile.”

Optimization 99

Optimization Digital Transformation Cost-Benefit Data Warehouse 99

Domino Data Lab

MAY 8, 2019

Paco Nathan’s latest article features several emerging threads adjacent to model interpretability. I’ve been out themespotting and this month’s article features several emerging threads adjacent to the interpretability of machine learning models. Machine learning model interpretability. Introduction. 2018-06-21).

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Paul Turley

MAY 11, 2019

This post demonstrates some of the advanced tools you can you to test slowing performing queries and to do deep troubleshooting and performance analysis in your data models. Using the new Performance Analyzer in the Power BI Desktop May 2019 release, finding … Continue reading →

Testing 42

Testing Modeling 42

The Unofficial Google Data Science Blog

APRIL 23, 2024

Experiments, Parameters and Models At Youtube, the relationships between system parameters and metrics often seem simple — straight-line models sometimes fit our data well. That is true generally, not just in these experiments — spreading measurements out is generally better, if the straight-line model is a priori correct.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

Dataiku

MAY 20, 2020

Remote work is the ultimate litmus test of the data organization’s robustness. According to the 2019 State of Remote Work Survey , 99% of respondents said they would like to work remotely, at least some of the time, for the rest of their career. The Challenges of Remote Data Science.

Data Science 105

Data Science IT Machine Learning Testing 105

Data Science 101

MAY 6, 2019

I think in physics one of the things that attracted me most to the field that I studied, which was particle physics, was the ability to leverage computer science mathematical modeling and data visualization to solve big questions. And what kind of transformation do you need to apply to the data set to enable modeling?

Data Science 98

Data Science Modeling Machine Learning Testing 98

datapine

OCTOBER 21, 2020

Now that we live longer, treatment models have changed and many of these changes are namely driven by data. Every patient has his own digital record which includes demographics, medical history, allergies, laboratory test results, etc. and could provide a model for the EU to follow. 2) Electronic Health Records (EHRs).

Big Data 364

Big Data Data Analytics Analytics Cost-Benefit 364

CIO Business Intelligence

JANUARY 23, 2023

As OpenAI’s exclusive cloud provider it will see additional revenue for its Azure services, as one of OpenAI’s biggest costs is providing the computing capacity to train and run its AI models. That app, Microsoft Designer , is currently in closed beta test. The deal, announced by OpenAI and Microsoft on Jan.

Enterprise 131

Enterprise Deep Learning Recreation/Entertainment Interactive 131

bridgei2i

JULY 2, 2019

BANGALORE, July 2, 2019. BRIDGEi2i Analytics Solutions was featured in Gartner’s 2019 list of ‘Market Guide for Data and Analytics Service Providers.’ Advanced AI algorithms are also the benchmark to test AI-intuitive ideas and newer business models.’. ” You can read the Press Release here.

Marketing 45

Marketing Analytics Contextual Data Consulting 45

Cloudera

DECEMBER 11, 2020

That compares to only 36 percent of customer interactions as of December 2019, which was before the pandemic impacted business, and only 20 percent in May 2018. Insurance and finance are two industries that rely on measuring risk with historical data models. Data Variety.

Insurance 94

Insurance Digital Transformation Unstructured Data Machine Learning 94

IBM Big Data Hub

JULY 19, 2023

Other use cases where generative AI models can help life sciences organizations unleash competitive advantage are: Summarization : call center interactions, documents such as financial reports, analyst articles, emails, news, media trends and more. Fairness : AI models should treat all groups equitably.

Consulting 62

Consulting Machine Learning Manufacturing Optimization 62

AWS Big Data

MARCH 3, 2023

Tricentis is the global leader in continuous testing for DevOps, cloud, and enterprise applications. Speed changes everything, and continuous testing across the entire CI/CD lifecycle is the key. Tricentis instills that confidence by providing software tools that enable Agile Continuous Testing (ACT) at scale.

Software 52

Software Data Lake Testing Cost-Benefit 52