Smart Data Collective

AUGUST 2, 2022

Along with converting to electric vehicles and delivering self-driving cars, automotive companies master their software development expertise. Companies that fail to leverage AI effectively risk falling behind in a competitive industry. AI aids with digital transformation and software-defined vehicles.

Software 127

Software Machine Learning B2B Manufacturing 127

O'Reilly on Data

DECEMBER 12, 2019

Not least is the broadening realization that ML models can fail. And that’s why model debugging, the art and science of understanding and fixing problems in ML models, is so critical to the future of ML. Because all ML models make mistakes, everyone who cares about ML should also care about model debugging. [1]

Machine Learning 191

Machine Learning Modeling Testing Risk Management 191

CIO Business Intelligence

MARCH 25, 2024

Modern digital organisations tend to use an agile approach to delivery, with cross-functional teams, product-based operating models , and persistent funding. But to deliver transformative initiatives, CIOs need to embrace the agile, product-based approach, and that means convincing the CFO to switch to a persistent funding model.

Modeling 119

Modeling Cost-Benefit IT ROI 119

Smart Data Collective

APRIL 22, 2020

Big data has turned the software industry on its head. The relationship between software development and big data is a two-way street. While many software developers are looking to create new applications that use big data, they are also using big data to streamline development. Big data helps compilers operate more efficiently.

Data-driven 92

Data-driven Software Big Data Testing 92

Smart Data Collective

NOVEMBER 3, 2021

New software uses AI to manage bank loans. AI Makes Bank Lending Software Far More Reliable. In this article, we decided to cover the tendencies in banking loan software in 2022 and give a brief market outlook of AI-driven lending software as a whole. Digital banking market. Integrated lending module.

Software 121

Software Data-driven Interactive Insurance 121

CIO Business Intelligence

MAY 15, 2024

It seems anyone can make an AI model these days. Even if you don’t have the training data or programming chops, you can take your favorite open source model, tweak it, and release it under a new name. According to Stanford’s AI Index Report, released in April, 149 foundation models were released in 2023, two-thirds of them open source.

Modeling 90

Modeling Risk Software Enterprise 90

CIO Business Intelligence

MAY 17, 2022

Even if the AI apocalypse doesn’t come to pass, shortchanging AI ethics poses big risks to society — and to the enterprises that deploy those AI systems. The following real-world implementation issues highlight prominent risks every IT leader must account for in putting together their company’s AI deployment strategy.

Risk 142

Risk Consulting Machine Learning Data Science 142

O'Reilly on Data

JULY 11, 2023

There’s a lot of angst about software developers “losing their jobs” to AI, being replaced by a more intelligent version of ChatGPT, GitHub’s Copilot, Google’s Codey, or something similar. What does this mean for people who earn their living from writing software? Programmers who work for those companies risk losing their jobs to AI.

Testing 248

Testing Software Visualization Interactive 248

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

DataKitchen

FEBRUARY 2, 2023

This will drive a new consolidated set of tools the data team will leverage to help them govern, manage risk, and increase team productivity. Their software purchase behavior will align with enabling standards for line-of-business data teams who use various tools that act on data. What will exist at the end of 2025?

Metadata 130

Metadata Testing Risk Data Science 130

O'Reilly on Data

JULY 28, 2020

Product Managers are responsible for the successful development, testing, release, and adoption of a product, and for leading the team that implements those milestones. You must detect when the model has become stale, and retrain it as necessary. The Core Responsibilities of the AI Product Manager.

Marketing 362

Marketing Experimentation Metrics Testing 362

DataKitchen

SEPTEMBER 21, 2023

In the context of Data in Place, validating data quality automatically with Business Domain Tests is imperative for ensuring the trustworthiness of your data assets. Running these automated tests as part of your DataOps and Data Observability strategy allows for early detection of discrepancies or errors.

Testing 169

Testing Data Quality Predictive Modeling Metrics 169

Jet Global

SEPTEMBER 1, 2023

In this modern, turbulent market, predictive analytics has become a key feature for analytics software customers. But we’re also seeing its use expand in other industries, like Financial Services applications for credit risk assessment or Human Resources applications to identify employee trends.

Predictive Analytics 52

Predictive Analytics Risk Analytics Software 52

Sisense

SEPTEMBER 23, 2019

The API layer of any application is one of the most crucial software components. If it breaks, it puts at risk, not just a single application, but an entire chain of business processes built around it. If it breaks, it puts at risk, not just a single application, but an entire chain of business processes built around it.

Testing 89

Testing Strategy Modeling ROI 89

erwin

JANUARY 9, 2020

For decades, data modeling has been the optimal way to design and deploy new relational databases with high-quality data sources and support application development. Today’s data modeling is not your father’s data modeling software. So here’s why data modeling is so critical to data governance.

Data Governance 144

Data Governance Modeling Metadata Unstructured Data 144

CIO Business Intelligence

MARCH 5, 2024

India’s Ministry of Electronics and Information Technology (MeitY) has caused consternation with its stern reminder to makers and users of large language models (LLMs) of their obligations under the country’s IT Act, after Google’s Gemini model was prompted to make derogatory remarks about Indian Prime Minister Narendra Modi.

Testing 124

Testing Modeling Cost-Benefit Reporting 124

CIO Business Intelligence

DECEMBER 13, 2023

Next-Generation Software Development – New software tools enable modern code-deployment pipelines and automate code generation, testing, refactoring, and translation, improving application quality and development processes CIO, Generative AI

Machine Learning 107

Machine Learning Software Testing Risk 107

DataKitchen

SEPTEMBER 20, 2021

The best way to ensure error-free execution of data production is through automated testing and monitoring. The DataKitchen Platform enables data teams to integrate testing and observability into data pipeline orchestrations. Automated tests work 24×7 to ensure that the results of each processing stage are accurate and correct.

Testing 246

Testing Metrics Measurement Dashboards 246

IBM Big Data Hub

FEBRUARY 13, 2024

This data is fed into generational models, and there are a few to choose from, each developed to excel at a specific task. Generative adversarial networks (GANs) or variational autoencoders (VAEs) are used for images, videos, 3D models and music. Autoregressive models or large language models (LLMs) are used for text and language.

Enterprise 125

Enterprise Modeling Testing Data-driven 125

CIO Business Intelligence

MAY 14, 2024

Enterprises need to ensure that private corporate data does not find itself inside a public AI model,” McCarthy says. You don’t want a mistake to happen and have it end up ingested or part of someone else’s model. The excitement and related fears surrounding AI only reinforces the need for private clouds.

IT 136

IT Data Processing Enterprise Modeling 136

CIO Business Intelligence

DECEMBER 11, 2023

“This regulation aims to ensure that fundamental rights, democracy, the rule of law and environmental sustainability are protected from high risk AI, while boosting innovation and making Europe a leader in the field,” said the press release issued by European Parliament. million) or 1.5% of the turnover to $37.6 This is just not true.

Risk 110

Risk Testing Insurance Cost-Benefit 110

Smart Data Collective

AUGUST 9, 2022

The risk of data breaches is rising sharply. Cybersecurity experts are using data analytics and AI to identify warning signs that a firewall has been penetrated, conduct risk scoring analyses and perform automated cybersecurity measures. The number increased 56% between 2017 and 2018.

Big Data 112

Big Data Technology Testing Cost-Benefit 112

CIO Business Intelligence

MARCH 3, 2024

Worse, it said “adversaries are accelerating and widening their range of sophisticated attacks at scale through automation, cybercrime-as-a-service models, impersonations and adaptation.” And only 45 percent of CISOs were very or somewhat concerned about the risks of unsecured printers, compared to 72 percent of CIOs.

IT 102

IT Measurement Risk Testing 102

CIO Business Intelligence

FEBRUARY 28, 2024

Essentially, the technology involves the replication of the human body in software models. Using these models, healthcare providers can test drugs and therapies with unprecedented speed and accuracy, reducing risks for both patients and physicians.

Informatics 102

Informatics Data-driven Digital Transformation Predictive Analytics 102

CIO Business Intelligence

AUGUST 24, 2023

Gen AI has the potential to magnify existing risks around data privacy laws that govern how sensitive data is collected, used, shared, and stored. We’re getting bombarded with questions and inquiries from clients and potential clients about the risks of AI.” The risk is too high.” Not without warning signs, however.

Uncertainty 97

Uncertainty Risk Testing Enterprise 97

Domino Data Lab

AUGUST 10, 2021

Models are the central output of data science, and they have tremendous power to transform companies, industries, and society. At the center of every machine learning or artificial intelligence application is the ML/AI model that is built with data, algorithms and code. The process of creating models is called modeling.

Modeling 64

Modeling IT Risk Management Deep Learning 64

datapine

APRIL 15, 2020

Your Chance: Want to test an agile business intelligence solution? Try our business intelligence software for 14 days, completely free! The term “agile” was originally conceived in 2011 as a software development methodology. Working software over comprehensive documentation. What Is Agile Analytics And BI?

Business Intelligence 276

Business Intelligence Analytics Testing Dashboards 276

Smart Data Collective

AUGUST 30, 2022

With cloud computing, companies can use their servers and hardware as much as they want with little overhead from extra hardware and software. The model enables easy transfer of cloud services between different geographic regions, either onshore or offshore. Testing new programs. Multi-cloud computing. Centralized data storage.

Technology 134

Technology Enterprise Cost-Benefit Testing 134

CIO Business Intelligence

MARCH 18, 2024

Developers of risky generative AI models are now free to release them without government approval, but are being encouraged to self-regulate by adding labels to the output of their models warning of their potential unreliability. Akshara Bassi, senior analyst at Counterpoint, weighed in on the implications for AI model developers.

Metadata 73

Metadata Visualization Modeling Risk 73

CIO Business Intelligence

JUNE 8, 2023

Skills such as software engineering, architecture, cloud, and program management are highly sought after as more companies explore creating both internal and external applications and solutions. Key skills for the role include resource allocation, risk and change management, quality assurance, communication, and leadership and team building.

IT 137

IT Digital Transformation Software Risk 137

IBM Big Data Hub

SEPTEMBER 28, 2023

An AI and data platform, such as watsonx, can help empower businesses to leverage foundation models and accelerate the pace of generative AI adoption across their organization. Business-targeted, IBM-developed foundation models built from sound data Business leaders charged with adopting generative AI need model flexibility and choice.

Testing 94

Testing Finance Enterprise Modeling 94

DataKitchen

AUGUST 8, 2023

It can improve data quality, mitigate risk and adhere to governance requirements, detect unexpected or unknown events, reduce time to investigate and solve issues, improve budget planning and cost control, and increase efficiency and productivity. However, there are potential risks and challenges in adopting Data Observability.

Data Quality 130

Data Quality Testing Snapshot Reporting 130

Smart Data Collective

MARCH 23, 2022

This AI could be utilized as a safety feature , like real-time risk assessment, for example, alerting the driver when a potential incident has been detected. After this incident went viral on social media, Chrysler released a software patch to combat this kind of attack. The first is developing high-quality software.

IoT 110

IoT Internet of Things Testing Cost-Benefit 110

DataKitchen

JUNE 19, 2023

Our customers start looking at the data in dashboards and models and then find many issues. Data Journeys run on software, on servers, and with code. Using automated data validation tests, you can ensure that the data stored within your systems is accurate, complete, consistent, and relevant to the problem at hand.

Testing 130

Testing Cost-Benefit Metrics Data Quality 130

CIO Business Intelligence

FEBRUARY 20, 2024

Others are weighing the advantages of subscription-based business models where industrial equipment, automation, and processes are delivered as a service. Nall comments: “Copilot can help manufacturers de-risk their supply chains by helping predict potential disruption so they can put mitigations in place ahead of time.”

Manufacturing 86

Manufacturing Sales Risk Management Forecasting 86

Sisense

MARCH 2, 2020

Introducing the Sisense Data Model APIs. The new Sisense Data Model APIs extend the capabilities provided by the Sisense REST APIs. Builders will be able to programmatically create and modify Sisense Data Models using fully RESTful and JSON-based APIs. You may be asking “What’s a Sisense Data Model, exactly?”

Modeling 87

Modeling Data-driven Dashboards Testing 87

Smart Data Collective

JUNE 7, 2019

However, recent advances in applying transfer learning to NLP allows us to train a custom language model in a matter of minutes on a modest GPU, using relatively small datasets,” writes author Euan Wielewski. Appreciating the Machine Learning Technology Behind Modern Task Management Software. Final Thoughts. Happy learning!

Machine Learning 78

Machine Learning Software Management Data-driven 78