Cloudera

JULY 15, 2021

We recently hosted a roundtable focused on o ptimizing risk and exposure management with data insights. For financial institutions and insurers, risk and exposure management has always been a fundamental tenet of the business. Now, risk management has become exponentially complicated in multiple dimensions. .

Risk 99

Risk Optimization Management Insurance 99

IBM Big Data Hub

JANUARY 9, 2024

These applications are designed to meet specific business needs by integrating proprietary data and help to ensure more accurate and relevant responses. This trend signals a move toward more efficient and personalized AI-driven business solutions. This approach results in highly personalized customer interactions.

Data-driven 102

Data-driven Risk Modeling Marketing 102

Cloudera

AUGUST 21, 2021

The same study also stated that having stronger online data security, being able to conduct more banking transactions online and having more real-time problem resolution were the top priorities of consumers. . Financial institutions need a data management platform that can keep pace with their digital transformation efforts.

Data-driven 101

Data-driven Digital Transformation Risk Risk Management 101

AWS Big Data

MAY 28, 2024

Welcome back to our exciting exploration of architectural patterns for real-time analytics with Amazon Kinesis Data Streams! Before we dive in, we recommend reviewing Architectural patterns for real-time analytics using Amazon Kinesis Data Streams, part 1 for the basic functionalities of Kinesis Data Streams.

IoT 92

IoT Analytics Dashboards Data-driven 92

CIO Business Intelligence

MAY 9, 2024

They should lead the efforts to tie AI capabilities to data analytics and business process strategies and champion an AI-first mindset throughout the organization. They also need to understand the vitality of quality data for AI success, as well as governance frameworks to ensure responsible and ethical use of AI.

Risk Management 129

Risk Management Risk Cost-Benefit Technology 129

O'Reilly on Data

NOVEMBER 28, 2023

And everyone has opinions about how these language models and art generation programs are going to change the nature of work, usher in the singularity, or perhaps even doom the human race. AI users say that AI programming (66%) and data analysis (59%) are the most needed skills. Many AI adopters are still in the early stages.

Enterprise 267

Enterprise Modeling Testing Reporting 267

Jet Global

SEPTEMBER 1, 2023

Predictive analytics refers to the use of historical data, machine learning, and artificial intelligence to predict what will happen in the future. 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.

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Predictive Analytics Risk Analytics Software 52

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 93

Informatics Data-driven Digital Transformation Predictive Analytics 93

Cloudera

MAY 18, 2021

This article is the second in a multipart series to showcase the power and expressibility of FlinkSQL applied to market data. Code and data for this series are available on github. Flink SQL is a data processing language that enables rapid prototyping and development of event-driven and streaming applications.

Risk 96

Risk Marketing Risk Management Data-driven 96

CIO Business Intelligence

MAY 15, 2024

This is driving a greater degree of risk in complex environments. GenAI’s ability to rapidly summarize vast quantities of information and provide answers from an established data set is fast making it a hit with incident response teams. In those circumstances, the risk outweighs any expected rewards.

Machine Learning 109

Machine Learning Risk Data-driven Testing 109

DataKitchen

FEBRUARY 27, 2024

Your LLM Needs a Data Journey: A Comprehensive Guide for Data Engineers The rise of Large Language Models (LLMs) such as GPT-4 marks a transformative era in artificial intelligence, heralding new possibilities and challenges in equal measure. Embedding: The retrieved data is encoded into embeddings that the LLM can interpret.

Data Quality 117

Data Quality Unstructured Data Testing Modeling 117

bridgei2i

JUNE 2, 2020

Episode 7: The Impact of COVID-19 on Financial Services & Risk. The Impact of COVID-19 on Financial Services & Risk Management. Additionally, institutions are finding it difficult to forecast trends, as historical data isn’t relevant anymore. PODCAST: COVID 19 | Redefining Digital Enterprises. Management.

Risk Management 128

Risk Management Risk Enterprise Management 128

erwin

FEBRUARY 20, 2020

Enterprise architecture (EA) and business process (BP) modeling tools are evolving at a rapid pace. Recently, Glassdoor named enterprise architecture the top tech job in the UK , indicating its increasing importance to the enterprise in the tech and data-driven world.

Enterprise 128

Enterprise Modeling Dashboards Digital Transformation 128

Laminar Security

DECEMBER 13, 2023

In the ever-evolving digital landscape, the importance of data discovery and classification can’t be overstated. As we generate and interact with unprecedented volumes of data, the task of accurately identifying, categorizing, and utilizing this information becomes increasingly difficult.

Data-driven 119

Data-driven Machine Learning Risk Deep Learning 119

erwin

MAY 2, 2022

How to create a solid foundation for data modeling of OLTP systems. As you undertake a cloud database migration , a best practice is to perform data modeling as the foundation for well-designed OLTP databases. This makes mastering basic data modeling techniques and avoiding common pitfalls imperative.

Modeling 98

Modeling Insurance Cost-Benefit Data Warehouse 98

IBM Big Data Hub

MAY 17, 2024

Poorly run implementations of traditional or generative AI in commerce—such as models trained on inadequate or inappropriate data—lead to bad experiences that alienate consumers and businesses. This includes trust in the data, the security, the brand and the people behind the AI.

B2B 66

B2B Interactive Optimization Forecasting 66

O'Reilly on Data

JUNE 7, 2022

DeepMind’s new model, Gato, has sparked a debate on whether artificial general intelligence (AGI) is nearer–almost at hand–just a matter of scale. Gato is a model that can solve multiple unrelated problems: it can play a large number of different games, label images, chat, operate a robot, and more.

Modeling 363

Modeling Interactive Optimization Deep Learning 363

Laminar Security

DECEMBER 1, 2023

Cloud data security is one of the most critical, yet most challenging aspects of doing business in the age of cloud. As more organizations migrate their data to the cloud, they face an increasing range of risks and threats, including data breaches, data leakage, data loss, data misuse, data compliance violations, shadow data and more.

Modeling 52

Modeling Cost-Benefit Risk Data-driven 52

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

IBM Big Data Hub

FEBRUARY 13, 2024

The compact design and touch-based interactivity seemed like a leap into the future. Demystifying generative AI At the heart of Generative AI lie massive databases of texts, images, code and other data types. This data is fed into generational models, and there are a few to choose from, each developed to excel at a specific task.

Enterprise 120

Enterprise Modeling Testing Data-driven 120

erwin

MAY 14, 2021

compliance with the General Data Protection Regulation). Accelerating the retrieval and analysis of data —so much of it unstructured—is vital to becoming a data-driven business that can effectively respond in real time to customers, partners, suppliers and other parties, and profit from these efforts.

Modeling 80

Modeling Digital Transformation Data-driven Optimization 80

CIO Business Intelligence

APRIL 30, 2024

The law will also extend beyond the borders of the EU member nations, as any company interacting with residents of the EU will be subject to the regulations. They must conduct risk assessments, take steps to reduce risk, maintain use logs, comply with transparency requirements, and ensure human oversight.

IT 83

IT Risk Data-driven Modeling 83

bridgei2i

NOVEMBER 20, 2020

Episode 2: AI enabled Risk Management for FS powered by BRIDGEi2i Watchtower. AI enabled Risk Management for FS powered by BRIDGEi2i Watchtower. Today the Chief Risk Officers(CROs) struggle with the critical task of monitoring and assessing key risks in real time and firefight to mitigate any critical issues that arise.

Risk Management 92

Risk Management Risk Management Metrics 92

CIO Business Intelligence

MAY 30, 2024

Case in point is its new conversational assistant copilot, AlpiGPT an internal search engine of corporate data that can personalize travel packages and quickly answer questions, says company CIO, Francesco Ciuccarelli. Creating new business models Gen AI is also unique in that it can generate useful business models.

Cost-Benefit 103

Cost-Benefit Sales Modeling Experimentation 103

FineReport

APRIL 9, 2024

Evolving BI Tools in 2024 Significance of Business Intelligence In 2024, the role of business intelligence software tools is more crucial than ever, with businesses increasingly relying on data analysis for informed decision-making.

Business Intelligence 52

Business Intelligence Software Data-driven Predictive Modeling 52

Cloudera

OCTOBER 24, 2023

The AI technologies of today—including not just large language models (LLMs) but also deep learning, reinforcement learning, and natural-language processing (NLP) tools—will equip telcos with powerful new automation and analytics capabilities. AI-powered automation is already driving significant margin growth by reducing costs.

Interactive 79

Interactive Data-driven Cost-Benefit Optimization 79

IBM Big Data Hub

DECEMBER 1, 2023

IBM’s work with insurance clients, along with studies by IBM’s Institute of Business Value (IBV), show that insurer management decisions are driven by digital orchestration, core productivity and the need for flexible infrastructure. The supervised learning that is used to train AI requires a lot of human effort.

Insurance 99

Insurance Digital Transformation Unstructured Data Risk 99

Jet Global

APRIL 5, 2021

Enterprises actively use financial modeling to guide their financial planning and strategic decision-making. Financial models offer data-driven, quantitative analysis that tells you where your company stands and where it’s heading. That being said, one model can’t do it all. What Is Financial Modeling?

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Modeling Forecasting Metrics Finance 98

IBM Big Data Hub

FEBRUARY 9, 2024

2023 saw an explosion of increasingly efficient foundation models with open licenses, beginning with the launch of Meta’s LlaMa family of large language models (LLMs) and followed by the likes of StableLM, Falcon, Mistral, and Llama 2. DeepFloyd and Stable Diffusion have achieved relative parity with leading proprietary models.

Cost-Benefit 97

Cost-Benefit Modeling Data-driven Enterprise 97

Ontotext

FEBRUARY 26, 2024

This is part of Ontotext’s AI-in-Action initiative aimed at enabling data scientists and engineers to benefit from the AI capabilities of our products. The answers to these foundational questions help you uncover opportunities and detect risks. Why do risk and opportunity events matter?

Data-driven 59

Data-driven Risk Modeling Risk Management 59

datapine

NOVEMBER 27, 2019

Data exploded and became big. Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. The rise of self-service analytics democratized the data product chain. 1) Data Quality Management (DQM). We all gained access to the cloud.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Rocket-Powered Data Science

OCTOBER 6, 2023

In the world of data there are other types of nuanced applications of business analytics that are also actionable – perhaps these are not too different from predictive and prescriptive, but their significance, value, and implementation can be explained and justified differently. This is predictive power discovery.

Business Analytics 157

Business Analytics Prescriptive Analytics Analytics Diagnostic Analytics 157

O'Reilly on Data

JULY 28, 2020

It’s often difficult for businesses without a mature data or machine learning practice to define and agree on metrics. Fair warning: if the business lacks metrics, it probably also lacks discipline about data infrastructure, collection, governance, and much more.) Agreeing on metrics. Fault Tolerant Versus Fault Intolerant AI Problems.

Marketing 361

Marketing Experimentation Metrics Testing 361

IBM Big Data Hub

JANUARY 12, 2024

The advantages of AI are numerous and impactful, from predictive analytics that refine strategies, to natural language processing that fuels customer interactions and assists users in their daily tasks, to assistive tools that enhance accessibility, communication and independence for people with disabilities.

Data-driven 96

Data-driven Interactive Data Processing Technology 96

DataRobot

SEPTEMBER 16, 2021

The ability to charge more accurate premiums helps the company mitigate risk and maintain a competitive advantage, which, in turn, also benefits consumers. The later introduction of Generalized Linear Models (GLM) significantly expanded the pricing actuary’s toolbox. Loss cost modeling-related features. Claim Count.

Modeling 52

Modeling Insurance Cost-Benefit Machine Learning 52

erwin

AUGUST 15, 2022

For NoSQL, data lakes, and data lake houses—data modeling of both structured and unstructured data is somewhat novel and thorny. This blog is an introduction to some advanced NoSQL and data lake database design techniques (while avoiding common pitfalls) is noteworthy. A sample data warehousing project.

Data Lake 52

Data Lake Modeling Unstructured Data Data Warehouse 52

datapine

OCTOBER 21, 2020

Big data has changed the way we manage, analyze, and leverage data across industries. One of the most notable areas where data analytics is making big changes is healthcare. In this article, we’re going to address the need for big data in healthcare and hospital big data: why and how can it help?

Big Data 364

Big Data Data Analytics Analytics Cost-Benefit 364