erwin

JANUARY 24, 2020

There are three different types of data models: conceptual, logical and physical, and each has a specific purpose. Conceptual Data Models: High-level, static business structures and concepts. Logical Data Models: Entity types, data attributes and relationships between entities.

Modeling 143

Modeling Business Driver Sales Data-driven 143

DataRobot Blog

APRIL 29, 2022

With the big data revolution of recent years, predictive models are being rapidly integrated into more and more business processes. When business decisions are made based on bad models, the consequences can be severe. When business decisions are made based on bad models, the consequences can be severe. What is a model?

Risk 111

Risk Modeling IT Risk Management 111

Decision Management Solutions

JANUARY 5, 2021

Bart de Langhe and Stefano Puntoni recently published a great article in the MIT Sloan Management Review called “Leading With Decision-Driven Data Analytics” In contrast to so much of the literature that focuses first on data, they focus on decision-making. We call this approach decision-driven data analytics.”.

Data-driven 40

Data-driven Data Analytics Analytics Modeling 40

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

erwin

JANUARY 9, 2020

Enterprises are trying to manage data chaos. They also face increasing regulatory pressure because of global data regulations , such as the European Union’s General Data Protection Regulation (GDPR) and the new California Consumer Privacy Act (CCPA), that went into effect last week on Jan. GDPR: Key Differences.

Data Governance 144

Data Governance Modeling Metadata Unstructured Data 144

DataKitchen

MARCH 12, 2024

Key Success Metrics, Benefits, and Results for Data Observability Using DataKitchen Software Lowering Serious Production Errors Key Benefit Errors in production can come from many sources – poor data, problems in the production process, being late, or infrastructure problems. Director, Data Analytics Team “We had some data issues.

Metrics 117

Metrics Software Cost-Benefit Testing 117

AWS Big Data

MARCH 30, 2023

An event-driven architecture is a software design pattern in which decoupled applications can asynchronously publish and subscribe to events via an event broker. By containerizing your data processing tasks, you can simply deploy them into Amazon EKS as Kubernetes jobs and use Kubernetes to manage underlying computing compute resources.

Data-driven 75

Data-driven Metadata Testing Management 75

Rocket-Powered Data Science

FEBRUARY 15, 2023

While generative AI has been around for several years , the arrival of ChatGPT (a conversational AI tool for all business occasions, built and trained from large language models) has been like a brilliant torch brought into a dark room, illuminating many previously unseen opportunities.

Strategy 290

Strategy Experimentation Uncertainty Machine Learning 290

CIO Business Intelligence

MAY 29, 2024

There was a definite buzz about cybersecurity investments and M&A picking up steam, AI-based defense and AI-delivered industry models, and overall product innovation. Increased AI attacks AI adoption in the enterprise is driving a wave to protect the AI models and the data they are training.

Machine Learning 131

Machine Learning Enterprise Data-driven Modeling 131

CIO Business Intelligence

MARCH 8, 2023

The security-shared-responsibility model is essential when choosing as-a-service offerings, which make a third-party partner responsible for some element of the enterprise operational model. But outsourcing operational risk is untenable, given the criticality of data-first modernization to overall enterprise success.

Modeling 95

Modeling Risk Management Internet of Things Risk 95

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

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

Domino Data Lab

NOVEMBER 14, 2019

This Domino Data Science Field Note covers a proposed definition of interpretability and distilled overview of the PDR framework. James Murdoch, Chandan Singh, Karl Kumber, and Reza Abbasi-Asi’s recent paper, “Definitions, methods, and applications in interpretable machine learning” Introduction.

Modeling 71

Modeling Machine Learning Data Science Experimentation 71

CIO Business Intelligence

MAY 7, 2024

Chief data officers have a lot to think about these days. Chief among them, they must ensure responsible, compliant use of their organizations’ data in the face of increasingly complex regulatory environments across the globe. At the end of the day, it’s all the company’s data or the consumer’s data,” he adds.

Data Strategy 131

Data Strategy Data-driven Data Quality Strategy 131

Domino Data Lab

AUGUST 6, 2021

Model Risk Management is about reducing bad consequences of decisions caused by trusting incorrect or misused model outputs. An enterprise starts by using a framework to formalize its processes and procedures, which gets increasingly difficult as data science programs grow. What Is Model Risk? Types of Model Risk.

Risk Management 64

Risk Management Risk Modeling Enterprise 64

CIO Business Intelligence

NOVEMBER 14, 2022

Decision support systems definition A decision support system (DSS) is an interactive information system that analyzes large volumes of data for informing business decisions. A DSS leverages a combination of raw data, documents, personal knowledge, and/or business models to help users make decisions.

Data mining 144

Data mining Data-driven Statistics OLAP 144

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. And these models, though they lag behind the big commercial ones, are improving quickly.

Modeling 137

Modeling Risk Software Enterprise 137

CIO Business Intelligence

APRIL 30, 2024

The law will create new mandates for organizations to validate, monitor, and audit the entire AI lifecycle, says Kjell Carlsson, head of AI strategy at Domino Data Lab, a data science and AI company. The transparency and monitoring requirements will be a new experience for some organizations, Domino Data Lab’s Carlsson says.

IT 115

IT Risk Data-driven Modeling 115

DataKitchen

DECEMBER 9, 2022

ChatGPT> DataOps, or data operations, is a set of practices and technologies that organizations use to improve the speed, quality, and reliability of their data analytics processes. The goal of DataOps is to help organizations make better use of their data to drive business decisions and improve outcomes.

Machine Learning 130

Machine Learning Data-driven Optimization Modeling 130

CIO Business Intelligence

NOVEMBER 17, 2023

Turner helps drive that success by wearing two hats for the company: He oversees a product-driven organization that must develop and deliver innovative services out to hotel owners and guests continuously even as his teams continue to build out IHG’s internal technology stack and services.

Forecasting 132

Forecasting Consulting Data-driven Digital Transformation 132

erwin

APRIL 4, 2022

If you’re a long-time erwin ® Data Modeler by Quest ® customer, you might be asking yourself, “What happened to the release naming convention of erwin Data Modeler?” In 2021 erwin Data Modeler released 2021R1. What’s new in erwin Data Modeler R12.0? Google Big Query. Couchbase 7.0.

Modeling 52

Modeling Data Processing Data-driven Big Data 52

erwin

JUNE 7, 2022

Designing databases for data warehouses or data marts is intrinsically much different than designing for traditional OLTP systems. Accordingly, data modelers must embrace some new tricks when designing data warehouses and data marts. Figure 1: Pricing for a 4 TB data warehouse in AWS. Data Modeling.

Data Warehouse 52

Data Warehouse Modeling Sales Data Lake 52

CIO Business Intelligence

FEBRUARY 14, 2023

By George Trujillo, Principal Data Strategist, DataStax Increased operational efficiencies at airports. To succeed with real-time AI, data ecosystems need to excel at handling fast-moving streams of events, operational data, and machine learning models to leverage insights and automate decision-making.

Data Strategy 116

Data Strategy Strategy Machine Learning Data-driven 116

CIO Business Intelligence

JUNE 3, 2024

For generative AI, a stubborn fact is that it consumes very large quantities of compute cycles, data storage, network bandwidth, electrical power, and air conditioning. But the sheer quantity of infrastructure needed to process genAI’s large language models (LLMs), along with power and cooling requirements, is fast becoming unsustainable.

Data Processing 80

Data Processing Data-driven Modeling Strategy 80

CIO Business Intelligence

DECEMBER 19, 2023

After all, every department is pressured to drive efficiencies and is clamoring for automation, data capabilities, and improvements in employee experiences, some of which could be addressed with generative AI. As every CIO can attest, the aggregate demand for IT and data capabilities is straining their IT leadership teams.

Digital Transformation 143

Digital Transformation Unstructured Data Machine Learning Risk Management 143

erwin

SEPTEMBER 5, 2022

As with part 1 , part 2 ,and part 3 of this data modeling blog series, this blog also stresses that the cloud is not nirvana. Data modeling best practices. So, good relational design as covered in part 1 of this data modeling blog series holds true. Yes, it offers essentially infinitely scalable resources.

Modeling 52

Modeling Cost-Benefit Testing Data-driven 52

CIO Business Intelligence

MAY 2, 2023

Worse is when prioritized initiatives don’t have a documented shared vision, including a definition of the customer, targeted value propositions, and achievable success criteria. But are product managers developing market- and customer-driven roadmaps and prioritized backlogs?

Digital Transformation 141

Digital Transformation IT Data-driven Metrics 141

Peter James Thomas

AUGUST 4, 2020

A revised and expanded version of the peterjamesthomas.com Data and Analytics Dictionary has been published. The new Dictionary includes 22 additional definitions, bringing the total number of entries to 220, totalling well over twenty thousand words. Conformed Data (Conformed Dimension). Data Capability. Data Driven.

Data Analytics 98

Data Analytics Analytics Machine Learning Data Governance 98

Octopai

APRIL 20, 2023

Data mesh is an approach to data architecture that is intentionally distributed, where data is owned and governed by domain-specific teams who treat the data as a product to be consumed by other domain-specific teams. What are the principles behind data mesh architecture?

Data-driven 77

Data-driven Data Architecture Sales Modeling 77

Birst BI

JANUARY 16, 2018

If you’re a business intelligence (BI) and analytics application user, it’s likely that “data-driven insight to the masses” will soon be top-of-mind. Some data discovery vendors tout that they already deliver “self-service to the masses,” but that’s a dubious claim. Machine learning will transform BI and analytics.

Data-driven 70

Data-driven Analytics Dashboards Machine Learning 70

CIO Business Intelligence

JULY 28, 2023

JLL, for instance, provides facilities management services for many cloud and data center operators. More recently, the company launched Carbon Pathfinder, an AI-driven sustainability software planning tool that is sold as SaaS or a suite with professional services.

Structured Data 98

Structured Data Software Data-driven Modeling 98

AWS Big Data

MAY 23, 2024

In today’s data-driven world, organizations often deal with data from multiple sources, leading to challenges in data integration and governance. This process is crucial for maintaining data integrity and avoiding duplication that could skew analytics and insights.

Machine Learning 98

Machine Learning Interactive Recreation/Entertainment Data Integration 98

Cloudera

SEPTEMBER 29, 2022

Data teams have the impossible task of delivering everything (data and workloads) everywhere (on premise and in all clouds) all at once (with little to no latency). Each of these trends claim to be complete models for their data architectures to solve the “everything everywhere all at once” problem. Data mesh defined.

Data Architecture 76

Data Architecture Metadata Data Warehouse Sales 76

erwin

JANUARY 14, 2021

These surveys helped IDC develop a model that describes the five stages of enterprise recovery , aligning business focus with the economic situation: When the COVID-19 crisis hit, organizations focused on business continuity. When the pandemic first hit, there was some negative impact on big data and analytics spending.

Digital Transformation 143

Digital Transformation Metadata Big Data Data-driven 143

Domino Data Lab

OCTOBER 16, 2019

This article covers a couple of key Machine Learning (ML) vital signs to consider when tracking ML models in production to ensure model reliability, consistency and performance in the future. Machine learning models: running wild. They may also experience relief when the model “works” in production.

Metrics 49

Metrics Modeling Machine Learning Measurement 49

IBM Big Data Hub

MAY 6, 2024

Optimize protocols using historical and synthetic data Complex and stringent protocols are notorious for delaying clinical trials and eroding patient engagement. Diving deep into historical trial data with a protocol complexity rating also reveals golden insights, especially around patient-centric elements.

Advertising 81

Advertising Data-driven Optimization Strategy 81

Rocket-Powered Data Science

JULY 7, 2019

Definitions of terminology frequently seen and used in discussions of emerging digital technologies. AGI (Artificial General Intelligence): AI (Artificial Intelligence): Application of Machine Learning algorithms to robotics and machines (including bots), focused on taking actions based on sensory inputs (data). Career Relevance.

Internet of Things 157

Internet of Things Machine Learning Manufacturing IoT 157