Analytics Vidhya

MAY 26, 2022

Introduction What are Large Language Models(LLM)? Most of you definitely faced this question in your data science journey. Large Language Models are often tens of terabytes in size and are trained on massive volumes of text data, occasionally reaching petabytes. They’re also among the models with the most […].

Data Science 347

Data Science Publishing Modeling Analytics 347

FineReport

JUNE 11, 2021

This article will discuss the definition of business intelligence and analytics and the difference between them. Definition. According to the definition, business intelligence and analytics refer to the data management solutions implemented in companies to collect, analyze and drive insights from data.

Business Intelligence 52

Business Intelligence Analytics Dashboards Statistics 52

erwin

AUGUST 20, 2020

As organization’s become increasingly complex, agile enterprise architecture can help organizations avoid over-analysis – often dubbed “analysis paralysis” – and take a “just-in-time”, “just-enough” approach to modeling. Why Is Enterprise Architecture Important?

Enterprise 140

Enterprise Cost-Benefit Risk Data Governance 140

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. As machine learning advances globally, we can only expect the focus on model risk to continue to increase.

Risk 111

Risk Modeling IT Risk Management 111

FineReport

APRIL 9, 2021

It often happens in very new sectors or in companies whose business models are relatively innovative. Financial Reporting & Financial Analysis: Definitive Guide shows at FineReport first. By comparison with peers, a financial analyst can detect the strengths and shortcomings which may always be meaningful for future enhancement.

Reporting 98

Reporting Finance Dashboards Enterprise 98

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

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. Data modeling basics.

Modeling 98

Modeling Insurance Cost-Benefit Data Warehouse 98

FineReport

MAY 31, 2023

Dupont Analysis Dashboard FineReport simplifies the implementation of the Dupont analysis model, enabling an in-depth examination of an enterprise’s financial condition through Return on Investment (ROI). The Dupont analysis model comprises three key components: profit margin, asset turnover, and equity multiplier.

Dashboards 52

Dashboards Key Performance Indicator Metrics Visualization 52

O'Reilly on Data

MARCH 26, 2024

TL;DR LLMs and other GenAI models can reproduce significant chunks of training data. Researchers are finding more and more ways to extract training data from ChatGPT and other models. And the space is moving quickly: SORA , OpenAI’s text-to-video model, is yet to be released and has already taken the world by storm.

Modeling 275

Modeling Machine Learning Risk Advertising 275

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

DataRobot Blog

MAY 10, 2022

Addressing the Key Mandates of a Modern Model Risk Management Framework (MRM) When Leveraging Machine Learning . The regulatory guidance presented in these documents laid the foundation for evaluating and managing model risk for financial institutions across the United States.

Risk 64

Risk Modeling Machine Learning Data Quality 64

IBM Big Data Hub

APRIL 4, 2023

We taught an AI model to analyze Masters video and produce highlight reels for every player, minutes after their round is complete. We built models that generate scoring predictions for every player on every hole. The second need is closely related, and really applies to any AI model used in a corporate setting.

Modeling 89

Modeling Consulting Metadata Enterprise 89

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. Yet, Bin Yu, W.

Modeling 71

Modeling Machine Learning Data Science Experimentation 71

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. As with the part 1 and part 2 of this data modeling blog series, the cloud is not nirvana. Data modeling basics. Data Modeling. This blog is based upon a recent webcast that can be viewed here.

Data Lake 52

Data Lake Modeling Unstructured Data Data Warehouse 52

KDnuggets

JUNE 19, 2023

In this article we will learn about its definition, differences and how to calculate FLOPs and MACs using Python packages.

Deep Learning 97

Deep Learning Modeling IT Machine Learning 97

IBM Big Data Hub

APRIL 13, 2023

After developing a machine learning model, you need a place to run your model and serve predictions. If your company is in the early stage of its AI journey or has budget constraints, you may struggle to find a deployment system for your model. Also, a column in the dataset indicates if each flight had arrived on time or late.

Modeling 93

Modeling Statistics Machine Learning Testing 93

CIO Business Intelligence

APRIL 11, 2023

Over the next five years, the healthcare industry is expected to go through dramatic changes as service providers expand value-based care models and equipment manufacturers strive to keep pace in a digital-first world. Betadam: I think there is definitely a slowdown in innovation activities, especially during times of economic uncertainty.

Modeling 98

Modeling IT Strategy Uncertainty 98

O'Reilly on Data

FEBRUARY 15, 2022

But a recent discussion of Google’s new Large Language Models (LLMs), and its claim that one of these models (named Gopher) has demonstrated reading comprehension approaching human performance , has spurred some thoughts about comprehension, ambiguity, intelligence, and will. That definition itself is ambiguous.

Testing 293

Testing Modeling Measurement IT 293

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. The security-shared-responsibility model provides a clear definition of the roles and responsibilities for security.”

Modeling 90

Modeling Risk Management Internet of Things Risk 90

Ontotext

OCTOBER 12, 2023

Did you know that, if you add “take a deep breath” to a prompt, chances are you will get more accurate results from Large Language Models (LLMs)? Do Knowledge Graphs Dream of Large Language Models? I didn’t either. He shared the need for more research at the intersection of LLMs and knowledge graphs.

Modeling 75

Modeling Recreation/Entertainment Data Processing Metadata 75

TDAN

AUGUST 18, 2020

The business glossary is simple in concept, but it can be a challenge to structure, define and maintain shared business terminology. Consistent business meaning is important because distinctions between business terms are not typically well defined or documented.

Management 96

Management Metadata Data Architecture IT 96

erwin

MAY 14, 2021

But even though speed is critical, businesses must take the time to model and document new applications for compliance and transparency. 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.

Modeling 80

Modeling Digital Transformation Data-driven Optimization 80

Domino Data Lab

SEPTEMBER 10, 2020

Building models requires a lot of time and effort. Data scientists can spend weeks just trying to find, capture and transform data into decent features for models, not to mention many cycles of training, tuning, and tweaking models so they’re performant. Certainly, organizations need to hire expert data science professionals.

Modeling 101

Modeling IT Data Science Experimentation 101

Domino Data Lab

AUGUST 6, 2021

Model Risk Management is about reducing bad consequences of decisions caused by trusting incorrect or misused model outputs. Systematically enabling model development and production deployment at scale entails use of an Enterprise MLOps platform, which addresses the full lifecycle including Model Risk Management.

Risk Management 64

Risk Management Risk Modeling Enterprise 64

Rocket-Powered Data Science

SEPTEMBER 25, 2022

This is all fueled and facilitated by data flows across processes, products, and people’s activities, used in synergy with computational models and simulations of the system being digitally twinned. Beyond being a technical how-to manual (though it is definitely that), this book delivers so much more! 6) Specific Industry 4.0

Diagnostic Analytics 214

Diagnostic Analytics Prescriptive Analytics Internet of Things IoT 214

AWS Big Data

OCTOBER 26, 2023

Data analysts and database developers want to use this data to train machine learning (ML) models, which can then be used to generate insights on new data for use cases such as forecasting revenue, predicting customer churn, and detecting anomalies. We also need an offline feature store to store features in feature groups.

Modeling 62

Modeling Data Warehouse Machine Learning Testing 62

Decision Management Solutions

APRIL 12, 2021

James Taylor, CEO of Decision Management Solutions, will be teaching this three part live training on Decision Modeling with DMN. WHAT IT IS: DMN is Decision Modeling Notation, and it is a fast becoming the standard and definitive approach for decision modeling. It also helps to frame requirements for analytic projects.

Modeling 52

Modeling Dashboards Management Reporting 52

DataKitchen

MARCH 12, 2024

Thanks to Observability, I could diagnose the problem – definitely helped me a lot during the process.” It’s definitive, and that changes the game, especially for senior leadership.” DataKitchen helped us completely transform our operations by broadening our testing definition. That was amazing for the team.”

Metrics 120

Metrics Software Cost-Benefit Testing 120

CIO Business Intelligence

APRIL 30, 2024

Between the astronomical fines, sweeping scope, and unclear definitions, every organization operating in the EU now runs a potentially lethal risk in their AI-, ML-, and analytics-driven activities.” “With the passing of the EU AI act, the scariest thing about AI is now, unequivocally, AI regulation itself,” Carlsson says.

IT 110

IT Risk Data-driven Modeling 110

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. So, this release of erwin Data Modeler aligns with the release of erwin Data Intelligence 12.0,” he concluded. “So,

Modeling 52

Modeling Data Processing Data-driven Big Data 52

DataRobot

JUNE 17, 2021

Personally, I think there are definitely horizons in math, biology, and physics that we may never reach… but maybe AI can change that. At the time, I had a small following of people interested in using Eureqa to derive mathematical formulas and models. What Makes Eureqa Models Different from other Models.

Modeling 52

Modeling Experimentation Machine Learning Measurement 52

erwin

JUNE 7, 2022

Accordingly, data modelers must embrace some new tricks when designing data warehouses and data marts. Data modeling for the cloud: good database design means “right size” and savings. Now to cover some data modeling basics that applies no matter whether on-premises or in the cloud. Data Modeling. Business Focus.

Data Warehouse 52

Data Warehouse Modeling Sales Data Lake 52

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. So, if you have 1 trillion data points (g.,

Strategy 289

Strategy Experimentation Uncertainty Machine Learning 289

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. Are there data modeling tools to assist with such an effort?

Modeling 52

Modeling Cost-Benefit Testing Data-driven 52

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 128

Testing Modeling Cost-Benefit Reporting 128

Occam's Razor

SEPTEMBER 15, 2011

Winners, well before they think data or tool, have a well structured Digital Marketing & Measurement Model. This article guides you in understanding the value of the Digital Marketing & Measurement Model (notice the repeated emphasis on Marketing, not just Measurement), and how to create one for yourself. Losers don't.

Measurement 166

Measurement Marketing Modeling Key Performance Indicator 166

CIO Business Intelligence

MAY 7, 2024

One possible definition of the CDO is the organization’s leader responsible for data governance and use, including data analysis , mining , and processing. Part of the challenge is to capture the right amount of data needed to train large language models for specialized tasks at each organization, she says.

Data Strategy 119

Data Strategy Data-driven Data Quality Strategy 119