erwin

JANUARY 17, 2020

What is Data Modeling? Data modeling is a process that enables organizations to discover, design, visualize, standardize and deploy high-quality data assets through an intuitive, graphical interface. Data models provide visualization, create additional metadata and standardize data design across the enterprise.

Data-driven 138

Data-driven Modeling Metadata Data Governance 138

CIO Business Intelligence

DECEMBER 19, 2023

Many technology investments are merely transitionary, taking something done today and upgrading it to a better capability without necessarily transforming the business or operating model. Improving search capabilities and addressing unstructured data processing challenges are key gaps for CIOs who want to deliver generative AI capabilities.

Digital Transformation 143

Digital Transformation Unstructured Data Machine Learning Risk Management 143

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. Data modeling basics.

Data Lake 52

Data Lake Modeling Unstructured Data Data Warehouse 52

IBM Big Data Hub

NOVEMBER 29, 2023

Non-symbolic AI can be useful for transforming unstructured data into organized, meaningful information. This helps to simplify data analysis and enable informed decision-making. Events as fuel for AI Models: Artificial intelligence models rely on big data to refine the effectiveness of their capabilities.

Unstructured Data 92

Unstructured Data Data-driven ROI Machine Learning 92

Analytics Vidhya

DECEMBER 1, 2023

Many tools and applications are being built around this concept, like vector stores, retrieval frameworks, and LLMs, making it convenient to work with custom documents, especially Semi-structured Data with Langchain. Introduction Retrieval Augmented Generation has been here for a while.

Structured Data 304

Structured Data Analytics Unstructured Data IT 304

CIO Business Intelligence

AUGUST 11, 2023

How natural language processing works NLP leverages machine learning (ML) algorithms trained on unstructured data, typically text, to analyze how elements of human language are structured together to impart meaning. Transformer models take applications such as language translation and chatbots to a new level.

Unstructured Data 142

Unstructured Data Modeling Machine Learning Data mining 142

O'Reilly on Data

NOVEMBER 18, 2019

Highlights from the interview include: The biggest hurdle businesses face when implementing machine learning or AI solutions is cleaning and preparing unstructured data that exists across silos. So, it’s going to be less about the models, per se—it’s going to be more about the use cases and applications of those models.”

ROI 132

ROI Unstructured Data Machine Learning Modeling 132

IBM Big Data Hub

AUGUST 22, 2023

It uses real-world data (both real time and historical) combined with engineering, simulation or machine learning (ML) models to enhance operations and support human decision-making. Traditional AI models versus foundation models These capabilities can help to continuously determine the state of the physical object.

Unstructured Data 82

Unstructured Data Consulting Visualization IoT 82

AWS Big Data

MARCH 25, 2024

Foundation models (FMs) are large machine learning (ML) models trained on a broad spectrum of unlabeled and generalized datasets. This scale and general-purpose adaptability are what makes FMs different from traditional ML models. FMs are multimodal; they work with different data types such as text, video, audio, and images.

Data Lake 86

Data Lake Unstructured Data Management Modeling 86

CIO Business Intelligence

SEPTEMBER 29, 2023

That’s because generative AI large language models (LLMs) have prowess in text-based generation, readily finding language and word patterns. That’s because vast, real-time, unstructured data sets are used to build, train, and implement generative AI. Regulatory compliance. Financial assistant. Automation.

Finance 133

Finance Unstructured Data Risk Cost-Benefit 133

Alation

JUNE 2, 2022

Data management is not yet a solved problem, but modern data management is leagues ahead of prior approaches. These include tracking, documenting, monitoring, versioning, and controlling access to AI/ML models. Governance is frequently administered at the tool, modeler, or departmental level. from cognilytica.

Modeling 52

Modeling Data Governance Statistics Unstructured Data 52

CIO Business Intelligence

DECEMBER 19, 2023

Verifying that bonds are ERISA-compliant has historically been a manual process involving a thorough review of documentation and legal history. Auditing a 401(k)-plan document manually can cost up to $7,500 and consume about 45 hours of a skilled professional’s time.

Risk 52

Risk Cost-Benefit Unstructured Data Data-driven 52

Ontotext

OCTOBER 19, 2023

We need to solve many problems, including deduplication of data that refers to the same entity, extracting structured data within narratives in different languages, as well as mapping them to a common and international ontology. Cleaning and integrating this data to create a unified and accurate patient profile is essential.

Unstructured Data 64

Unstructured Data Structured Data Publishing Machine Learning 64

CIO Business Intelligence

MARCH 7, 2023

Vince Kellen understands the well-documented limitations of ChatGPT, DALL-E and other generative AI technologies — that answers may not be truthful, generated images may lack compositional integrity, and outputs may be biased — but he’s moving ahead anyway. And, he says, using generative AI for coding has worked well.

Enterprise 116

Enterprise IT Experimentation Unstructured Data 116

CIO Business Intelligence

NOVEMBER 1, 2023

SAP doesn’t want to build those tools from scratch itself: “We definitely want to leverage what’s already out there,” Sun said, noting there are already many large language models (LLMs) it can build on, adding its own prompting, fine tuning, and data embedding to get those models to business customers quickly.

Enterprise 132

Enterprise Cost-Benefit Unstructured Data Software 132

Smart Data Collective

MAY 1, 2022

This problem will not stop as more documents and other types of information are collected and stored. This will eventually lead you to situations where you know that valuable data is inside these documents, but you cannot extract them. . If data had to be sorted manually, it would easily take months or even years to do it.

Cost-Benefit 117

Cost-Benefit Unstructured Data Machine Learning Marketing 117

CIO Business Intelligence

DECEMBER 11, 2023

Any and all activities that focus on improving patient data, processes and communications are prime for improvement. With generative AI-based analytics and large language models, healthcare professionals will have a greater capacity to make tailored recommendations for preventative screenings and services.

Unstructured Data 75

Unstructured Data Interactive Data-driven Consulting 75

CIO Business Intelligence

JANUARY 22, 2024

Unlike prior chatbots and other digital point solutions, generative AI technology is transformative because it unlocks the power of unstructured data to create new content. In addition, large language models can both summarize massive amounts of data and create new, original content.

Cost-Benefit 105

Cost-Benefit Digital Transformation Data-driven Interactive 105

CIO Business Intelligence

DECEMBER 4, 2023

Although less complex than the “4 Vs” of big data (velocity, veracity, volume, and variety), orienting to the variety and volume of a challenging puzzle is similar to what CIOs face with information management. When data is stored in a modern, accessible repository, organizations gain newfound capabilities. Preserve/Dispose.

Unstructured Data 52

Unstructured Data Data Lake Business Objectives Metadata 52

CIO Business Intelligence

OCTOBER 13, 2023

Solutions data architect: These individuals design and implement data solutions for specific business needs, including data warehouses, data marts, and data lakes. Application data architect: The application data architect designs and implements data models for specific software applications.

Data Architecture 132

Data Architecture Data Warehouse Statistics Visualization 132

CIO Business Intelligence

FEBRUARY 23, 2024

Honda has plans to roll out Microsoft’s ChatGPT Enterprise, also called Copilot, for its Office 365 workers using Outlook or PowerPoint, for example, and is actively piloting a GitHub AI model to gain efficiencies in application development, application maintenance, and IT service processes that are primarily internal.

IT 122

IT Manufacturing Unstructured Data Strategy 122

IBM Big Data Hub

DECEMBER 4, 2023

The most common insurance use cases include optimizing processes that require processing large documents and large blocks of text or images. Customer engagement Providing insurance coverage involves working with numerous documents. IBM works with several insurance companies to identify high-value opportunities for using generative AI.

Insurance 55

Insurance Digital Transformation Risk Management Risk 55

Smart Data Collective

AUGUST 30, 2022

It also allows companies to offload large amounts of data from their networks by hosting it on remote servers anywhere on the globe. Cloud computing allows companies’ multiple servers to store and manage their data in a distributed fashion. Centralized data storage. Multi-cloud computing. Before you go.

Technology 133

Technology Enterprise Cost-Benefit Testing 133

Ontotext

DECEMBER 16, 2021

Companies in the life sciences face data challenges on two fronts: Volume. Organizations in this sector often deal with multiple repositories of millions of documents on top of proprietary data from labs and other internal sources. That information enhances the graph, which improves the NLP model. See figure 1.).

Metadata 98

Metadata Reporting Unstructured Data Risk 98

CIO Business Intelligence

JULY 14, 2023

Whether it’s text, images, video or, more likely, a combination of multiple models and services, taking advantage of generative AI is a ‘when, not if’ question for organizations. But many organizations are limiting use of public tools while they set policies to source and use generative AI models.

Modeling 98

Modeling Machine Learning Cost-Benefit B2B 98

CIO Business Intelligence

SEPTEMBER 21, 2023

AI is now a board-level priority Last year, AI consisted of point solutions and niche applications that used ML to predict behaviors, find patterns, and spot anomalies in carefully curated data sets. Today’s foundational models are jacks-of-all-trades. All of PwC’s clients are having this discussion, he says. Then gen AI came out.

Enterprise 130

Enterprise Consulting Modeling Cost-Benefit 130

Ontotext

JULY 20, 2023

With our technology we can cover most use cases in one go, our platform is data agnostic and can do text and speech in different languages. Most importantly, our knowledge modeling is done with knowledge graphs , which enables us to merge different data types and enable answering complex questions.

Manufacturing 52

Manufacturing Unstructured Data Structured Data Modeling 52

IBM Big Data Hub

JULY 12, 2023

Generative AI based on foundation models has brought us to this inflection point. By training their models with company-specific HR data, HR professionals can use AI to help with tasks like creating job postings, summarizing groups of incoming resumes and helping professionals better understand new policy documents.

Enterprise 59

Enterprise Unstructured Data Modeling Machine Learning 59

CIO Business Intelligence

JANUARY 16, 2024

Still, to ensure workers gain the most out of the tools, Mayar suggested multimodal LLMs combining structured datasets and unstructured data should be designed smaller and for specific tasks. It’s only been 13 months and it made time nonlinear,” he quipped. Thomson Reuters is one organization targeting gen AI for efficiency.

Cost-Benefit 130

Cost-Benefit Enterprise Unstructured Data Technology 130

CIO Business Intelligence

FEBRUARY 21, 2024

At the heart of the issue is retrieval-augmented generation (RAG), a natural language processing technique combining data retrieval with a GenAI model. Before moving forward, CIOs consider the problem they are trying to solve with RAG and how complex their data is, then compare their needs with each data architecture’s pros and cons.

Insurance 64

Insurance Unstructured Data Data Architecture Technology 64

IBM Big Data Hub

AUGUST 28, 2023

Text mining —also called text data mining—is an advanced discipline within data science that uses natural language processing (NLP) , artificial intelligence (AI) and machine learning models, and data mining techniques to derive pertinent qualitative information from unstructured text data.

Data mining 59

Data mining Machine Learning Deep Learning Marketing 59

AWS Big Data

OCTOBER 25, 2023

Unstructured data is information that doesn’t conform to a predefined schema or isn’t organized according to a preset data model. Unstructured information may have a little or a lot of structure but in ways that are unexpected or inconsistent. You can integrate different technologies or tools to build a solution.

Unstructured Data 115

Unstructured Data Metadata Management Analytics 115

Ontotext

MAY 25, 2023

The Master class that Peio delivered covered Reconciliation, Text Analytics and Virtualization with Knowledge Graphs, using GraphDB and Text Analysis services tailored explicitly for tasks demanding intricate domain knowledge and linking documents to reference or master data.

Machine Learning 52

Machine Learning Structured Data Unstructured Data Predictive Modeling 52

Sisense

AUGUST 18, 2019

It also supports hierarchical documentation of data. PostgreSQL is also open-source, but it’s a relational database that is much more concerned with standards compliance and extensibility than with giving you freedom over how you store data. they’re great for handling large volumes of unstructured data, at speed.

Unstructured Data 81

Unstructured Data Data Processing Dashboards Testing 81

Cloudera

SEPTEMBER 1, 2020

DDE also makes it much easier for application developers or data workers to self-service and get started with building insight applications or exploration services based on text or other unstructured data (i.e. data best served through Apache Solr). Stores source documents. What does DDE entail?

Snapshot 66

Snapshot Unstructured Data Dashboards Interactive 66

Ontotext

JANUARY 6, 2021

Having a formal definition that is both machine and human readable of enterprise-level models describing important and shared concepts across all business departments and reach agreement on common meta-data, reference and master data entities has an enormous value.

Metadata 59

Metadata Unstructured Data Cost-Benefit Enterprise 59

Ontotext

MARCH 18, 2020

According to an article in Harvard Business Review , cross-industry studies show that, on average, big enterprises actively use less than half of their structured data and sometimes about 1% of their unstructured data.

Enterprise 59

Enterprise B2B Unstructured Data Machine Learning 59