Ontotext

JANUARY 10, 2024

In Computer Science, we are trained to use the Okham razor – the simplest model of reality that can get the job done is the best one. And each of these gains requires data integration across business lines and divisions. We call this the Bad Data Tax. So, how to manage this complexity better?

Metadata 72

Metadata Slice and Dice Data Integration Enterprise 72

erwin

MAY 14, 2021

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. The Newest Release of erwin Data Modeler.

Modeling 80

Modeling Digital Transformation Data-driven Optimization 80

erwin

MAY 13, 2020

The role of data modeling (DM) has expanded to support enterprise data management, including data governance and intelligence efforts. Metadata management is the key to managing and governing your data and drawing intelligence from it. Types of Data Models: Conceptual, Logical and Physical.

Data Governance 93

Data Governance Modeling Enterprise Management 93

Ontotext

JULY 11, 2019

Ontotext’s GraphDB is an enterprise-ready semantic graph database (also called RDF triplestore because it stores data in RDF triples). It provides the core infrastructure for solutions where modelling agility, data integration, relationship exploration, cross-enterprise data publishing and consumption are critical. .

Statistics 40

Statistics Modeling Metadata Enterprise 40

IBM Big Data Hub

JANUARY 9, 2024

Companies still often accept the risk of using internal data when exploring large language models (LLMs) because this contextual data is what enables LLMs to change from general-purpose to domain-specific knowledge. In the generative AI or traditional AI development cycle, data ingestion serves as the entry point.

Enterprise 73

Enterprise Data Integration Data Quality Contextual Data 73

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. Choose Create notebook. b.id )) """).write.mode("overwrite").parquet(f"s3://{bucket_name}/models/1/trainingData/marked/")

Machine Learning 96

Machine Learning Interactive Recreation/Entertainment Data Integration 96

Ontotext

JUNE 27, 2019

Ontotext’s GraphDB is an enterprise-ready semantic graph database (also called RDF triplestore as it stores data in RDF triples). It provides the core infrastructure for solutions where modeling agility, data integration, relationship exploration, cross-enterprise data publishing and consumption are critical.

Metadata 40

Metadata Management Enterprise Optimization 40

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

APRIL 1, 2024

Capturing the “as-is” state of your environment, you’ll develop topology diagrams and document information on your technical systems. Data preparation, including anonymizing, labeling, and normalizing data across sources, is key. Right-size your model(s). Assess your readiness. Choose a workload location.

Data Lake 117

Data Lake Consulting Uncertainty Risk 117

Rocket-Powered Data Science

JULY 6, 2021

So, there must be a strategy regarding who, what, when, where, why, and how is the organization’s content to be indexed, stored, accessed, delivered, used, and documented. That is, use AI and machine learning techniques on digital content (databases, documents, images, videos, press releases, forms, web content, social network posts, etc.)

Strategy 267

Strategy Machine Learning Metadata Knowledge Discovery 267

AWS Big Data

APRIL 17, 2024

In this post, we discuss how the reimagined data flow works with OR1 instances and how it can provide high indexing throughput and durability using a new physical replication protocol. We also dive deep into some of the challenges we solved to maintain correctness and data integrity.

Optimization 114

Optimization Snapshot Metadata Cost-Benefit 114

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? DevOps GitHub integration via Mart.

Modeling 52

Modeling Data Processing Data-driven Big Data 52

AWS Big Data

MAY 21, 2024

A significant part of this phase involved the innovative process of data flattening, a technique crucial for managing complex product data. This product is linked to several related tables: one for basic details like model number and manufacturer, another for pricing, and another for features such as energy efficiency and capacity.

Manufacturing 97

Manufacturing Sales Optimization Data Processing 97

CIO Business Intelligence

MARCH 6, 2024

SAP unveiled Datasphere a year ago as a comprehensive data service, built on SAP Business Technology Platform (BTP), to provide a unified experience for data integration, data cataloging, semantic modeling, data warehousing, data federation, and data virtualization.

Unstructured Data 104

Unstructured Data Dashboards Business Intelligence Data Governance 104

CIO Business Intelligence

NOVEMBER 21, 2023

Set parameters and emphasize collaboration To address one root cause of shadow IT, CIOs must also establish a governance and delivery model for evaluating, procuring, and implementing department technology solutions.

IT 124

IT Risk Cost-Benefit Risk Management 124

O'Reilly on Data

JUNE 18, 2019

Machine learning solutions for data integration, cleaning, and data generation are beginning to emerge. “AI AI starts with ‘good’ data” is a statement that receives wide agreement from data scientists, analysts, and business owners. The problem is even more magnified in the case of structured enterprise data.

Machine Learning 255

Machine Learning Data Quality Statistics Modeling 255

AWS Big Data

NOVEMBER 29, 2023

It enables data engineers, data scientists, and analytics engineers to define the business logic with SQL select statements and eliminates the need to write boilerplate data manipulation language (DML) and data definition language (DDL) expressions. Data engineers define dbt models for their data representations.

Data Lake 103

Data Lake Management Metrics Data Warehouse 103

AWS Big Data

FEBRUARY 29, 2024

Data is your generative AI differentiator, and a successful generative AI implementation depends on a robust data strategy incorporating a comprehensive data governance approach. Data governance is a critical building block across all these approaches, and we see two emerging areas of focus.

Data Governance 95

Data Governance Unstructured Data Metadata Data Lake 95

Cloudera

AUGUST 28, 2023

The release of ChatGPT pushed the interest in and expectations of Large Language Model based use cases to record heights. Privacy concerns loom large, as many enterprises are cautious about sharing their internal knowledge base with external providers to safeguard data integrity.

Enterprise 76

Enterprise Machine Learning Modeling Data Processing 76

CIO Business Intelligence

MARCH 24, 2023

It encompasses the people, processes, and technologies required to manage and protect data assets. The Data Management Association (DAMA) International defines it as the “planning, oversight, and control over management of data and the use of data and data-related sources.”

Data Governance 142

Data Governance Management Metadata Data Quality 142

CIO Business Intelligence

NOVEMBER 7, 2023

Opting for a centralized data and reporting model rather than training and embedding analysts in individual departments has allowed us to stay nimble and responsive to meet urgent needs, and prevented us from spending valuable resources on low-value data projects which often had little organizational impact,” Higginson says.

Data Warehouse 135

Data Warehouse Digital Transformation Data-driven Reporting 135

erwin

OCTOBER 8, 2020

But even with the “need for speed” to market, new applications must be modeled and documented for compliance, transparency and stakeholder literacy. The metadata-driven suite automatically finds, models, ingests, catalogs and governs cloud data assets. Subscribe to the erwin Expert Blog.

Data Governance 145

Data Governance Metadata Testing Data Lake 145

O'Reilly on Data

OCTOBER 11, 2022

We’ll see it in the processing of the thousands of documents businesses handle every day. So from the start, we have a data integration problem compounded with a compliance problem. Data integration problems aren’t pretty; they’re boring, uninteresting, the “killing field of any modeling project,” as Lorien Pratt has said.

Data Integration 286

Data Integration Insurance Dashboards Modeling 286

CIO Business Intelligence

JULY 6, 2023

Classic examples are the use of AI to capture and convert semi-structured documents such as purchase orders and invoices, Fleming says. We’re equipping this tool with a private ‘knowledge base’ of AT&T-specific data, with chat enabled to get answers directly from these internal AT&T documents and materials.”

Cost-Benefit 110

Cost-Benefit Technology Unstructured Data Testing 110

IBM Big Data Hub

JANUARY 26, 2024

AI intelligent maintenance diagnosis : AI intelligent maintenance and diagnosis uses AI technology and intelligent diagnostic models to guide technicians in diagnosing faults in the form of questions and answers. Likewise, it can provide best practice repair methods based on historical data and sort the matching degree.

Cost-Benefit 72

Cost-Benefit Enterprise Technology KPI 72

IBM Big Data Hub

OCTOBER 12, 2023

Connecting AI models to a myriad of data sources across cloud and on-premises environments AI models rely on vast amounts of data for training. Once trained and deployed, models also need reliable access to historical and real-time data to generate content, make recommendations, detect errors, send proactive alerts, etc.

Cost-Benefit 77

Cost-Benefit Metadata Data Governance Modeling 77

CIO Business Intelligence

JANUARY 5, 2023

Many customers find the sweet spot in combining them with similar low code/no code tools for data integration and management to quickly automate standard tasks, and experiment with new services. This is especially true for routine, well-defined functions such as managing documents and workflows.

IT 116

IT Cost-Benefit Testing Dashboards 116

CIO Business Intelligence

NOVEMBER 17, 2022

A key component to the appeal of cloud-first business models is cloud technologies’ ability to simplify processes and streamline workflows through integration and automation. This is especially true for content management operations looking to navigate the complexities of data compliance while getting the most from their data.

Software 127

Software Management Digital Transformation Data Governance 127

Cloudera

JUNE 1, 2021

This means we can double down on our strategy – continuing to win the Hybrid Data Cloud battle in the IT department AND building new, easy-to-use cloud solutions for the line of business. It also means we can complete our business transformation with the systems, processes and people that support a new operating model. .

Uncertainty 144

Uncertainty Cost-Benefit Risk Strategy 144

CIO Business Intelligence

NOVEMBER 18, 2022

3M 360 Encompass is a collection of applications that work together to help hospitals streamline processes, receive accurate reimbursement, promote compliance, and make data-informed decisions. This is a dynamic view on data that evolves over time,” said Koll. The cloud served as the foundation for this transformation.

Insurance 73

Insurance Contextual Data Testing Unstructured Data 73

Ontotext

FEBRUARY 26, 2024

From a technological perspective, RED combines a sophisticated knowledge graph with large language models (LLM) for improved natural language processing (NLP), data integration, search and information discovery, built on top of the metaphactory platform. Let’s have a quick look under the bonnet.

Data-driven 59

Data-driven Risk Modeling Risk Management 59

IBM Big Data Hub

OCTOBER 20, 2023

Artificial intelligence platforms enable individuals to create, evaluate, implement and update machine learning (ML) and deep learning models in a more scalable way. AI platform tools enable knowledge workers to analyze data, formulate predictions and execute tasks with greater speed and precision than they can manually.

Machine Learning 72

Machine Learning Manufacturing Cost-Benefit Deep Learning 72

CIO Business Intelligence

MARCH 21, 2022

Way back in 1999, his team did a cost-benefit analysis of the free shipping model, which is arguably one of the key drivers of Amazon’s stupendous growth. This is the impact of data-driven financial analysis – or what is termed FP&A – in the business context. billion a year. Lost productivity.

Data-driven 98

Data-driven IT Finance Forecasting 98

erwin

JANUARY 30, 2020

Organizations also are experiencing multiple bottlenecks in their data value chains, including documenting complete data lineage, understanding the quality of source data, and finding, identifying and harvesting data assets and curating assets with business context. Stop Wasting Your Time.

Data Governance 145

Data Governance Metadata Cost-Benefit Digital Transformation 145

AWS Big Data

JULY 25, 2023

Redshift Serverless automatically provisions and intelligently scales data warehouse capacity to deliver fast performance for even the most demanding and unpredictable workloads, and you pay only for what you use. Solution overview The integration of Talend with Amazon Redshift adds new features and capabilities.

Data Analytics 52

Data Analytics Data Warehouse Analytics Data Processing 52

Smart Data Collective

OCTOBER 19, 2022

What Are Their Ranges of Data Models? MongoDB has a wider range of datatypes than DynamoDB, even though both databases can store binary data. DynamoDB is limited to 400KB for documents and MongoDB can support up to 16MB file sizes. It is compatible with a laptop to mainframe and on-premise through a hybrid cloud.

Big Data 110

Big Data Management Cost-Benefit Recreation/Entertainment 110

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. We are planning to develop or use AI-based tools for each of these problems.

Unstructured Data 64

Unstructured Data Structured Data Publishing Machine Learning 64