Ontotext

AUGUST 22, 2023

Central to today’s efficient business operations are the activities of data capturing and storage, search, sharing, and data analytics. Semantically integrated data makes metadata meaningful, allowing for better interpretation, improved search, and enhanced knowledge-discovery processes.

Metadata 52

Metadata Knowledge Discovery Big Data Enterprise 52

Ontotext

APRIL 6, 2023

To Wrap It Up Knowledge graphs play a vital role in connecting the data from siloed legacy systems and platforms, enabling seamless data sharing, knowledge discovery and analytics. This can lead to operational cost cutting and improve competitiveness.

Manufacturing 83

Manufacturing Cost-Benefit Knowledge Discovery Optimization 83

Ontotext

DECEMBER 30, 2019

As 2019 comes to an end, we at Ontotext are taking stock of the most fascinating things we have done to empower knowledge management and knowledge discovery this year. In 2019, Ontotext open-sourced the front-end and engine plugins of GraphDB to make the development and operation of knowledge graphs easier and richer.

Knowledge Discovery 52

Knowledge Discovery Publishing Technology Enterprise 52

Ontotext

AUGUST 19, 2020

There is a link between the concept extracted and the ontology, which means that concept and now the text too have context, which enables more accurate search and further analytics. The text analysis is also able to identify gaps in the knowledge graph such as concepts and relationships previously unidentified.

Metadata 59

Metadata Knowledge Discovery Cost-Benefit Data Governance 59

Ontotext

MARCH 8, 2023

Gartner predicts that graph technologies will be used in 80% of data and analytics innovations by 2025, up from 10% in 2021. Several factors are driving the adoption of knowledge graphs. Graph solutions have gained momentum due to their wide-ranging applications across multiple industries.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

Ontotext

DECEMBER 1, 2023

Krasimira touched upon the ways knowledge graphs can harness unstructured data and enhance it with semantic metadata. She also shared the architecture behind the vision of building useful semantic search, valuable insights platform, and powerful knowledge discovery environment.

Metadata 78

Metadata Sales Consulting Enterprise 78

FineReport

DECEMBER 19, 2019

Data analysis is a type of knowledge discovery that gains insights from data and drives business decisions. Professional data analysts must have a wealth of business knowledge in order to know from the data what has happened and what is about to happen. For super rookies, the first task is to understand what data analysis is.

Knowledge Discovery 98

Knowledge Discovery Visualization Experimentation Reporting 98

Ontotext

SEPTEMBER 15, 2020

Augment your data via reasoning, analytics and text analysis. By applying inference and graph analytics to uncover new information. It is also better interconnected, which brings more content and enables deeper analytics. Enrich your data extracting new entities and relationships from text. Maximize the usability of your data.

Metadata 69

Metadata Knowledge Discovery Data Quality Strategy 69

Domino Data Lab

DECEMBER 4, 2020

PharmaceUtical Modeling And Simulation (or PUMAS) is a suite of tools to perform quantitative analytics for pharmaceutical drug development [2]. The framework can facilitate a wide range of analytics task, including but not limited to: Non-compartmental Analysis. Specification of Nonlinear Mixed Effects (NLME) Models.

Metrics 59

Metrics Data Science Knowledge Discovery Measurement 59

TDAN

JUNE 15, 2022

“Information is the oil of the 21st century, and analytics is the combustion engine,” says Peter Sondergaard, former Global Head of Research at Gartner. And he has a point. Given that the global big data market is forecast to be valued at $103 billion in 2027, it’s worth noticing. As the amount of data generated […].

Data mining 98

Data mining Forecasting Big Data Marketing 98

Data Science 101

OCTOBER 31, 2019

Data mining is the process of discovering these patterns among the data and is therefore also known as Knowledge Discovery from Data (KDD). It is a supervised learning technique used in predictive analytics to find a continuous value based on one or numerous variables. Regression.

Data mining 77

Data mining KDD Data Science Forecasting 77

Ontotext

OCTOBER 28, 2021

This might be sufficient for information retrieval purposes and simple fact-checking, but if you want to get deeper insights, you need to have normalized data that allows analytics or machine interaction with it. Although there are already established reference datasets in some domains (e.g.

Visualization 52

Visualization Interactive Knowledge Discovery Modeling 52

datapine

NOVEMBER 19, 2019

In this day and age, we’re all constantly hearing the terms “big data”, “data scientist”, and “in-memory analytics” being thrown around. Almost all the major software companies are continuously making use of the leading Business Intelligence (BI) and Data Discovery tools available in the market to take their brand forward.

Business Intelligence 20

Business Intelligence Knowledge Discovery Unstructured Data Software 20

Ontotext

MAY 18, 2020

These are the so-called supercomputers, led by a smart legion of researchers and practitioners in the fields of data-driven knowledge discovery. ExaMode, an acronym for Extreme-scale Analytics via Multimodal Ontology Discovery & Enhancement, is a project funded by the European Union, H2020 programme. Certainly not!

Knowledge Discovery 72

Knowledge Discovery Experimentation Data-driven Metadata 72

FineReport

JULY 16, 2021

When we talk about business intelligence system, it normally includes the following components: data warehouse BI software Users with appropriate analytical. It is a process of using knowledge discovery tools to mine previously unknown and potentially useful knowledge. It is an active method of automatic discovery.

Business Intelligence 98

Business Intelligence Informatics Data Warehouse Data mining 98

Ontotext

AUGUST 10, 2023

The interoperability of knowledge graphs allows the easy integration and reuse of publicly available as well as proprietary data. The resulting high-quality standardized and interlinked data becomes the foundation for business analytics and insight generation.

Technology 52

Technology Knowledge Discovery Interactive Enterprise 52

Ontotext

APRIL 27, 2021

Ontotext has years of experience transforming data into knowledge across a number of industries and especially in the healthcare sector. By the addition of formal semantics to data, both machines and humans can process the data correctly and efficiently through better search and analytics and the automation of knowledge tasks.

Knowledge Discovery 59

Knowledge Discovery Unstructured Data Insurance Testing 59

Ontotext

FEBRUARY 19, 2020

Match entities across datasets with overlapping scope, handle their attributes to merge single and multiple data fields, and manually map their different taxonomies, all of which will greatly impact your analytics. Choose your data storage. An RDF triplestore (such as Ontotext’s GraphDB) will enable you to do incremental inference.

Modeling 90

Modeling Knowledge Discovery Data Quality Technology 90

Ontotext

FEBRUARY 21, 2024

This dramatically simplifies the interaction with complex databases and analytics systems. The post Enhancing Knowledge Discovery: Implementing Retrieval Augmented Generation with Ontotext Technologies appeared first on Ontotext. Or you can take things into your hands directly.

Knowledge Discovery 64

Knowledge Discovery Technology Metadata Data-driven 64

Ontotext

JULY 29, 2021

We rather see it as a new paradigm that is revolutionizing enterprise data integration and knowledge discovery. Providing a formal unified conceptual model, ontologies enable unified access to and correct interpretation of diverse information and greatly facilitate analytics, decision making and knowledge re-use.

Enterprise 124

Enterprise Metadata Knowledge Discovery Management 124

Domino Data Lab

JUNE 15, 2021

Similarly, Snowflake’s Data Cloud has been gaining momentum and is now one of the key players in cloud-based data storage and analytics (the data warehouse-as-a-service space). Both platforms are cloud agnostic so they can run in Azure, GCP, and AWS. Connecting to Snowflake from Domino. About Domino.

Modeling 69

Modeling Data Science Data-driven Data Warehouse 69