FineReport

JULY 16, 2021

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. Data Visualization. Data visualization can reflect business operations intuitively.

Business Intelligence 98

Business Intelligence Informatics Data Warehouse Data mining 98

AWS Big Data

SEPTEMBER 26, 2024

These summaries, encapsulating key insights, are stored alongside the original content in the curated zone, enriching the organization’s data assets for further analysis, visualization, and informed decision-making.

Data Lake 115

Data Lake Cost-Benefit Unstructured Data Modeling 115

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). The patterns discovered after this step are interpreted using various visualization and reporting techniques and are made comprehensible for other team members to understand. Deployment.

Data mining 77

Data mining KDD Data Science Forecasting 77

Domino Data Lab

MAY 20, 2021

Figure 3 shows visual explanation of how SMOTE generates synthetic observations in this case. Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining, 73–79. 30(2–3), 195–215. link] Ling, C. X., & Li, C. Data mining for direct marketing: Problems and solutions. Quinlan, J. Everhart, J.

Machine Learning 136

Machine Learning Metrics Data mining Knowledge Discovery 136

Ontotext

SEPTEMBER 15, 2020

Start delivering the answers to your original questions through different knowledge discovery tools such as powerful SPARQL queries, easy to use GraphQL interface, semantic search, faceted search, data visualization, etc. Maximize the usability of your data. Make it easy to maintain and evolve your data fabric.

Metadata 69

Metadata Knowledge Discovery Data Quality Strategy 69

Domino Data Lab

DECEMBER 4, 2020

We can now visually inspect the change in plasma concentration over time in the 5, 20, and 80mg profiles: Next, we call the Pumas read_nca function, which creates an NCAPopulation object containing preprocessed data for generation of all NCA values. pain_df.TIME.== 0, pain_df.DOSE, missing).

Metrics 59

Metrics Data Science Knowledge Discovery Measurement 59

Ontotext

AUGUST 22, 2023

Beyond that, and without a way to visualize, connect, and utilize the data, it’s still just a bunch of random information. 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

MARCH 8, 2023

Graphs boost knowledge discovery and efficient data-driven analytics to understand a company’s relationship with customers and personalize marketing, products, and services. Yet, the biggest challenge for risk analysis continues to suffer from lack of a scalable way of understanding how data is interrelated.

Enterprise 52

Enterprise Knowledge Discovery Risk Machine Learning 52

Domino Data Lab

AUGUST 1, 2021

Skater provides a wide range of algorithms that can be used for visual interpretation (e.g. Partial Dependence Plot is another visual method, which is model agnostic and can be successfully used to gain insights into the inner workings of a black-box model like a deep ANN. Conference on Knowledge Discovery and Data Mining, pp.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

Ontotext

OCTOBER 28, 2021

This post looks at a specific clinical trial scoping example, powered by a knowledge graph that we have built for the EU funded project FROCKG , where both Ontotext and metaphacts are partners. Visual Ontology Modeling With metaphactory. Let’s first have a look at the knowledge graph management capabilities provided by metaphactory.

Visualization 52

Visualization Interactive Knowledge Discovery Dashboards 52

Ontotext

AUGUST 31, 2023

While a knowledge graph can exist without an ontology, an ontology is often represented in a knowledge graph because of the natural human desire to organize data—visually or in structure.

Modeling 64

Modeling Knowledge Discovery Optimization Enterprise 64

Ontotext

AUGUST 21, 2024

As a result, contextualized information and graph technologies are gaining in popularity among analysts and businesses due to their ability to positively affect knowledge discovery and decision-making processes. The goal should be to create value without really caring what is being used at the backend.

Knowledge Discovery 52

Knowledge Discovery Cost-Benefit Data-driven Metadata 52