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. Hoewever, it can be a double-edged sword for enterprises.

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. Let’s walk through the architecture chronologically for a closer look at each step.

Data Lake 115

Data Lake Cost-Benefit Unstructured Data Modeling 115

Domino Data Lab

MAY 20, 2021

Figure 3 shows visual explanation of how SMOTE generates synthetic observations in this case. Insufficient training data in the minority class — In domains where data collection is expensive, a dataset containing 10,000 examples is typically considered to be fairly large. Merging the two results in a completely balanced dataset (50:50).

Machine Learning 136

Machine Learning Metrics Data mining Data Science 136

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). Domain Knowledge. The foremost step of this process is to possess relevant domain knowledge regarding the problem at hand. Deployment.

Data mining 77

Data mining KDD Data Science Forecasting 77

Ontotext

SEPTEMBER 15, 2020

Knowledge Graphs are the Warp and Weft of a Data Fabric. Knowledge graphs can be used to foster text analysis and make this easier, as in the Ontotext Platform. In other words, knowledge graphs solve the data silo problem by making it irrelevant. What Makes a Data Fabric? It is a buzzword.

Metadata 69

Metadata Knowledge Discovery Data Quality Strategy 69

Ontotext

OCTOBER 28, 2021

In our previous post, we covered the basics of how the Ontotext and metaphacts joint solution based on GraphDB and metaphactory helps customers accelerate their knowledge graph journey and generate value from it in a matter of days. You can also listen to our on-demand webinar on the same topic or check out our use case brief.

Visualization 52

Visualization Interactive Knowledge Discovery Dashboards 52

Domino Data Lab

DECEMBER 4, 2020

When analysing pharmacokinetic data to determine the degree of exposure of a drug and associated pharmacokinetic parameters (e.g., clearance, elimination half-life, maximum observed concentration ( ), time where the maximum concentration was observed ( ), Non-Compartmental Analysis (NCA) is usually the preferred approach [1]. Mean residence time.

Metrics 59

Metrics Data Science Knowledge Discovery Measurement 59

Ontotext

AUGUST 22, 2023

However, for this to happen, there needs to be context for the data to become knowledge. Beyond that, and without a way to visualize, connect, and utilize the data, it’s still just a bunch of random information. It also creates a knowledge base to power growth through well-defined context and coherent systems.

Metadata 52

Metadata Knowledge Discovery Big Data Enterprise 52

Ontotext

AUGUST 31, 2023

The growth of large language models drives a need for trusted information and capturing machine-interpretable knowledge, requiring businesses to recognize the difference between a semantic knowledge graph and one that isn’t—if they want to leverage emerging AI technologies and maintain a competitive edge. What is a knowledge graph?

Modeling 64

Modeling Knowledge Discovery Optimization Enterprise 64

Ontotext

MARCH 8, 2023

Specifically, the increasing amount of data being generated and collected, and the need to make sense of it, and its use in artificial intelligence and machine learning, which can benefit from the structured data and context provided by knowledge graphs. We get this question regularly. Linked Data, subscriptions, purchased datasets, etc.).

Enterprise 52

Enterprise Knowledge Discovery Risk Machine Learning 52

Domino Data Lab

AUGUST 1, 2021

This can be attributed to the popularity that machine learning algorithms, and more specifically deep learning, has been gaining in various domains. It is not possible to fully understand the inferential process of a deep neural network and to prove that it would generalise as expected. According to Fox et al.,

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

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. Knowledge graph development: The Graph CoE should lead the development of each of the knowledge graph components.

Knowledge Discovery 52

Knowledge Discovery Cost-Benefit Data-driven Metadata 52