DataKitchen

APRIL 28, 2021

Industry analysts who follow the data and analytics industry tell DataKitchen that they are receiving inquiries about “data fabrics” from enterprise clients on a near-daily basis. Gartner included data fabrics in their top ten trends for data and analytics in 2019. Process Constraints. What is a Data Fabric?

Statistics 246

Statistics Optimization Technology Data Analytics 246

Ontotext

JUNE 10, 2021

And yeah, the real-world relationships among the entities represented in the data had to be fudged a bit to fit in the counterintuitive model of tabular data, but, in trade, you get reliability and speed. Relational databases benefit from decades of tweaks and optimizations to deliver performance. Schemas are powerful.

Metadata 119

Metadata Cost-Benefit OLAP Modeling 119

Ontotext

JULY 13, 2023

However, many times they create more headaches than benefits. For example, offering more of the same product or content instead of complementary items Analytics tools that don’t really support decision making Chatbots that fail the Alan Turing test You name it! Do you identify with any of these experiences?

Enterprise 52

Enterprise Metadata Digital Transformation Software 52

Ontotext

APRIL 6, 2023

Knowledge graphs are changing the game A knowledge graph is a data model that uses semantics to represent real-world entities and the relationships between them. This model is used in various industries to enable seamless data integration, unification, analysis and sharing. standards modeled in a knowledge graph!

Manufacturing 83

Manufacturing Cost-Benefit Knowledge Discovery Optimization 83

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. Graphs boost knowledge discovery and efficient data-driven analytics to understand a company’s relationship with customers and personalize marketing, products, and services. We get this question regularly.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

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. They can perform a wide range of different tasks, such as natural language processing, classifying images, forecasting trends, analyzing sentiment, and answering questions.

Data Lake 88

Data Lake Unstructured Data Management Modeling 88

Ontotext

AUGUST 19, 2020

XML and later JSON were the languages that enabled data interchange by establishing a common data model by establishing a standard description of the data being shared. Separating the definitions of the metadata from the data had the benefit of simplifying validation and introducing flexibility. Semantics Makes It Powerful.

Metadata 59

Metadata Knowledge Discovery Cost-Benefit Data Governance 59

Ontotext

NOVEMBER 22, 2020

The ability to define the concepts and their relationships that are important to an organization in a way that is understandable to a computer has immense benefits. Traditionally, semantic technology required specialist expertise that most developers didn’t have. Developer-Friendly Semantic Technology.

Metadata 72

Metadata Cost-Benefit Unstructured Data Technology 72

Cloudera

JANUARY 19, 2024

As described in our recent blog post , an SQL AI Assistant has been integrated into Hue with the capability to leverage the power of large language models (LLMs) for a number of SQL tasks. Supported AI models and services The SQL AI Assistant is not bundled with a specific LLM; instead it supports various LLMs and hosting services.

Data Warehouse 72

Data Warehouse Data Processing Optimization Modeling 72

IBM Big Data Hub

FEBRUARY 23, 2024

Beyond the simplistic chat bubble of conversational AI lies a complex blend of technologies, with natural language processing (NLP) taking center stage. DL models can improve over time through further training and exposure to more data. DL, a subset of ML, excels at understanding context and generating human-like responses.

Enterprise 103

Enterprise Interactive Data-driven Key Performance Indicator 103

Ontotext

MARCH 18, 2020

Consequently, many data leaders today are striving to overcome these barriers by streamlining their enterprise knowledge management processes and practices. The knowledge graph model is one way of doing it and, not surprisingly, it has been in increasing demand in the last decade. Why Enterprise Knowledge Graphs?

Enterprise 59

Enterprise B2B Unstructured Data Machine Learning 59

Ontotext

JANUARY 21, 2021

It benefits from years of work by leading ontologists and technologists and the participation of a broad range of business subject matter experts. The use of semantic web technologies, natural language processing tools and knowledge graph architectures does not insure the meaningfulness of content expressed with those tools.

Modeling 72

Modeling Finance Technology Insurance 72

Ontotext

NOVEMBER 18, 2021

Picture this – you start with the perfect use case for your data analytics product. Nowadays, data analytics doesn’t exist on its own. And you have to be able to automate the processes and absorb continuous updates. The core analytics task. The rule implementing its semantics looks like this: a.

Visualization 98

Visualization Reporting Metadata Enterprise 98

O'Reilly on Data

MARCH 7, 2019

We’re in an exciting decade for natural language processing (NLP). It has different semantics. Lesson #1: Off-the-shelf NLP models don’t work. Azure Text Analytics. The next mistake I made, like many others, was building models that “solve health care.” spaCy Named Entity Visualizer. Amazon Comprehend (offline).

Deep Learning 227

Deep Learning Testing Machine Learning Modeling 227

IBM Big Data Hub

AUGUST 28, 2023

Manually processing data at that scale, however, can prove prohibitively costly and time-consuming. One of the best ways to take advantage of social media data is to implement text-mining programs that streamline the process. The data collection process should be tailored to the specific objectives of the analysis.

Data mining 56

Data mining Machine Learning Deep Learning Marketing 56

bridgei2i

DECEMBER 15, 2021

Naturally, the change in consumer behavior prompted media companies to change their business models. Even music streaming sites can benefit from using AI as it allows for personalized listener recommendations and also the right ad placement based on the target audience. Anticipating Demand through Predictive Modelling on OTT.

Recreation/Entertainment 52

Recreation/Entertainment Metadata Advertising Predictive Modeling 52

IBM Big Data Hub

DECEMBER 16, 2022

For example, imagine business analyst Alex is working on a data analytics project to help her retail company better quantify the success of shoe sales versus jewelry sales. Let’s look at five benefits of an enterprise data catalog and how they make Alex’s workflow more efficient and her data-driven analysis more informed and relevant.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

FineReport

APRIL 26, 2023

This has led to the emergence of the field of Big Data, which refers to the collection, processing, and analysis of vast amounts of data. The term “Big” does not only refer to its size, but also to its capacity to acquire, organize, and process information beyond the capabilities of traditional databases. What is Big Data?

Big Data 52

Big Data Data Analytics Analytics Cost-Benefit 52

Alation

FEBRUARY 20, 2020

Data catalogs have emerged as a core component of a modern technology stack and are a critical foundation for the transition from process-driven to data-driven decision making. According to Gartner, across all vendors, the key business benefits to metadata management now include: Facilitating collaboration around data.

Metadata 52

Metadata Management Data-driven Data Governance 52

Sisense

MARCH 4, 2019

That’s not feasible for the long term on a global scale, nor is it tenable in the near term for smaller organizations who may have limited resources to deal with their analytics challenges. Approximate Query Processing (AQP) removes the need to query the entire Big Data set and serves up usable results rapidly. The Training Process.

Big Data 68

Big Data Data Analytics Analytics IoT 68

Ontotext

DECEMBER 2, 2021

Then, there would be a mapping file that specifies the translation process. The great benefits of GraphQL are that it’s easy (compared to SPARQL, anyway), you only get what you request, it has a ready federation solution and there’s a lot of services implementing it. Data analytics can be a bit elitist. GraphQL federation.

Visualization 98

Visualization Interactive Dashboards Enterprise 98

Juice Analytics

MARCH 11, 2021

3) That’s where our data visualization and user experience capabilities helped them turn this data into a web-based analytical tool that focused users on the metrics and peer groups they cared about. Depth : Can you explore deeply the behaviors of individual people, companies, or processes?

Predictive Modeling 128

Predictive Modeling Visualization Reporting Interactive 128

Smart Data Collective

MARCH 30, 2021

Based on reliable statistics and data modeling tools , companies can refine their SEO strategies more clearly and modify them to achieve better results. Thanks to Google Analytics , you can get the following user data: age; gender; geographical location of site visitors; devices from which the site is opened; channels of acquisition, etc.

Data-driven 91

Data-driven Sales Big Data Marketing 91

Ontotext

FEBRUARY 26, 2024

This is part of Ontotext’s AI-in-Action initiative aimed at enabling data scientists and engineers to benefit from the AI capabilities of our products. Further, RED’s underlying model can be visually extended and customized to complex extraction and classification tasks. and “What is the financial impact?”.

Data-driven 59

Data-driven Risk Modeling Risk Management 59

Ontotext

MAY 22, 2023

What is the future of knowledge graphs in the era of ChatGPT and Large Language Models? To start with, Large Language Models (LLM) will not replace databases. They are good for compressing information, but one cannot retrieve from such a model the same information that it got trained on. That’s something that LLMs cannot do.

Management 59

Management Unstructured Data Metadata Cost-Benefit 59

Ontotext

DECEMBER 7, 2023

The descriptions of these entities have a specific structure and meaning (semantics). This allows both humans and machines to process them efficiently and unambiguously. Because of the formal semantics attached to the data, knowledge graphs can act as a knowledge base.

Metadata 64

Metadata Modeling Software Statistics 64

AWS Big Data

APRIL 17, 2024

Today, customers widely use OpenSearch Service for operational analytics because of its ability to ingest high volumes of data while also providing rich and interactive analytics. As your operational analytics data velocity and volume of data grows, bottlenecks may emerge. The new design doesn’t modify the way searches work.

Optimization 112

Optimization Snapshot Metadata Cost-Benefit 112

Ontotext

FEBRUARY 26, 2024

However, it still requires more effort than building a single-purpose graph, like a labeled property graph (LPG), where you can whiteboard your graph model in an hour. The goal is to capture data, convert it into the right insights, and integrate those insights quickly and efficiently into your business decisions and processes.

Technology 52

Technology Cost-Benefit Data-driven Metadata 52

Smarten

APRIL 19, 2024

In this article, we will discuss the current state of AI in analytics, as well as the future of this burgeoning industry and how it can be applied to analytics to simplify and clarify results and to make analytics easier for businesses and business users to leverage. GPT – Is based on a Large Language Model (LLM).

Analytics 57

Analytics Predictive Modeling KPI Machine Learning 57

AWS Big Data

APRIL 2, 2024

We also detail how the feature works and what criteria was applied for the model and prompt selection while building on Amazon Bedrock. This feature also elevates data discovery and interpretation by providing recommendations on analytical applications for a dataset giving customers additional confidence in their analysis.

Metadata 87

Metadata Metrics Data-driven Modeling 87

AWS Big Data

JUNE 21, 2023

OpenSearch is a scalable, flexible, and extensible open-source software suite for search, analytics, security monitoring, and observability applications, licensed under the Apache 2.0 An embedding model, for instance, could encode the semantics of a corpus.

Metrics 77

Metrics Measurement Modeling Dashboards 77

Alation

APRIL 14, 2022

Moving data to the cloud can bring immense operational benefits. Semantics, context, and how data is tracked and used mean even more as you stretch to reach post-migration goals. And, as organizations progress and grow, “data drift” starts to impact data usage, models, and your business. The future lies in the cloud.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

Ontotext

JANUARY 25, 2024

Providing unified information access, flexible data integration and automation of data management tasks, knowledge graphs have a huge impact on many systems and processes across various industries. The vast amounts of data enterprises have today need to be processed, understood and leveraged in real time.

Enterprise 64

Enterprise Management Cost-Benefit Metadata 64

Domino Data Lab

JANUARY 6, 2019

Also, clearly there’s no “one size fits all” educational model for data science. Laura Noren, who runs the Data Science Community Newsletter , presented her NYU postdoc research at JuptyerCon 2018, comparing infrastructure models for data science in research and education. The Berkeley model addresses large university needs in the US.

Data Science 56

Data Science Machine Learning Reporting Visualization 56

Sisense

MAY 26, 2020

In Talking Data , we delve into the rapidly evolving worlds of Natural Language Processing and Generation. The science of understanding and learning from text data is called natural language processing (NLP). It’s a huge challenge to process that data and get useful information out of it. Semantic meaning of words.

Unstructured Data 98

Unstructured Data Big Data Testing Machine Learning 98

Ontotext

DECEMBER 30, 2022

Ontotext started in 2000 as an R&D lab, led by now CEO Atanas Kiryakov, becoming one of the pioneers of the Semantic Web. 9 years of research, prototyping and experimentation went into developing enterprise ready Semantic Technology products. Ontotext develops re-usable domain models as pre-packaged knowledge graphs.

Enterprise 52

Enterprise Sales Cost-Benefit Marketing 52

Ontotext

DECEMBER 30, 2022

Ontotext started in 2000 as an R&D lab, led by now CEO Atanas Kiryakov, becoming one of the pioneers of the Semantic Web. 9 years of research, prototyping and experimentation went into developing enterprise ready Semantic Technology products. The first 18 years: Develop vision and products and deliver to innovation leaders.

Enterprise 52

Enterprise Sales Cost-Benefit Marketing 52