Ontotext

JULY 24, 2023

I did some research because I wanted to create a basic framework on the intersection between large language models (LLM) and data management. Examples of these types of applications are content summarization, programming tasks, data extraction, and conversational assistants (chatbots). Most applications are still exploratory.

Modeling 98

Modeling Management Structured Data Data Architecture 98

AWS Big Data

NOVEMBER 15, 2023

It seamlessly consolidates data from various data sources within AWS, including AWS Cost Explorer (and forecasting with Cost Explorer ), AWS Trusted Advisor , and AWS Compute Optimizer. Overview of the BMW Cloud Data Hub At the BMW Group, Cloud Data Hub (CDH) is the central platform for managing company-wide data and data solutions.

Dashboards 95

Dashboards Analytics Metadata Data Warehouse 95

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.

Modeling 64

Modeling Optimization Knowledge Discovery Enterprise 64

Jet Global

MARCH 14, 2024

The solution offers data movement, data science, real-time analytics, and business intelligence within a single platform. It is a complete tool for data preparation, automation, and modeling, which simplifies data management and speeds up time-to-value.

Analytics 52

Analytics Management Reporting Enterprise 52

Ontotext

MAY 30, 2019

Let’s imagine Johnny Mnemonic – Keanu Reeves’ character from the cyberpunk action thriller movie of the same name – who is carrying a data package inside his head. He has been tasked with smuggling data – not in the 90s as the movie had it, but these days. A Headful of Linked Data. Security (encryption).

Cost-Benefit 87

Cost-Benefit Technology Big Data Metadata 87

Cloudera

FEBRUARY 22, 2022

Over the past decade, the successful deployment of large scale data platforms at our customers has acted as a big data flywheel driving demand to bring in even more data, apply more sophisticated analytics, and on-board many new data practitioners from business analysts to data scientists.

Snapshot 110

Snapshot Metadata Cost-Benefit Data Architecture 110

Ontotext

SEPTEMBER 1, 2023

LLMs in particular have remarkable capabilities to comprehend and generate human-like text by learning intricate patterns from vast volumes of training data; however, under the hood, they are just statistical approximations. An LLM, on the other hand, is a neural network model built by processing text data.

Risk 52

Risk Modeling Data Quality Data Governance 52

Ontotext

MAY 30, 2019

In this article, we are bringing science fiction to the semantic technology (and data management) talk to shed some light on three common data challenges: the storage, retrieval and security of information. We will talk through these from the perspective of Linked Data (and cyberpunk). A Headful of Linked Data.

Cost-Benefit 75

Cost-Benefit Technology Big Data Metadata 75

erwin

JUNE 8, 2020

Our customers are in search of creative and sustainable ways to increase their speed to insights for digital transformation, infrastructure modernization and cloud migration and many of them are looking to implement the Snowflake Cloud Data Platform. Well, we think so. Let me know your thoughts on the new erwin/Snowflake partnership.

Management 52

Management Metadata Data Lake Digital Transformation 52

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. Use Case #1: Customer 360 / Enterprise 360 Customer data is typically spread across multiple applications, departments, and regions. Several factors are driving the adoption of knowledge graphs. million users.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

Smarten

APRIL 19, 2024

Benefits include customized and optimized models, data, parameters and tuning. This is a commercial, service-based GPT Chat Bot solution, designed to automate routine tasks and enhance communications to improve customer support and create marketing campaigns. It must be integrated with business systems to leverage available data.

Analytics 57

Analytics Predictive Modeling KPI Machine Learning 57

Ontotext

JANUARY 21, 2021

The Financial Industry Business Ontology (FIBO) is a standard that is being developed and published by the Enterprise Data Management Council that attempts to capture business domain knowledge using sophisticated knowledge representation techniques and linked open data technologies. In this way, FIBO can give meaning to any data (e.g.,

Modeling 72

Modeling Finance Technology Insurance 72

Octopai

DECEMBER 22, 2019

What a flashback to see all that we’ve achieved this year in data governance, risk and compliance, data analysis and reporting. The market demands easy and speedy management of data amid an increasingly complex data landscape. Data lineage can be achieved better, easier, and faster with automated tools.

Metadata 54

Metadata Management OLAP Data Governance 54

Cloudera

APRIL 15, 2021

According to IDG, when customers consider updating to the latest release of a product, they expect new features, enhanced security, and better performance, but increasingly want a more streamlined upgrade process. release and the new in-place upgrade from HDP that completely does away with replacing infrastructure and data migrations.

Cost-Benefit 70

Cost-Benefit Data Warehouse Management Data Processing 70

Cloudera

NOVEMBER 10, 2021

Cloudera Data Platform (CDP) brings many improvements to customers by merging technologies from the two legacy platforms, Cloudera Enterprise Data Hub (CDH) and Hortonworks Data Platform (HDP). It is useful in defining and enforcing different levels of privileges on data for users on a Hadoop cluster.

Data Lake 78

Data Lake Management Metadata Modeling 78

AWS Big Data

JUNE 15, 2023

In this post, we explain how you can enable business users to ask and answer questions about data using their everyday business language by using the Amazon QuickSight natural language query function, Amazon QuickSight Q. Q uses the same QuickSight datasets you use for your dashboards and reports so your data is governed and secured.

Sales 68

Sales Dashboards Visualization Testing 68

Birst BI

FEBRUARY 13, 2018

The Constellation ShortList recognizes leading Cloud BI solutions that help companies gain deep, contextual insights from combinations of internal and external data. Birst’s Networked approach to BI and analytics enables a single view of data, eliminating data silos. Mobile reporting, visualization, analysis.

Business Intelligence 66

Business Intelligence Diagnostic Analytics Analytics Visualization 66

FineReport

APRIL 26, 2023

As the world becomes increasingly digitized, the amount of data being generated on a daily basis is growing at an unprecedented rate. 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. What is Big Data? What is Big Data?

Big Data 52

Big Data Data Analytics Analytics Cost-Benefit 52

BI-Survey

FEBRUARY 7, 2022

The effective use of data and analytics is a challenge for most companies today. Analytics content must be created in an iterative manner and it must not be impeded by the restrictions caused by data silos. Creating all reports in a single tool and storing all data in a common data warehouse was meant to boost efficiency.

Analytics 52

Analytics Metadata Cost-Benefit Software 52

Andrew White

JANUARY 9, 2022

On Thursday January 6th I hosted Gartner’s 2022 Leadership Vision for Data and Analytics webinar. – In the webinar and Leadership Vision deck for Data and Analytics we called out AI engineering as a big trend. I would take a look at our Top Trends for Data and Analytics 2021 for additional AI, ML and related trends.

Analytics 64

Analytics Measurement Modeling Data-driven 64

Jet Global

FEBRUARY 23, 2024

The quick and dirty definition of data mapping is the process of connecting different types of data from various data sources. Data mapping is a crucial step in data modeling and can help organizations achieve their business goals by enabling data integration, migration, transformation, and quality.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

AWS Big Data

MARCH 20, 2023

We discuss how to create such a solution using Amazon Kinesis Data Streams , Amazon Managed Streaming for Kafka (Amazon MSK), Amazon Kinesis Data Analytics for Apache Flink ; the design decisions that went into the architecture; and the observed business benefits by Poshmark.

Analytics 52

Analytics Slice and Dice Data Processing Data Lake 52

Alation

APRIL 14, 2022

Moving data to the cloud can bring immense operational benefits. However, the sheer volume and complexity of today’s enterprise data can cause downstream headaches for data users. Semantics, context, and how data is tracked and used mean even more as you stretch to reach post-migration goals. Parametrization.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

AWS Big Data

JUNE 9, 2023

A modern data architecture enables companies to ingest virtually any type of data through automated pipelines into a data lake, which provides highly durable and cost-effective object storage at petabyte or exabyte scale. Apache Iceberg 1.2.0, and Delta Lake 2.3.0.

Data Lake 113

Data Lake Metadata Optimization Statistics 113

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. s legendary culture of innovation.

Insurance 75

Insurance Contextual Data Testing Unstructured Data 75

IBM Big Data Hub

JANUARY 17, 2023

A data lakehouse is an emerging data management architecture that improves efficiency and converges data warehouse and data lake capabilities driven by a need to improve efficiency and obtain critical insights faster. Let’s start with why data lakehouses are becoming increasingly important.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

erwin

MAY 27, 2020

Data modeling supports collaboration among business stakeholders – with different job roles and skills – to coordinate with business objectives. Data resides everywhere in a business , on-premise and in private or public clouds. A single source of data truth helps companies begin to leverage data as a strategic asset.

Modeling 98

Modeling Metadata Data Governance Visualization 98

AWS Big Data

OCTOBER 25, 2023

Unstructured data is information that doesn’t conform to a predefined schema or isn’t organized according to a preset data model. Text, images, audio, and videos are common examples of unstructured data. After decades of digitizing everything in your enterprise, you may have an enormous amount of data, but with dormant value.

Unstructured Data 119

Unstructured Data Metadata Management Analytics 119

Birst BI

MAY 14, 2019

Cloud, digital transformation, mergers and acquisitions, big data analytics, data monetization, and more are all critical business initiatives creating an even greater divide between centralized IT and decentralized analytic teams in the business.

Analytics 9

Analytics Key Performance Indicator Business Intelligence Visualization 9

IBM Big Data Hub

SEPTEMBER 11, 2023

On June 7, 1983, a product was born that would revolutionize how organizations would store, manage, process , and query their data: IBM Db2. Codd published his famous paper “ A Relational Model of Data for Large Shared Data Banks.” Over the past 40 years, Db2 has been on an exciting and transformational journey.

Machine Learning 85

Machine Learning Cost-Benefit IoT Data Warehouse 85

Alation

MARCH 17, 2021

Key Features of a Machine Learning Data Catalog. Data intelligence is crucial for the development of data catalogs. At the center of this innovation are machine learning data catalogs (MLDCs). Unlike standalone tools, machine learning data catalogs have features like: Data search. Data stewardship.

Machine Learning 52

Machine Learning Metadata Data Governance Interactive 52