article thumbnail

Reflections on the Knowledge Graph Conference 2023

Ontotext

The conference positioning focused on knowledge graphs as a mature, enterprise-ready technology for long-term and mission-critical use cases that require security, resilience and scalability. This message resonates with the market positioning of Ontotext as a trusted, stable option for demanding data-centric use cases.

article thumbnail

How Will The Cloud Impact Data Warehousing Technologies?

Smart Data Collective

sThe recent years have seen a tremendous surge in data generation levels , characterized by the dramatic digital transformation occurring in myriad enterprises across the industrial landscape. The amount of data being generated globally is increasing at rapid rates. Big data and data warehousing.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

5 ways to deploy your own large language model

CIO Business Intelligence

The most popular LLMs in the enterprise today are ChatGPT and other OpenAI GPT models, Anthropic’s Claude, Meta’s Llama 2, and Falcon, an open-source model from the Technology Innovation Institute in Abu Dhabi best known for its support for languages other than English. Things are changing week by week. We have every model working,” he adds.

Modeling 139
article thumbnail

Big Data Ingestion: Parameters, Challenges, and Best Practices

datapine

Operations data: Data generated from a set of operations such as orders, online transactions, competitor analytics, sales data, point of sales data, pricing data, etc. The gigantic evolution of structured, unstructured, and semi-structured data is referred to as Big data. Self-Service.

Big Data 100
article thumbnail

5 Pain Points of Moving Data to the Cloud and Strategies for Success

Alation

We have seen the COVID-19 pandemic accelerate the timetable of cloud data migration , as companies evolve from the traditional data warehouse to a data cloud, which can host a cloud computing environment. Accompanying this acceleration is the increasing complexity of data. Complex data management is on the rise.

article thumbnail

How to Take Back 40-60% of Your IT Spend by Fixing Your Data

Ontotext

While relational databases are the best fit for managing structured data workloads, they are not good for ad hoc inquiry and scenario-based analysis. Data has become isolated and mismatched across repositories and silos due to technology fragmentation and the rigidity of the relational paradigm.

IT 69
article thumbnail

From Data Silos to Data Fabric with Knowledge Graphs

Ontotext

Connecting the data in a graph allows concepts and entities to complement each other’s description. Given a critical mass of domain knowledge and good level of connectivity, KG can serve as context that helps computers comprehend and manipulate data. Ontotext’s Platform for Enterprise Knowledge Graphs.