CIO Business Intelligence

JUNE 7, 2022

But only in recent years, with the growth of the web, cloud computing, hyperscale data centers, machine learning, neural networks, deep learning, and powerful servers with blazing fast processors, has it been possible for NLP algorithms to thrive in business environments. Intel® Technologies Move Analytics Forward.

Unstructured Data 98

Unstructured Data Deep Learning Insurance Interactive 98

Smart Data Collective

SEPTEMBER 23, 2020

Type of Data: structured and unstructured from different sources of data Purpose: Cost-efficient big data storage Users: Engineers and scientists Tasks: storing data as well as big data analytics, such as real-time analytics and deep learning Sizes: Store data which might be utilized.

Data Lake 106

Data Lake Data Warehouse Unstructured Data Big Data 106

Smart Data Collective

DECEMBER 21, 2020

We previously talked about the benefits of data analytics in the insurance industry. One report found that big data vendors will generate over $2.4 Key benefits of AI include recognizing speech, identifying objects in an image, and analyzing natural or unstructured data forms. billion from the insurance industry.

Insurance 134

Insurance Cost-Benefit Big Data Unstructured Data 134

IBM Big Data Hub

JULY 6, 2023

It uses advanced tools to look at raw data, gather a data set, process it, and develop insights to create meaning. Areas making up the data science field include mining, statistics, data analytics, data modeling, machine learning modeling and programming.

Machine Learning 62

Machine Learning Data Science Statistics Deep Learning 62

IBM Big Data Hub

FEBRUARY 14, 2024

Energy Companies in the energy sector can increase their cost competitiveness by harnessing AI and data analytics for demand forecasting, energy conservation, optimization of renewables and smart grid management. AI platforms can use machine learning and deep learning to spot suspicious or anomalous transactions.

Cost-Benefit 91

Cost-Benefit Insurance Unstructured Data Machine Learning 91

CIO Business Intelligence

MARCH 9, 2022

Applying artificial intelligence (AI) to data analytics for deeper, better insights and automation is a growing enterprise IT priority. But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Data Quality 119

DataKitchen

APRIL 13, 2021

DataOps needs a directed graph-based workflow that contains all the data access, integration, model and visualization steps in the data analytic production process. It orchestrates complex pipelines, toolchains, and tests across teams, locations, and data centers. Amaterasu — is a deployment tool for data pipelines.

Testing 307

Testing Machine Learning Consulting Data Quality 307