CIO Business Intelligence

JUNE 7, 2022

billion in cost savings for the insurance industry as well during the same period. . For banks, brokerages, insurance companies, fintech firms, and other financial services organizations, NLP is increasingly being seen as a solution to too much data and too few employees. The same study estimated that chatbots would lead to $1.3

Unstructured Data 98

Unstructured Data Deep Learning Insurance Interactive 98

O'Reilly on Data

SEPTEMBER 19, 2023

While data scientists were no longer handling Hadoop-sized workloads, they were trying to build predictive models on a different kind of “large” dataset: so-called “unstructured data.” “Here’s our risk model. A single document may represent thousands of features.

Machine Learning 247

Machine Learning Testing Modeling Cost-Benefit 247

Cloudera

SEPTEMBER 15, 2022

Structured data (such as name, date, ID, and so on) will be stored in regular SQL databases like Hive or Impala databases. There are also newer AI/ML applications that need data storage, optimized for unstructured data using developer friendly paradigms like Python Boto API. Diversity of workloads.

Metadata 89

Metadata Big Data Optimization Unstructured Data 89

Ontotext

SEPTEMBER 2, 2020

The risk is that the organization creates a valuable asset with years of expertise and experience that is directly relevant to the organization and that valuable asset can one day cross the street to your competitors. These organizations reached the limit of optimization relying on keywords long before anyone else.

Insurance 72

Insurance Metadata Publishing Unstructured Data 72

Cloudera

NOVEMBER 25, 2020

Sample and treatment history data is mostly structured, using analytics engines that use well-known, standard SQL. Interview notes, patient information, and treatment history is a mixed set of semi-structured and unstructured data, often only accessed using proprietary, or less known, techniques and languages.

Data Warehouse 58

Data Warehouse Unstructured Data Analytics Visualization 58

bridgei2i

APRIL 9, 2019

Most enterprises and heavyweight financial companies are acquiring start-ups with the motive to analyze the massive amounts of unstructured data automatically. AI automates various financial processes of wealth management to offer tax-optimized and personalized investment experiences to their clients.

Unstructured Data 69

Unstructured Data Sales Data-driven Finance 69

bridgei2i

MAY 21, 2019

Most enterprises and heavyweight financial companies are acquiring start-ups with the motive to analyze the massive amounts of unstructured data automatically. AI automates various financial processes of wealth management to offer tax-optimized and personalized investment experiences to their clients.

Unstructured Data 40

Unstructured Data Sales Data-driven Finance 40

AWS Big Data

FEBRUARY 21, 2023

Loading complex multi-point datasets into a dimensional model, identifying issues, and validating data integrity of the aggregated and merged data points are the biggest challenges that clinical quality management systems face. Additionally, scalability of the dimensional model is complex and poses a high risk of data integrity issues.

Data Warehouse 63

Data Warehouse Data Lake Cost-Benefit Modeling 63

Sisense

MAY 4, 2020

In his article in Forbes , he discussed how some of the biggest names in global business — Nike, Burger King, and McDonald’s — and progressive newer entrants to huge sectors like insurance, are embracing data and analytics technology as a platform on which to build their competitive advantages. Organizations must adapt or die.

Big Data 78

Big Data Data-driven Snapshot Unstructured Data 78

CIO Business Intelligence

AUGUST 1, 2023

As many CIOs prepare their 2024 budgets and digital transformation priorities, developing a strategy that seeks opportunities to evolve business models, targets near-term operational impacts, prioritizes where employees should experiment, and defines AI-related risk-mitigating plans is imperative.

Digital Transformation 98

Digital Transformation Unstructured Data Strategy Experimentation 98

Alation

FEBRUARY 10, 2022

Data classification is necessary for leveraging data effectively and efficiently. Effective data classification helps mitigate risk, maintain governance and compliance, improve efficiencies, and help businesses understand and better use data. Mitigate Security Risk. Then, it labels them accordingly.

Data Governance 52

Data Governance Risk Insurance Strategy 52