AWS Big Data

FEBRUARY 29, 2024

However, enterprise data generated from siloed sources combined with the lack of a data integration strategy creates challenges for provisioning the data for generative AI applications. Data governance is a critical building block across all these approaches, and we see two emerging areas of focus.

Data Governance 109

Data Governance Unstructured Data Metadata Data Lake 109

Cloudera

FEBRUARY 15, 2024

While there are clear reasons SVB collapsed, which can be reviewed here , my purpose in this post isn’t to rehash the past but to present some of the regulatory and compliance challenges financial (and to some degree insurance) institutions face and how data plays a role in mitigating and managing risk.

Insurance 88

Insurance Data Architecture Risk Management Risk 88

DataKitchen

FEBRUARY 27, 2024

Challenges in Developing Reliable LLMs Organizations venturing into LLM development encounter several hurdles: Data Location: Critical data often resides in spreadsheets, characterized by a blend of text, logic, and mathematics.

Data Quality 117

Data Quality Unstructured Data Testing Data-driven 117

datapine

FEBRUARY 22, 2022

Improved risk management: Another great benefit from implementing a strategy for BI is risk management. IT should be involved to ensure governance, knowledge transfer, data integrity, and the actual implementation. However, it is possible to identify some potential drawbacks and apply risk management practices in advance.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Dashboards 218

Cloudera

SEPTEMBER 12, 2022

Organizations don’t know what they have anymore and so can’t fully capitalize on it — the majority of data generated goes unused in decision making. And second, for the data that is used, 80% is semi- or unstructured. Both obstacles can be overcome using modern data architectures, specifically data fabric and data lakehouse.

Unstructured Data 75

Unstructured Data Data Architecture Data Lake Snapshot 75

AWS Big Data

JULY 29, 2024

In the era of big data, data lakes have emerged as a cornerstone for storing vast amounts of raw data in its native format. They support structured, semi-structured, and unstructured data, offering a flexible and scalable environment for data ingestion from multiple sources.

Metadata 118

Metadata Snapshot Data Lake Metrics 118

CIO Business Intelligence

MAY 9, 2024

In today’s data-driven world, the ability to seamlessly integrate structured and unstructured data in a hybrid cloud environment is critical for organizations seeking to harness the full potential of their data assets.

Digital Transformation 52

Digital Transformation Data Integration Unstructured Data Data-driven 52

Cloudera

JUNE 22, 2023

It ensures compliance with regulatory requirements while shifting non-sensitive data and workloads to the cloud. Its built-in intelligence automates common data management and data integration tasks, improves the overall effectiveness of data governance, and permits a holistic view of data across the cloud and on-premises environments.

Cost-Benefit 66

Cost-Benefit Digital Transformation Data Governance Unstructured Data 66

CIO Business Intelligence

JULY 6, 2023

For example, IDP uses native AI to quickly and accurately extract data from business documents of all types, for both structured and unstructured data,” Reis says. Another benefit is greater risk management.

Cost-Benefit 119

Cost-Benefit Technology Unstructured Data Testing 119

CIO Business Intelligence

SEPTEMBER 2, 2022

Skills for financial data engineers include coding skills, data analytics, data visualization, data optimization, data integration, data modeling, cloud computing services, knowledge of relational and nonrelational database systems, and an ability to work with high volumes of structured and unstructured data.

Finance 98

Finance IT Software Reporting 98

CIO Business Intelligence

AUGUST 31, 2022

Skills for financial data engineers include coding skills, data analytics, data visualization, data optimization, data integration, data modeling, cloud computing services, knowledge of relational and nonrelational database systems, and an ability to work with high volumes of structured and unstructured data.

Finance 98

Finance IT Software Reporting 98

IBM Big Data Hub

OCTOBER 30, 2023

IBM, a pioneer in data analytics and AI, offers watsonx.data, among other technologies, that makes possible to seamlessly access and ingest massive sets of structured and unstructured data. AWS’s secure and scalable environment ensures data integrity while providing the computational power needed for advanced analytics.

Insurance 77

Insurance Data Warehouse Data-driven Unstructured Data 77

IBM Big Data Hub

NOVEMBER 10, 2023

These capabilities are needed to establish patient attribution, identify individual patients with gaps in care, and update the patient care plan with the necessary actions to address the patient risks and care gaps.

Cost-Benefit 95

Cost-Benefit Insurance Unstructured Data Consulting 95

Ontotext

FEBRUARY 26, 2024

The answers to these foundational questions help you uncover opportunities and detect risks. We bundle these events under the collective term “Risk and Opportunity Events” This post is part of Ontotext’s AI-in-Action initiative aimed to empower data, scientists, architects and engineers to leverage LLMs and other AI models.

Data-driven 59

Data-driven Risk Modeling Risk Management 59

Cloudera

SEPTEMBER 6, 2018

Handle increases in data volume gracefully. Represent entity relationships, to help determine ultimate beneficial owner, contribute to risk scoring, and facilitate investigations. Provide audit and data lineage information to facilitate regulatory reviews. Entity Resolution and Data Enrichment. Entity Risk Scoring.

Machine Learning 40

Machine Learning Big Data Risk Data Science 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. And for data models that can be directly reported, a dimensional model can be developed.

Data Warehouse 70

Data Warehouse Data Lake Cost-Benefit Metadata 70

CIO Business Intelligence

NOVEMBER 18, 2022

This type of flexible, cloud-based data management allows 3M HIS to aggregate different data sets for different purposes, ensuring both data integrity and faster processing. This is a dynamic view on data that evolves over time,” said Koll. Security by design is one of the underlying operating principles for AWS.

Insurance 75

Insurance Contextual Data Testing Unstructured Data 75

Cloudera

MAY 16, 2018

This approach also relates to monitoring internal fiduciary risk by tying separate events together, such as a large position (relative to historic norms) being taken immediately after the risk model that would have flagged it was modified in a separate system. Market data: Coordinated trading among multiple parties.

Data Lake 42

Data Lake Risk Visualization Unstructured Data 42

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. For efficient drug discovery, linked data is key.

Insurance 72

Insurance Metadata Publishing Unstructured Data 72

IBM Big Data Hub

AUGUST 4, 2023

Data within a data fabric is defined using metadata and may be stored in a data lake, a low-cost storage environment that houses large stores of structured, semi-structured and unstructured data for business analytics, machine learning and other broad applications.

Data Architecture 59

Data Architecture Data Lake Machine Learning Data Governance 59

Ontotext

NOVEMBER 2, 2023

Achieving this advantage is dependent on their ability to capture, connect, integrate, and convert data into insight for business decisions and processes. This is the goal of a “data-driven” organization. We call this the “ Bad Data Tax ”.

IT 69

IT Cost-Benefit Data-driven Technology 69

AWS Big Data

JULY 20, 2023

Orca Security is an industry-leading Cloud Security Platform that identifies, prioritizes, and remediates security risks and compliance issues across your AWS Cloud estate. To overcome these issues, Orca decided to build a data lake.

Data Lake 93

Data Lake Analytics Snapshot Data Quality 93

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.

Data Governance 52

Data Governance Risk Insurance Business Objectives 52

IBM Big Data Hub

DECEMBER 16, 2022

It also serves as a governance tool to drive compliance with data privacy and industry regulations. In other words, a data catalog makes the use of data for insights generation far more efficient across the organization, while helping mitigate risks of regulatory violations.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

FineReport

APRIL 26, 2023

Apache Hadoop Apache Hadoop is a Java-based open-source platform used for storing and processing big data. It is based on a cluster system, allowing it to efficiently process data and run it parallelly. It can process structured and unstructured data from one server to multiple computers and offers cross-platform support to users.

Big Data 52

Big Data Data Analytics Analytics Cost-Benefit 52

CIO Business Intelligence

APRIL 9, 2025

In Prioritizing AI investments: Balancing short-term gains with long-term vision , I addressed the foundational role of data trust in crafting a viable AI investment strategy. Absent governance and trust, the risks are higher as organizations adopt increasingly sophisticated analytics.

Enterprise 102

Enterprise Analytics Experimentation Statistics 102

Jet Global

MAY 9, 2024

Batch processing pipelines are designed to decrease workloads by handling large volumes of data efficiently and can be useful for tasks such as data transformation, data aggregation, data integration , and data loading into a destination system. structured, semi-structured, or unstructured data).

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

CIO Business Intelligence

JANUARY 30, 2025

As organizations handle terabytes of sensitive data daily, dynamic masking capabilities are expected to set the gold standard for secure data operations. Real-time data integration at scale Real-time data integration is crucial for businesses like e-commerce and finance, where speed is critical.

Management 113

Management Data-driven Data Governance Unstructured Data 113

CIO Business Intelligence

FEBRUARY 12, 2025

At the time, Grahams didnt have a plan for enterprise data, a challenge many organizations face. While businesses often tout their data-driven capabilities, the reality is that effective enterprise data integration is costly and time-consuming and results in a lot of manual effort.

Unstructured Data 98

Unstructured Data Data-driven Enterprise Reporting 98

BI-Survey

FEBRUARY 13, 2025

Instead, the Databricks object store provides an industry-standard and more cost-efficient solution for storing data. Customers using analytics outside of SAP systems faced the challenge of extracting SAP data and transferring it to their target environments.

Cost-Benefit 52

Cost-Benefit Unstructured Data Strategy Data-driven 52

CIO Business Intelligence

NOVEMBER 12, 2024

Complicating the issue is the fact that a majority of data (80% to 90%, according to multiple analyst estimates) is unstructured. 3 Modern DBAs must now navigate a landscape where data resides across increasingly diverse environments, including relational databases, NoSQL, and data lakes.

Statistics 52

Statistics Unstructured Data Cost-Benefit Data Lake 52

CIO Business Intelligence

FEBRUARY 18, 2025

My journey started by looking at the AI opportunity landscape in terms of business and technology maturity models, patterns, risk, reward and the path to business value. Focus on enabling enterprise data platforms that prioritize data quality first to establish trustworthy data products.

Machine Learning 90

Machine Learning Data Quality Enterprise Sales 90