Alation

SEPTEMBER 7, 2021

In this blog we will discuss how Alation helps minimize risk with active data governance. Now that you have empowered data scientists and analysts to access the Snowflake Data Cloud and speed their modeling and analysis, you need to bolster the effectiveness of your governance models. Find Trusted Data.

Data Governance 59

Data Governance Risk Data Quality Dashboards 59

CIO Business Intelligence

APRIL 29, 2022

Preparing for an artificial intelligence (AI)-fueled future, one where we can enjoy the clear benefits the technology brings while also the mitigating risks, requires more than one article. This first article emphasizes data as the ‘foundation-stone’ of AI-based initiatives. Establishing a Data Foundation. era is upon us.

Data Governance 145

Data Governance IT Risk Data Lake 145

erwin

APRIL 11, 2019

Some industries, such as healthcare and financial services, have been subject to stringent data regulations for years: GDPR now joins the Health Insurance Portability and Accountability Act (HIPAA), the Payment Card Industry Data Security Standard (PCI DSS) and the Basel Committee on Banking Supervision (BCBS).

Insurance 100

Insurance Data-driven Data Governance Metadata 100

IBM Big Data Hub

OCTOBER 12, 2023

Among the tasks necessary for internal and external compliance is the ability to report on the metadata of an AI model. Metadata includes details specific to an AI model such as: The AI model’s creation (when it was created, who created it, etc.)

Cost-Benefit 79

Cost-Benefit Metadata Data Governance Modeling 79

Cloudera

JULY 20, 2021

Risk models for financial institutions and insurers are exponentially more complicated . So relying upon the past for future insights with data that is outdated due to changing customer preferences, the hyper-competitive world and emphasis on environment, society and governance produces non-relevant insights and sub-optimized returns.

Manufacturing 104

Manufacturing Forecasting IoT Insurance 104

Alation

AUGUST 26, 2021

What Is Data Intelligence? Data intelligence is a system to deliver trustworthy, reliable data. It includes intelligence about data, or metadata. IDC coined the term, stating, “data intelligence helps organizations answer six fundamental questions about data.” Yet finding data is just the beginning.

Metadata 64

Metadata Data Governance Dashboards Software 64

Cloudera

AUGUST 31, 2021

Running on CDW is fully integrated with streaming, data engineering, and machine learning analytics. It has a consistent framework that secures and provides governance for all data and metadata on private clouds, multiple public clouds, or hybrid clouds. Consideration of both data & metadata in the migration.

Data Warehouse 82

Data Warehouse Cost-Benefit Metadata Data-driven 82

AWS Big Data

AUGUST 14, 2023

At the same time, unstructured approaches to data mesh management that don’t have a vision for what types of products should exist and how to ensure they are developed are at high risk of creating the same effect through simple neglect. When do new data products get created, and who is allowed to create them?

Management 81

Management Risk Measurement Optimization 81

Timo Elliott

JANUARY 5, 2022

The first one is: companies should invest more in improving their data quality before doing anything else. You must master your metadata and make sure that everything is lined up. To make a big step forward with data science, you first need to do that painful work. That’s an awful waste of resources.

Digital Transformation 115

Digital Transformation Machine Learning Enterprise Insurance 115

Andrew White

JANUARY 11, 2021

As such banking, finance, insurance and media are good examples of information-based industries compared to manufacturing, retail, and so on. But we also know not all data is equal, and not all data is equally valuable. Some data is more a risk than valuable. Would really like to explore this one in debate.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

Domino Data Lab

JULY 22, 2019

You know, companies like telecom and insurance, they don’t really need machine learning.” If you were out five years ago talking in industry about the importance of graphs and graph algorithms and representation of graph data, because most business data ultimately is some form of graph. ” But that changed.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109