CIO Business Intelligence

AUGUST 21, 2024

“The systems are fed the data, and trained, and then improve over time on their own.” Adding smarter AI also adds risk, of course. “At The big risk is you take the humans out of the loop when you let these into the wild.” Many risks are the same as gen AI in general since it’s gen AI that powers agentic systems.

Risk 136

Risk Insurance Cost-Benefit Software 136

CIO Business Intelligence

APRIL 8, 2025

Fragmented systems, inconsistent definitions, legacy infrastructure and manual workarounds introduce critical risks. Data quality is no longer a back-office concern. We also examine how centralized, hybrid and decentralized data architectures support scalable, trustworthy ecosystems.

Data Quality 102

Data Quality Data-driven Key Performance Indicator Metadata 102

DataKitchen

JUNE 1, 2022

They have a Low Change Appetite: Teams have complicated in place data architectures and tools. There is no single pane of glass: no ability to see across all tools, pipelines, data sets, and teams in one place. How do other organizations solve this risk problem? The biggest risk of all is space flight.

Risk 100

Risk Management Testing Dashboards 100

CIO Business Intelligence

OCTOBER 24, 2024

This retreat risks stifling long-term growth and innovation as leaders realize that the ROI from AI will unfold over a more extended period of time than initially anticipated.” 40% of highly regulated enterprises will combine data and AI governance.

ROI 127

ROI Data-driven Enterprise Experimentation 127

Cloudera

AUGUST 9, 2022

With all of the buzz around cloud computing, many companies have overlooked the importance of hybrid data. Many large enterprises went all-in on cloud without considering the costs and potential risks associated with a cloud-only approach. The truth is, the future of data architecture is all about hybrid.

Data Architecture 92

Data Architecture Data Strategy Strategy Data-driven 92

CIO Business Intelligence

JULY 28, 2023

This approach allows enterprises to streamline processes, gather data for specific purposes, get better insights from data in a secure environment, and efficiently share it. 1 A clear picture of where data lives and how it moves enables enterprises to consistently protect this data and its privacy.

Risk 98

Risk Management Data mining Cost-Benefit 98

Cloudera

JULY 29, 2022

It supports business objectives like increasing revenues, improving customer experience, and driving profitability by giving business units and users access to relevant data so they can quickly gain the insight they need. This does not mean ‘one of each’ – a public cloud data strategy and an on-prem data strategy.

Data Architecture 89

Data Architecture Data Strategy Risk Management Strategy 89

Cloudera

JUNE 27, 2023

The way to achieve this balance is by moving to a modern data architecture (MDA) that makes it easier to manage, integrate, and govern large volumes of distributed data. When you deploy a platform that supports MDA you can consolidate other systems, like legacy data mediation and disparate data storage solutions.

Data Architecture 62

Data Architecture Predictive Modeling Data Governance Data-driven 62

Cloudera

DECEMBER 17, 2024

The introduction of these faster, more powerful networks has triggered an explosion of data, which needs to be processed in real time to meet customer demands. Traditional data architectures struggle to handle these workloads, and without a robust, scalable hybrid data platform, the risk of falling behind is real.

Enterprise 62

Enterprise Data Architecture Data-driven Optimization 62

CIO Business Intelligence

DECEMBER 11, 2024

Furthermore, generally speaking, data should not be split across multiple databases on different cloud providers to achieve cloud neutrality. Not my original quote, but a cardinal sin of cloud-native data architecture is copying data from one location to another.

Management 111

Management Data Governance Data Science Reporting 111

CIO Business Intelligence

FEBRUARY 20, 2024

In this way, manufacturers would be able to reduce risk, increase resilience and agility, boost productivity, and minimise their environmental footprint. According to Gartner , as much as 75% of operational decisions could be made within an AI-enabled application or process by 2030.

Data Architecture 98

Data Architecture Unstructured Data Manufacturing IT 98

Cloudera

JANUARY 7, 2025

A leading meal kit provider migrated its data architecture to Cloudera on AWS, utilizing Cloudera’s Open Data Lakehouse capabilities. This transition streamlined data analytics workflows to accommodate significant growth in data volumes.

Cost-Benefit 82

Cost-Benefit Optimization Strategy Data-driven 82

IBM Big Data Hub

AUGUST 4, 2023

Today, the way businesses use data is much more fluid; data literate employees use data across hundreds of apps, analyze data for better decision-making, and access data from numerous locations. This results in more marketable AI-driven products and greater accountability.

Data Architecture 59

Data Architecture Data Lake Machine Learning Data Governance 59

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

Alation

JANUARY 9, 2023

Alation joined with Ortecha , a data management consultancy, to publish a white paper providing insights and guidance to stakeholders and decision-makers charged with implementing or modernising data risk management functions. The Increasing Focus On Data Risk Management. Download the complete white paper now.

Risk Management 52

Risk Management Risk Management Metadata 52

erwin

JULY 9, 2020

For more info about how enterprise architecture differs from solutions, technical and data architecture, see: The Difference Between Enterprise Architecture and Solutions Architecture. The Difference Between Enterprise Architecture and Technical Architecture.

Enterprise 145

Enterprise Data Architecture Data-driven Digital Transformation 145

DataKitchen

NOVEMBER 5, 2024

This architecture is valuable for organizations dealing with large volumes of diverse data sources, where maintaining accuracy and accessibility at every stage is a priority. It sounds great, but how do you prove the data is correct at each layer? How do you ensure data quality in every layer ?

Data Quality 195

Data Quality Testing Metrics Reporting 195

erwin

JULY 12, 2019

Modern, strategic data governance , which involves both IT and the business, enables organizations to plan and document how they will discover and understand their data within context, track its physical existence and lineage, and maximize its security, quality and value. Strengthen data security. How erwin Can Help.

Data Governance 110

Data Governance Management Metadata Risk Management 110

erwin

JUNE 19, 2020

Despite the similarities in name, there are a number of key differences between an enterprise architecture and solutions architecture. Much like the differences between enterprise architecture (EA) and data architecture, EA’s holistic view of the enterprise will often see enterprise and solution architects collaborate.

Enterprise 130

Enterprise Data Architecture Strategy Data Governance 130

CIO Business Intelligence

OCTOBER 25, 2022

The data platform supports several critical initiatives in this industry: Support for new product development by using data to identify opportunities where current services aren’t available or are unattractive to customers. The use of a data platforms to drive new product offers and address customer needs is already beginning.

Insurance 119

Insurance Data Architecture Data-driven Interactive 119

TDAN

MAY 16, 2023

Cybersecurity risks in procurement can result in significant financial loss, reputational damage, and legal liability. Procurement is an essential function within any organization, involving the acquisition of goods and services necessary for business operations. Therefore, it is crucial […]

Risk 52

Risk Technology Risk Management Data Architecture 52

erwin

JUNE 25, 2020

The Difference Between Technical Architecture and Enterprise Architecture. We previously have discussed the difference between data architecture and EA plus the difference between solutions architecture and EA. Lower risks and costs driven by an enhanced ability to identify redundant systems and processes.

Enterprise 144

Enterprise Data Architecture Data-driven Cost-Benefit 144

IBM Big Data Hub

APRIL 10, 2023

A well-designed data architecture should support business intelligence and analysis, automation, and AI—all of which can help organizations to quickly seize market opportunities, build customer value, drive major efficiencies, and respond to risks such as supply chain disruptions.

Strategy 85

Strategy Data Architecture Cost-Benefit Reporting 85

TDAN

OCTOBER 17, 2023

Nonetheless, utilizing cloud computing carries potential risks that need to be addressed for sustainable […] Regardless of whether private, public, or hybrid cloud models are employed, the advantages of cloud computing are numerous, including heightened efficiency, reduced expenses, and increased flexibility.

Risk 52

Risk Management Modeling Data Architecture 52

AWS Big Data

DECEMBER 4, 2024

With this launch, you can query data regardless of where it is stored with support for a wide range of use cases, including analytics, ad-hoc querying, data science, machine learning, and generative AI. We’ve simplified data architectures, saving you time and costs on unnecessary data movement, data duplication, and custom solutions.

Data Analytics 85

Data Analytics Analytics Data Lake Data Quality 85

Cloudera

NOVEMBER 1, 2022

These systems can pose operational risks, including rising costs and the inability to meet mission requirements. . Mission use case: increasing visibility and mitigating supply chain risk . The source and availability of every material and part across each branch is an opportunity for risk.

Cost-Benefit 89

Cost-Benefit Data Architecture Risk IoT 89

erwin

JANUARY 9, 2020

For decades, data modeling has been the optimal way to design and deploy new relational databases with high-quality data sources and support application development. Today’s data modeling is not your father’s data modeling software. And the good news is that it just keeps getting better.

Data Governance 144

Data Governance Modeling Metadata Unstructured Data 144

CIO Business Intelligence

MARCH 9, 2022

When looking to move large portions of their application portfolios to a cloud-first model, organizations should ensure their developers embrace well-defined, cloud-native principles, says Brian Campbell, principal at Deloitte, including the use of APIs, microservices, and a modern data architecture.

Strategy 145

Strategy Consulting Risk Testing 145

erwin

OCTOBER 24, 2019

It is the only solution that can automatically harvest, transform and feed metadata from operational processes, business applications and data models into a central data catalog and then made accessible and understandable within the context of role-based views. With erwin, organizations can: 1.

Metadata 104

Metadata Management Data-driven Data Architecture 104

CIO Business Intelligence

MARCH 24, 2023

The Business Application Research Center (BARC) warns that data governance is a highly complex, ongoing program, not a “big bang initiative,” and it runs the risk of participants losing trust and interest over time.

Data Governance 142

Data Governance Management Metadata Data Quality 142

Cloudera

MAY 30, 2024

In this context, Cloudera and TAI Solutions have partnered to help financial services customers accelerate their data-driven transformation, improve customer centricity, ensure compliance with regulations, enhance risk management, and drive innovation. Regulation and risk are a big focus for financial institutions.

Data Analytics 81

Data Analytics Risk Management Analytics Digital Transformation 81

AWS Big Data

FEBRUARY 1, 2024

Amazon Redshift features like streaming ingestion, Amazon Aurora zero-ETL integration , and data sharing with AWS Data Exchange enable near-real-time processing for trade reporting, risk management, and trade optimization. Ruben Falk is a Capital Markets Specialist focused on AI and data & analytics.

Data Warehouse 131

Data Warehouse Dashboards Risk Management Risk 131

CIO Business Intelligence

JANUARY 20, 2023

Doing it right requires thoughtful data collection, careful selection of a data platform that allows holistic and secure access to the data, and training and empowering employees to have a data-first mindset. Security and compliance risks also loom.

Data Lake 135

Data Lake Data-driven Finance Data Architecture 135

CIO Business Intelligence

APRIL 12, 2023

After walking his executive team through the data hops, flows, integrations, and processing across different ingestion software, databases, and analytical platforms, they were shocked by the complexity of their current data architecture and technology stack. It isn’t easy.

Machine Learning 145

Machine Learning Cost-Benefit Data-driven Strategy 145

CIO Business Intelligence

MARCH 19, 2025

Additionally, Deloittes ESG Trends Report highlights fragmented ESG data, inconsistent reporting frameworks and difficulties in measuring sustainability ROI as primary challenges preventing organizations from fully leveraging their data for ESG initiatives.

IT 59

IT Data Governance Data-driven Metrics 59

Octopai

JULY 9, 2020

It required banks to develop a data architecture that could support risk-management tools. Not only did the banks need to implement these risk-measurement systems (which depend on metrics arriving from distinct data dictionary tools), they also needed to produce reports documenting their use.

Insurance 98

Insurance Risk Management Machine Learning Metadata 98

Cloudera

JANUARY 30, 2023

This dark data resides everywhere in the enterprise, siloed in multiple data repositories, from laptops and mobile devices to data lakes and applications. The purpose of this blog isn’t to emphasize the cyber risk of dark data but to spotlight its implications.

IoT 83

IoT Data Architecture Data Lake Machine Learning 83