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

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 94

Strategy Data Architecture Cost-Benefit Reporting 94

Cloudera

NOVEMBER 1, 2022

A quick trip in the congressional time machine to revisit 2017’s Modernizing Government Technology Act surfaces some of the most salient points regarding agencies’ challenges: The federal government spends nearly 75% of its annual information technology funding on operating and maintaining existing legacy information technology systems.

Cost-Benefit 83

Cost-Benefit Data Architecture Risk IoT 83

AWS Big Data

JANUARY 31, 2023

Data governance is the collection of policies, processes, and systems that organizations use to ensure the quality and appropriate handling of their data throughout its lifecycle for the purpose of generating business value.

Data Lake 82

Data Lake Data Governance Data Architecture Machine Learning 82

AWS Big Data

APRIL 29, 2024

This system simplifies managing user access, saves time for data security administrators, and minimizes the risk of configuration errors. Effective permission management helps tackle these challenges by controlling how data is accessed and used, providing data integrity and minimizing the risk of data breaches.

Management 83

Management Big Data Metadata Data Warehouse 83

Cloudera

JUNE 29, 2023

To ensure the stability of the US financial system, the implementation of advanced liquidity risk models and stress testing using (MI/AI) could potentially serve as a protective measure. To improve the way they model and manage risk, institutions must modernize their data management and data governance practices.

Data Architecture 81

Data Architecture Risk Management Risk Management 81

erwin

SEPTEMBER 13, 2022

Speakers will cover data intelligence and governance on the first day of the summit. Day one will feature presentations from industry experts and experienced data professionals on the initiatives and tactical measures being taken by data-driven enterprises to reap the benefits of data intelligence and governance.

Data Governance 52

Data Governance Data-driven Data Architecture Data Quality 52

Alation

MARCH 31, 2023

Ehtisham Zaidi, Gartner’s VP of data management, and Robert Thanaraj, Gartner’s director of data management, gave an update on the fabric versus mesh debate in light of what they call the “active metadata era” we’re currently in. The foundations of successful data governance The state of data governance was also top of mind.

Data Analytics 52

Data Analytics Analytics Metadata Data Governance 52

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

MAY 1, 2023

The complexity of an organization’s application landscape, along with the lack of perceived value in modernizing core applications to introduce new capabilities and enhance existing capabilities, introduces risk to both internal colleagues and external customers.

Consulting 59

Consulting Data Governance Digital Transformation ROI 59

IBM Big Data Hub

JUNE 30, 2022

The diversity of data types, data processing, integration and consumption patterns used by organizations has grown exponentially. Competition plays harder, and every day, new business models and alternatives driven by data and digitalization surface in almost every industry.

Data Strategy 57

Data Strategy Strategy Business Objectives Data-driven 57

erwin

DECEMBER 12, 2019

Metadata is an important part of data governance, and as a result, most nascent data governance programs are rife with project plans for assessing and documenting metadata. But in many scenarios, it seems that the underlying driver of metadata collection projects is that it’s just something you do for data governance.

Metadata 84

Metadata Data Governance Digital Transformation Data Quality 84

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 94

Enterprise Data Architecture Strategy Data Governance 94

erwin

OCTOBER 16, 2020

IDC defines data intelligence as business, technical, relational, and operational metadata that provides transparency of data profiles, classification, quality, location, context, and lineage, providing people, processes, and technology with trustworthy, reliable data. Parts of this blog are excerpted from my keynote on day No.

Internet of Things 145

Internet of Things Data-driven Uncertainty Data Governance 145

Anmut

APRIL 6, 2023

By regularly conducting data maturity assessments, you can catch potential issues early and make proactive changes to supercharge your business’s success. Cost savings By identifying areas where data management processes can be optimised, organisations can reduce costs associated with data management and analysis.

Cost-Benefit 52

Cost-Benefit Data Quality Data Governance Measurement 52

erwin

SEPTEMBER 17, 2020

Replace manual and recurring tasks for fast, reliable data lineage and overall data governance. It’s paramount that organizations understand the benefits of automating end-to-end data lineage. The importance of end-to-end data lineage is widely understood and ignoring it is risky business.

Cost-Benefit 143

Cost-Benefit Data Governance Metadata Reporting 143

Octopai

JULY 9, 2020

By adopting automated data lineage and automated metadata tagging, companies have the opportunity to increase their data processing speed. That increase can manage huge endeavors, such as migrations, error location, and new data governance integrations which then become “routine” operations.

Insurance 86

Insurance Risk Management Machine Learning Metadata 86

Cloudera

SEPTEMBER 15, 2022

The consumption of the data should be supported through an elastic delivery layer that aligns with demand, but also provides the flexibility to present the data in a physical format that aligns with the analytic application, ranging from the more traditional data warehouse view to a graph view in support of relationship analysis.

Data Lake 78

Data Lake Data Architecture Data-driven Data Warehouse 78

erwin

DECEMBER 12, 2019

Metadata is an important part of data governance, and as a result, most nascent data governance programs are rife with project plans for assessing and documenting metadata. But in many scenarios, it seems that the underlying driver of metadata collection projects is that it’s just something you do for data governance.

Metadata 52

Metadata Data Governance Digital Transformation Data Quality 52

CIO Business Intelligence

APRIL 29, 2022

The strategy should put formalized processes in place to quantify the value of different types of information, leveraging the skills of a chief data officer (CDO), who should form and chair a data governance committee. Prioritize your investments.

Digital Transformation 132

Digital Transformation Strategy Data-driven Data Strategy 132

Alation

MAY 31, 2023

The state of data governance is evolving as organizations recognize the significance of managing and protecting their data. With stricter regulations and greater demand for data-driven insights, effective data governance frameworks are critical. What is a data architect?

Data Governance 52

Data Governance Metadata Data Architecture Data Quality 52

Alation

JULY 30, 2021

2: Biz Problem – Making Data Ready for Business Analysis. Good, trusted data is no accident; data governance is a crucial prerequisite. As Tom Davenport argues in Analytics at Work, “You can’t be really good at analytics without really good data.” (23). Clean it up before or as part of switching and moving.

Data Warehouse 52

Data Warehouse Data Governance Machine Learning Data-driven 52

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 82

Insurance Data Architecture Risk Management Risk 82

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 83

Data Architecture Data Strategy Risk Management Strategy 83

TDAN

JULY 5, 2022

Whichever metaphor you would like to use, what is certain is that no organization will survive the twenty-first century without optimizing the use of its data assets. Similarly, cybersecurity, privacy, and compliance risks increasingly present huge […].

Data-driven 52

Data-driven Risk Optimization Enterprise 52

Alation

FEBRUARY 13, 2020

Pfizer’s data catalog is at the heart of the company’s Virtual Analytics Workbench , which has been instrumental in identifying rare forms of heart failure. MunichRe’s data catalog sped the introduction of new, innovative data products to mitigate the risk of high impact crises caused by global warming.

Enterprise 52

Enterprise Data Lake Machine Learning Data-driven 52

Alation

MARCH 7, 2023

If data is the octopus, each tentacle then serves as a way to put that data to work. Some are dedicated to the management of the data : architecture, access, analytics, visualization, and automation. The remaining arms are focused more on finding value: governance, lineage , and curation.

Data-driven 52

Data-driven Forecasting Data Science Optimization 52

Jim Harris

JANUARY 1, 2016

The business folks usually own the data, or at least the business processes that create it, so they understand its meaning and daily use. The technical folks usually own the hardware and software comprising your data architecture. However, a data governance framework is often necessary for defect prevention to be successful.

Data Quality 61

Data Quality Data Governance Cost-Benefit ROI 61

AWS Big Data

JUNE 29, 2023

Therefore, over time, multiple Data Definition Language (DDL) or Data Control Language (DCL) queries, such as CREATE, ALTER, DROP, GRANT, or REVOKE SQL queries, are run on the Amazon Redshift data warehouse, which are sensitive in nature because they could lead to dropping tables or deleting data, causing disruptions or outages.

Data Warehouse 60

Data Warehouse Dashboards Testing Visualization 60

AWS Big Data

APRIL 28, 2023

The third post will show how end-users can consume data from their tool of choice, without compromising data governance. When building a scalable data architecture on AWS, giving autonomy and ownership to the data domains are crucial for the success of the platform.

Data Governance 65

Data Governance Management Data-driven Data Lake 65

Cloudera

OCTOBER 19, 2023

While navigating so many simultaneous data-dependent transformations, they must balance the need to level up their data management practices—accelerating the rate at which they ingest, manage, prepare, and analyze data—with that of governing this data.

Data-driven 73

Data-driven Data Architecture Predictive Modeling Digital Transformation 73

BizAcuity

APRIL 14, 2022

Be it supply chain resilience, staff management, trend identification, budget planning, risk and fraud management, big data increases efficiency by making data-driven predictions and forecasts. With adequate market intelligence, big data analytics can be used for unearthing scope for product improvement or innovation.

Big Data 52

Big Data Data Analytics Management Unstructured Data 52

Alation

JULY 28, 2022

The cloud is no longer synonymous with risk. There was a time when most CIOs would never consider putting their crown jewels — AKA customer data and associated analytics — into the cloud. What Are the Biggest Drivers of Cloud Data Warehousing? I am not interested in owning that risk internally.” They need a plan.

Data Warehouse 69

Data Warehouse Cost-Benefit Data Governance Data-driven 69

Alation

APRIL 14, 2022

Semantics, context, and how data is tracked and used mean even more as you stretch to reach post-migration goals. This is why, when data moves, it’s imperative for organizations to prioritize data discovery. Data discovery is also critical for data governance , which, when ineffective, can actually hinder organizational growth.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

TDAN

NOVEMBER 15, 2022

In 2006, the world learned an inconvenient truth. The planet we call “home” was getting hotter and we were to blame. Naturally, being intelligent and rational beings, we took the action necessary to prevent the oncoming catastrophe.

Data Architecture 52

Data Architecture Risk Data Strategy Business Intelligence 52

CIO Business Intelligence

SEPTEMBER 20, 2023

What we seek is to have a clear data architecture with a single point of origin for the information and for it to be consumed by whomever applies BI, advanced analytics, and so on. For this, we’re also working on creating a platform in the cloud for each country, which puts order in the data architecture.

Modeling 98

Modeling Insurance IT Cost-Benefit 98

IBM Big Data Hub

JULY 13, 2023

This is the practice of creating, updating and consistently enforcing the processes, rules and standards that prevent errors, data loss, data corruption, mishandling of sensitive or regulated data, and data breaches. Reduced data quality can result in productivity losses, revenue decline and reputational damage.

Data Quality 68

Data Quality Data Integration Metadata Cost-Benefit 68