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. So here’s why data modeling is so critical to data governance.

Data Governance 144

Data Governance Modeling Metadata Unstructured Data 144

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

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

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

AWS Big Data

APRIL 26, 2023

Having an accurate and up-to-date inventory of all technical assets helps an organization ensure it can keep track of all its resources with metadata information such as their assigned oners, last updated date, used by whom, how frequently and more. This is a guest blog post co-written with Corey Johnson from Huron.

Metadata 52

Metadata Dashboards Visualization Consulting 52

erwin

MAY 31, 2019

The typical notion is that enterprise architects and data (and metadata) architects are in opposite corners. At Avydium , we believe there’s an important middle ground where different architecture disciplines coexist, including enterprise, solution, application, data, metadata and technical architectures.

Data-driven 104

Data-driven Enterprise Metadata Strategy 104

Octopai

JULY 9, 2020

When conducted manually, however, which has tended to be the normal mode of operation before companies discovered automation – or machine learning data lineage solutions, data lineage can be extremely tedious and time-consuming for BI & Analytics teams. Automated Data Lineage Enables Data Teams to Deliver Faster Results.

Insurance 86

Insurance Risk Management Machine Learning Metadata 86

erwin

SEPTEMBER 17, 2020

With complex data architectures and systems within so many organizations, tracking data in motion and data at rest is daunting to say the least. Harvesting the data through automation seamlessly removes ambiguity and speeds up the processing time-to-market capabilities.

Cost-Benefit 143

Cost-Benefit Data Governance Metadata Reporting 143

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

OCTOBER 16, 2020

There’s a common denominator in what they’re all missing, and that is data intelligence. The IDC authors also interviewed erwin customers who described the erwin Data Intelligence Suite , part of the erwin EDGE platform, as a fundamental component of their efforts to generate more value from data while minimizing data-related risk.

Internet of Things 145

Internet of Things Data-driven Uncertainty Data Governance 145

Cloudera

JANUARY 5, 2023

Through the Cloudera Data Platform, UOB has launched a deposit analytics solution to ensure it can build stable deposits with optimal pricing, and provide consistent and accurate views of deposits. The results are higher revenues, lower risks, and increased productivity for the bank.

Cost-Benefit 52

Cost-Benefit Business Objectives Machine Learning Data Architecture 52

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

Cloudera

OCTOBER 11, 2022

Let this sink in a while – AI at scale isn’t magic, it’s data. What these data leaders are saying is that if you can’t do data at scale , you can’t possibly do AI at scale. Risk increases. Data and AI projects cost more and take longer. This leads to the obvious question – how do you do data at scale ?

Snapshot 89

Snapshot Data Science Digital Transformation Metadata 89

Cloudera

SEPTEMBER 28, 2020

By upgrading to CDP Private Cloud Base, the customer is also prepared for the next stages in their CDP journey as they are now enabled to install CDP Private Cloud Experiences to take advantage of Hive LLAP based virtual data warehousing. The total data size is over one petabyte (1PB). Phase 1: Planning. on roadmap).

Testing 130

Testing Metadata Risk Data Science 130

Alation

APRIL 19, 2021

If an enterprise doesn’t have visibility into data, then the process can become time-consuming and costly. With a good plan and a modern data catalog, you can minimize the time and cost of cloud migration. Source: Webinar with data expert Ibby Rahmani: Emerging Trends in Data Architecture: What’s the Next Big Thing?

Cost-Benefit 111

Cost-Benefit Strategy Enterprise Data Strategy 111

AWS Big Data

JANUARY 31, 2023

In addition, data governance is required to comply with an increasingly complex regulatory environment with data privacy (such as GDPR and CCPA) and data residency regulations (such as in the EU, Russia, and China).

Data Lake 78

Data Lake Data Governance Data Architecture Machine Learning 78

AWS Big Data

APRIL 3, 2024

They recognize the importance of accurate, complete, and timely data in enabling informed decision-making and fostering trust in their analytics and reporting processes. Amazon DataZone data assets can be updated at varying frequencies. You can also update an existing data source to enable data quality.

Data Quality 85

Data Quality Visualization Metadata Metrics 85

erwin

OCTOBER 24, 2019

Untapped data, if mined, represents tremendous potential for your organization. While there has been a lot of talk about big data over the years, the real hero in unlocking the value of enterprise data is metadata , or the data about the data. Metadata Is the Heart of Data Intelligence.

Metadata 104

Metadata Management Data-driven Data Architecture 104

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

MAY 31, 2023

This means that specialized roles such as data architects, which focus on modernizing data architecture to help meet business goals, are increasingly important to support data governance. What is a data architect? Their broad range of responsibilities include: Design and implement data architecture.

Data Governance 52

Data Governance Metadata Data Architecture Data Quality 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

APRIL 14, 2022

In today’s AI/ML-driven world of data analytics, explainability needs a repository just as much as those doing the explaining need access to metadata, EG, information about the data being used. The Cloud Data Migration Challenge. Edge computing can be decentralized from on-premises, cellular, data centers, or the cloud.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

Octopai

APRIL 8, 2020

While there are many factors that led to this event, one critical dynamic was the inadequacy of the data architectures supporting banks and their risk management systems. Inaccurate Data Management Leads to Financial Collapse. One reason the financial collapse took the world by surprise was the lack of data transparency.

Finance 52

Finance Cost-Benefit Metadata Data Architecture 52

AWS Big Data

JANUARY 22, 2024

Cost and resource efficiency – This is an area where Acast observed a reduction in data duplication, and therefore cost reduction (in some accounts, removing the copy of data 100%), by reading data across accounts while enabling scaling. In this approach, teams responsible for generating data are referred to as producers.

Data-driven 82

Data-driven Advertising Metadata Data Architecture 82

IBM Big Data Hub

JULY 13, 2023

Physical data integrity is the protection of data wholeness (meaning the data isn’t missing important information), accessibility and accuracy while data is stored or in transit. Natural disasters, power outages, human error and cyberattacks pose risks to the physical integrity of data.

Data Quality 69

Data Quality Data Integration Metadata Cost-Benefit 69

AWS Big Data

NOVEMBER 29, 2023

With Redshift, we are able to view risk counterparts and data in near real time— instead of on an hourly basis. Amazon Redshift ML large language model (LLM) integration Amazon Redshift ML enables customers to create, train, and deploy machine learning models using familiar SQL commands.

Data Warehouse 97

Data Warehouse Data Lake Analytics Machine Learning 97

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.” Data quality /wrangling.

Data Warehouse 69

Data Warehouse Cost-Benefit Data Governance Data-driven 69

Ontotext

FEBRUARY 26, 2024

Each additional graph use case increases its derived value thanks to reducing costs, adding new capabilities, and minimizing risk. RDF tends to be more data and metadata -centric. You also have controlled vocabularies and better data hygiene with data validation. The data can be NLP and text-analysis-ready.

Technology 52

Technology Cost-Benefit Data-driven Metadata 52

CIO Business Intelligence

MARCH 9, 2022

They conveniently store data in a flat architecture that can be queried in aggregate and offer the speed and lower cost required for big data analytics. On the other hand, they don’t support transactions or enforce data quality. Each ETL step risks introducing failures or bugs that reduce data quality. .

Data Lake 119

Data Lake Unstructured Data Data Warehouse Data Quality 119

AWS Big Data

MARCH 26, 2024

Profile aggregation – When you’ve uniquely identified a customer, you can build applications in Managed Service for Apache Flink to consolidate all their metadata, from name to interaction history. Then, you transform this data into a concise format. Enrichment typically involves adding demographic, behavioral, and geolocation data.

Data Strategy 66

Data Strategy Strategy Data Warehouse Prescriptive Analytics 66

CIO Business Intelligence

JANUARY 30, 2024

Even for more straightforward ESG information, such as kilowatt-hours of energy consumed, ESG reporting requirements call for not just the data, but the metadata, including “the dates over which the data was collected and the data quality,” says Fridrich. “The complexity is at a much higher level.”

Reporting 115

Reporting Data Quality Strategy Data-driven 115

AWS Big Data

JULY 20, 2023

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. Orca Security is an industry-leading Cloud Security Platform that identifies, prioritizes, and remediates security risks and compliance issues across your AWS Cloud estate.

Data Lake 84

Data Lake Analytics Snapshot Optimization 84

IBM Big Data Hub

JANUARY 17, 2023

IBM Cloud Pak for Data Express solutions offer clients a simple on ramp to start realizing the business value of a modern architecture. Data governance. The data governance capability of a data fabric focuses on the collection, management and automation of an organization’s data.

Data-driven 57

Data-driven Enterprise Data Governance Prescriptive Analytics 57

AWS Big Data

APRIL 28, 2023

When building a scalable data architecture on AWS, giving autonomy and ownership to the data domains are crucial for the success of the platform. Solution overview In the first post of this series, we explained how Novo Nordisk and AWS Professional Services built a modern data architecture based on data mesh tenets.

Data Governance 65

Data Governance Management Data-driven Data Lake 65

erwin

APRIL 16, 2024

The data mesh framework In the dynamic landscape of data management, the search for agility, scalability, and efficiency has led organizations to explore new, innovative approaches. One such innovation gaining traction is the data mesh framework. This empowers individual teams to own and manage their data.

Metadata 52

Metadata Data Quality Data Governance Modeling 52

Andrew White

JANUARY 9, 2022

Most of D&A concerns and activities are done within EA in the Info/Data architecture domain/phases. Where these efforts break down is in the data that goes into the connection at one end and comes out the other. So, I hear you say, let’s share metadata and make the data self-describing. This is flat wrong.

Analytics 64

Analytics Measurement Modeling Data-driven 64

Sisense

SEPTEMBER 3, 2019

When it comes to picking your node type, while it is easy to see the storage of the Dc2.8xlarge and chose it because it is the largest, if you don’t have the need for that node type, you risk losing out on the benefits of having a distributed database that can process your query in parallel across all of your nodes. Data architecture.

Data Warehouse 78

Data Warehouse OLAP Statistics Cost-Benefit 78