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 are these rampant and often uncontrolled projects to collect metadata properly motivated? What Is Metadata?

Metadata 52

Metadata Data Governance Digital Transformation Data Quality 52

CIO Business Intelligence

OCTOBER 13, 2023

Application data architect: The application data architect designs and implements data models for specific software applications. Information/data governance architect: These individuals establish and enforce data governance policies and procedures.

Data Architecture 132

Data Architecture Data Warehouse Statistics Visualization 132

erwin

JANUARY 17, 2020

Data modeling is a process that enables organizations to discover, design, visualize, standardize and deploy high-quality data assets through an intuitive, graphical interface. Data models provide visualization, create additional metadata and standardize data design across the enterprise. SQL or NoSQL?

Data-driven 138

Data-driven Modeling Metadata Data Governance 138

IBM Big Data Hub

DECEMBER 16, 2022

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

IBM Big Data Hub

NOVEMBER 4, 2022

Data observability capability makes data quality checks upstream possible. Data Governance. Ensuring data quality is critical for data governance initiatives. It is critical to promote a common business language across the enterprise to break down these silos.

Data Quality 57

Data Quality Metadata Data Governance Data-driven 57

IBM Big Data Hub

JANUARY 5, 2023

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

datapine

SEPTEMBER 29, 2022

With quality data at their disposal, organizations can form data warehouses for the purposes of examining trends and establishing future-facing strategies. Industry-wide, the positive ROI on quality data is well understood. The program manager should lead the vision for quality data and ROI. 2 – Data profiling.

Data Quality 241

Data Quality Metrics Data-driven Management 241

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 96

Strategy Data Architecture Cost-Benefit Reporting 96

erwin

APRIL 27, 2022

Best Data Governance Solution (erwin Data Intelligence). Best Data Modeling Solution (erwin Data Modeler). Best Data Security Solution (Quest ApexSQL). Best Data Governance Solution (erwin Data Intelligence). Best Data Governance Solution (erwin Data Intelligence).

Data Governance 52

Data Governance Digital Transformation Metadata Data Warehouse 52

AWS Big Data

MARCH 7, 2023

Analytics reference architecture for gaming organizations In this section, we discuss how gaming organizations can use a data hub architecture to address the analytical needs of an enterprise, which requires the same data at multiple levels of granularity and different formats, and is standardized for faster consumption.

Analytics 72

Analytics Data Warehouse Data Lake Metadata 72

AWS Big Data

MARCH 10, 2023

Since the deluge of big data over a decade ago, many organizations have learned to build applications to process and analyze petabytes of data. Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats.

Data Lake 105

Data Lake Sales Data Warehouse Snapshot 105

Octopai

JANUARY 31, 2021

The particular episode we recommend looks at how WeWork struggled with understanding their data lineage so they created a metadata repository to increase visibility. Agile Data. Another podcast we think is worth a listen is Agile Data. In terms of data lineage, they offer an excellent definition here. .

Data Governance 57

Data Governance Data Processing Data Quality Metadata 57

Domino Data Lab

APRIL 3, 2019

Paco Nathan ‘s latest column dives into data governance. This month’s article features updates from one of the early data conferences of the year, Strata Data Conference – which was held just last week in San Francisco. In particular, here’s my Strata SF talk “Overview of Data Governance” presented in article form.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

Jet Global

JULY 2, 2019

HDInsight: When it comes to Big Data analysis, the open-source Hadoop framework remains one of the most popular options. Just like actual lakes, the long-term health of your organizational data lake depends on defending it from ‘pollution’—data governance is critical to ensure your data lake doesn’t become a data swamp.

Data Lake 73

Data Lake Data Warehouse Big Data Machine Learning 73

AWS Big Data

MAY 7, 2024

Data governance is a key enabler for teams adopting a data-driven culture and operational model to drive innovation with data. Amazon DataZone allows you to simply and securely govern end-to-end data assets stored in your Amazon Redshift data warehouses or data lakes cataloged with the AWS Glue data catalog.

Metadata 77

Metadata Data Lake Data Processing Data-driven 77

AWS Big Data

SEPTEMBER 25, 2023

The enterprise standardized data from the EDW cluster is accessed by multiple consumer clusters using the Redshift data sharing feature to run downstream reports, dashboards, and other analytics workloads. Auditor data mart – This is only used for a few hours a day to run scheduled reports. 5 Used by the superuser queue.

Management 97

Management Data Warehouse Metrics Dashboards 97

Domino Data Lab

JULY 22, 2019

data science’s emergence as an interdisciplinary field – from industry, not academia. why data governance, in the context of machine learning is no longer a “dry topic” and how the WSJ’s “global reckoning on data governance” is potentially connected to “premiums on leveraging data science teams for novel business cases”.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Peter James Thomas

AUGUST 29, 2018

I have since run and driven transformation in Reference Data, Master Data , KYC [3] , Customer Data, Data Warehousing and more recently Data Lakes and Analytics , constantly building experience and capability in the Data Governance , Quality and data services domains, both inside banks, as a consultant and as a vendor.

Data-driven 61

Data-driven Cost-Benefit Metadata Technology 61

IBM Big Data Hub

JANUARY 17, 2023

Essential components of a data lakehouse architecture and what makes an open data lakehouse. At the core of a data lakehouse architecture includes the storage, metadata service and the query engine, and typically a data governance component made up of a policy engine and a data dictionary.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

erwin

MAY 27, 2020

What, then, should users look for in a data modeling product to support their governance/intelligence requirements in the data-driven enterprise? Nine Steps to Data Modeling. Provide metadata and schema visualization regardless of where data is stored.

Modeling 98

Modeling Metadata Data Governance Visualization 98

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

IBM Big Data Hub

OCTOBER 12, 2023

They’re built on machine learning algorithms that create outputs based on an organization’s data or other third-party big data sources. Sometimes, these outputs are biased because the data used to train the model was incomplete or inaccurate in some way. And that makes sense.

Cost-Benefit 85

Cost-Benefit Metadata Data Governance Modeling 85

AWS Big Data

JANUARY 22, 2024

The majority of data produced by these accounts is used downstream for business intelligence (BI) purposes and in Amazon Athena , by hundreds of business users every day. The solution Acast implemented is a data mesh, architected on AWS. Srikant Das is an Acceleration Lab Solutions Architect at Amazon Web Services.

Data-driven 88

Data-driven Advertising Metadata Data Architecture 88

TDAN

JUNE 21, 2022

Twenty-five years ago today, I published the first issue of The Data Administration Newsletter. It only took a few months to recognize that there was an audience for an “online” publication focused on data administration. […].

Publishing 78

Publishing Data Quality Data Architecture IT 78

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. Geocoding Geocoding is the process of adding location metadata to an organization’s datasets.

Data Quality 70

Data Quality Data Integration Metadata Cost-Benefit 70

AWS Big Data

APRIL 28, 2023

The first post of this series describes the overall architecture and how Novo Nordisk built a decentralized data mesh architecture, including Amazon Athena as the data query engine. The third post will show how end-users can consume data from their tool of choice, without compromising data governance.

Data Governance 67

Data Governance Management Data-driven Data Lake 67

Alation

MARCH 21, 2023

To fully realize data’s value, organizations in the travel industry need to dismantle data silos so that they can securely and efficiently leverage analytics across their organizations. What is big data in the travel and tourism industry? What are common data challenges for the travel industry?

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

TDAN

DECEMBER 6, 2022

Companies are increasingly focused on finding ways to connect to new and valuable sources of data in order to enhance their analytical capabilities, enrich their models, or deliver more insight to their business units. Due to the increased demand for new data sources, companies are also looking at their internal data differently.

Modeling 52

Modeling Analytics Metadata Data Governance 52

Alation

JANUARY 17, 2023

A typical modern data stack consists of the following: A data warehouse. Data ingestion/integration services. Data orchestration tools. Business intelligence (BI) platforms. These tools are used to manage big data, which is defined as data that is too large or complex to be processed by traditional means.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

TDAN

MAY 3, 2022

The road to creating business value through a well-oiled data management strategy can be long and challenging. A successful data management strategy is one that generates value rapidly and unlocks new data-driven insights.

Analytics 52

Analytics Data-driven Strategy Management 52

AWS Big Data

JUNE 9, 2023

Data in customers’ data lakes is used to fulfil a multitude of use cases, from real-time fraud detection for financial services companies, inventory and real-time marketing campaigns for retailers, or flight and hotel room availability for the hospitality industry.

Data Lake 116

Data Lake Metadata Optimization Statistics 116

erwin

SEPTEMBER 25, 2020

Therefore, the visual representation provided by a data model gives organizations the confidence to design their proposed systems and take them live. Data modeling is a critical component of metadata management , data governance and data intelligence. Increase agility in application development.

Modeling 111

Modeling Cost-Benefit Visualization Metadata 111

TDAN

JUNE 30, 2020

About a week ago, I was teaching a data modeling class, and an attendee asked me to explain the concept of a data catalog. However, I had recently read the book, The Data Catalog: Sherlock Holmes Data Sleuthing for Analytics by […]. Like a lot of hype-related terms in IT, there is more than one definition.

Modeling 52

Modeling Analytics Data Architecture IT 52

IBM Big Data Hub

MARCH 14, 2024

This involves unifying and sharing a single copy of data and metadata across IBM® watsonx.data ™, IBM® Db2 ®, IBM® Db2® Warehouse and IBM® Netezza ®, using native integrations and supporting open formats, all without the need for migration or recataloging. .

Cost-Benefit 85

Cost-Benefit Metadata Optimization Management 85

erwin

JUNE 27, 2019

From a business-outcome perspective, a data modeling tool is used to help organizations: Effectively manage and govern massive volumes of data. Consolidate and build applications with hybrid architectures, including traditional, Big Data, cloud and on premise.

Measurement 81

Measurement Modeling Unstructured Data Metadata 81

Grooper

OCTOBER 23, 2019

Lack of competitiveness or business losses seem to be the main drivers to becoming more proactive with data governance and management. What you’re shooting for is enterprise-wide information governance. Each department controls their data silos without a central policy or plan.

Metrics 59

Metrics Measurement Strategy Optimization 59

Alation

FEBRUARY 13, 2020

Gartner: Magic Quadrant for Metadata Management Solutions. Magic Quadrant for Metadata Management Solutions 4 based on its ability to execute and completeness of vision. Today, metadata management has become a critical business driver as data leaders seek to govern and maximize the value from the influx of data at their disposal.

Metadata 52

Metadata Machine Learning Data Governance Reporting 52