datapine

SEPTEMBER 29, 2022

Reporting being part of an effective DQM, we will also go through some data quality metrics examples you can use to assess your efforts in the matter. But first, let’s define what data quality actually is. What is the definition of data quality? Industry-wide, the positive ROI on quality data is well understood.

Data Quality 241

Data Quality Metrics Data-driven Management 241

Alation

DECEMBER 21, 2022

Transactional systems and data warehouses can then use the golden records as the entity’s most current, trusted representation. Data Catalog and Master Data Management. Early on, analysts used data catalogs to find and understand data more quickly. The MDM tool should help with this.

Management 52

Management Data Quality Metadata Testing 52

Octopai

DECEMBER 10, 2019

Well, scoot over Templeton, because it’s also going to be the year of the Automated Business Glossary for business intelligence and data governance teams everywhere. It should go beyond just listing definitions to key terms. According to the Chinese Zodiac, 2020 is the year of the rat.

Metadata 53

Metadata Data Warehouse Reporting Business Intelligence 53

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

Alation

FEBRUARY 13, 2020

These are all good questions and a logical place to start your data cataloging journey. This brief definition makes several points about data catalogs—data management, searching, data inventory, and data evaluation—but all depend on the central capability to provide a collection of metadata.

Metadata 64

Metadata Data Lake Recreation/Entertainment Big Data 64

Jet Global

JULY 2, 2019

The sheer scale of data being captured by the modern enterprise has necessitated a monumental shift in how that data is stored. From the humble database through to data warehouses , data stores have grown both in scale and complexity to keep pace with the businesses they serve, and the data analysis now required to remain competitive.

Data Lake 73

Data Lake Data Warehouse Big Data Machine Learning 73

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

erwin

FEBRUARY 19, 2021

Metadata management is key to wringing all the value possible from data assets. However, most organizations don’t use all the data at their disposal to reach deeper conclusions about how to drive revenue, achieve regulatory compliance or accomplish other strategic objectives. What Is Metadata? Harvest data.

Metadata 110

Metadata Management Data Quality Cost-Benefit 110

Alation

JULY 28, 2022

It’s costly and time-consuming to manage on-premises data warehouses — and modern cloud data architectures can deliver business agility and innovation. However, CIOs declare that agility, innovation, security, adopting new capabilities, and time to value — never cost — are the top drivers for cloud data warehousing.

Data Warehouse 69

Data Warehouse Cost-Benefit Data Governance Data-driven 69

Alation

MAY 24, 2022

generally available on May 24, Alation introduces the Open Data Quality Initiative for the modern data stack, giving customers the freedom to choose the data quality vendor that’s best for them with the added confidence that those tools will integrate seamlessly with Alation’s Data Catalog and Data Governance application.

Data Quality 98

Data Quality Data Governance Metadata Metrics 98

AWS Big Data

OCTOBER 4, 2023

Collaboration – Analysts, data scientists, and data engineers often own different steps within the end-to-end analytics journey but do not have an simple way to collaborate on the same governed data, using the tools of their choice. Domain is the starting point of a customer’s journey with Amazon DataZone.

Metadata 96

Metadata Data Lake Publishing Data Governance 96

erwin

FEBRUARY 7, 2019

Organization’s cannot hope to make the most out of a data-driven strategy, without at least some degree of metadata-driven automation. The volume and variety of data has snowballed, and so has its velocity. As such, traditional – and mostly manual – processes associated with data management and data governance have broken down.

Metadata 96

Metadata Insurance Data-driven Cost-Benefit 96

Octopai

DECEMBER 12, 2021

What enables you to use all those gigabytes and terabytes of data you’ve collected? Metadata is the pertinent, practical details about data assets: what they are, what to use them for, what to use them with. Without metadata, data is just a heap of numbers and letters collecting dust. Where does metadata come from?

Metadata 93

Metadata Management Data Quality Data Governance 93

Ontotext

MARCH 8, 2023

Rich metadata and semantic modeling continue to drive the matching of 50K training materials to specific curricula, leading new, data-driven, audience-based marketing efforts that demonstrate how the recommender service is achieving increased engagement and performance from over 2.3 million users.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

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

Alation

AUGUST 11, 2022

The data warehouse and analytical data stores moved to the cloud and disaggregated into the data mesh. Today, the brightest minds in our industry are targeting the massive proliferation of data volumes and the accompanying but hard-to-find value locked within all that data. Architectures became fabrics.

Metadata 52

Metadata Data Warehouse Data Quality Data Lake 52

AWS Big Data

JANUARY 24, 2023

AWS Lake Formation helps with enterprise data governance and is important for a data mesh architecture. It works with the AWS Glue Data Catalog to enforce data access and governance. This solution only replicates metadata in the Data Catalog, not the actual underlying data.

Data Architecture 64

Data Architecture Metadata Data Lake Snapshot 64

Alation

JANUARY 17, 2023

The modern data stack is a combination of various software tools used to collect, process, and store data on a well-integrated cloud-based data platform. It is known to have benefits in handling data due to its robustness, speed, and scalability. A typical modern data stack consists of the following: A data warehouse.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Business Intelligence 52

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

Alation

JANUARY 13, 2022

Spoiler alert: data fabric and data mesh are independent design concepts that are, in fact, quite complementary. Data fabric has captured most of the limelight; it focuses on the technologies required to support metadata-driven use cases across hybrid and multi-cloud environments. Gartner on Data Fabric.

Data Lake 59

Data Lake Metadata Data-driven Data Governance 59

Jen Stirrup

MARCH 29, 2023

Organisations are looking at ways of simplifying data; for example, through simple rebranding efforts to disguise the complexity. However, SAP Datasphere goes much deeper deeper than a simple rebranding; it is the next generation of SAP Data Warehouse Cloud.

Metadata 120

Metadata Data Warehouse Data Integration Business Intelligence 120

Octopai

SEPTEMBER 10, 2019

Enterprises today are focused on ensuring robust data governance, and are exploring different tools and approaches to support their efforts. Some organizations know exactly what they need, while others can be overwhelmed or confused by all the different solutions out there that claim to support data governance.

Metadata 40

Metadata Data Governance Cost-Benefit Reporting 40

Alation

JANUARY 25, 2022

Data Fabric: A Love Story , we defined data fabric and outlined its uses and motivations. As a reminder, here’s Gartner’s definition of data fabric: “A design concept that serves as an integrated layer (fabric) of data and connecting processes. The data catalog is a foundational layer of the data fabric.

Metadata 52

Metadata IT Metrics Data-driven 52

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. Automate data model and database schema generation.

Modeling 111

Modeling Cost-Benefit Visualization Metadata 111

Domino Data Lab

JULY 2, 2019

In other words, using metadata about data science work to generate code. In this case, code gets generated for data preparation, where so much of the “time and labor” in data science work is concentrated. ” Spark programs are DAGs by definition, designed to use a wide variety of different kinds of data sources.

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

Alation

FEBRUARY 8, 2022

Making the experts responsible for service streamlines the data-request pipeline, delivering higher quality data into the hands of those who need it more rapidly. Some argue that data governance and quality practices may vary between domains. Secure and governed by a global access control. ” 1.

Data Governance 52

Data Governance Data-driven Metadata Enterprise 52

Cloudera

MARCH 6, 2018

Instead, they have separate data stores and inconsistent (if any) frameworks for data governance, management, and security. If catalog metadata and business definitions live with transient compute resources, they will be lost, requiring work to recreate later and making auditing impossible.

Analytics 40

Analytics Metadata Recreation/Entertainment Big Data 40

Alation

SEPTEMBER 6, 2022

Ten years ago, there was no modern data catalog. So I was excited to sit down recently with Michael Ting, Senior Software Engineer on the Logical Metadata Infrastructure Team. And we change how we estimate every two weeks based on new data we get. That we have one today is testament to the work of our engineers.

Data-driven 52

Data-driven Software Testing Metadata 52

erwin

JULY 17, 2019

Your organization won’t be able to take complete advantage of analytics tools to become data-driven unless you establish a foundation for agile and complete data management. You need automated data mapping and cataloging through the integration lifecycle process, inclusive of data at rest and data in motion.

Digital Transformation 98

Digital Transformation Strategy Metadata Data-driven 98

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.” Why keep data at all?

Metadata 64

Metadata Data Governance Dashboards Software 64

IBM Big Data Hub

JULY 5, 2023

Their fast adoption meant that customers soon lost track of what ended up in the data lake. And, just as challenging, they could not tell where the data came from, how it had been ingested nor how it had been transformed in the process. Data governance remains an unexplored frontier for this technology.

Data Lake 71

Data Lake Metadata Cost-Benefit Data Warehouse 71

AWS Big Data

DECEMBER 21, 2023

To speed up the self-service analytics and foster innovation based on data, a solution was needed to provide ways to allow any team to create data products on their own in a decentralized manner. To create and manage the data products, smava uses Amazon Redshift , a cloud data warehouse.

Data Lake 85

Data Lake Data Warehouse B2B Data-driven 85

Alation

JUNE 30, 2022

We are now seeing a similar transformation in the world of data, where there’s tension between the old world (single-source-of-truth data warehouses with top-down data governance) and the new world (distributed, self-service analytics with grassroots management). Data quality can change with time.

Metadata 52

Metadata Data Warehouse Data Quality Data-driven 52

Jet Global

FEBRUARY 23, 2024

The quick and dirty definition of data mapping is the process of connecting different types of data from various data sources. Data mapping is a crucial step in data modeling and can help organizations achieve their business goals by enabling data integration, migration, transformation, and quality.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

Jet Global

DECEMBER 17, 2021

For example, the research finds that nearly half (48%) of finance organizations spend too much time on closing the books in reporting entities, and a similar percentage spend too much time on subsequent steps, such as, data collection, validation, and submission of data to the corporate center.

Reporting 52

Reporting Management Recreation/Entertainment Finance 52