erwin

JUNE 26, 2020

It’s no surprise that most organizations’ data is often fragmented and siloed across numerous sources (e.g., legacy systems, data warehouses, flat files stored on individual desktops and laptops, and modern, cloud-based repositories.). This also diminishes the value of data as an asset. Technical Metadata.

Metadata 132

Metadata Cost-Benefit Measurement Data-driven 132

erwin

SEPTEMBER 10, 2020

Not Documenting End-to-End Data Lineage Is Risky Busines – Understanding your data’s origins is key to successful data governance. Not everyone understands what end-to-end data lineage is or why it is important. Who are the data owners? Five Consequences of Ignoring Data Lineage.

Data Governance 131

Data Governance Key Performance Indicator Metadata Digital Transformation 131

AWS Big Data

FEBRUARY 26, 2025

S3 Tables integration with the AWS Glue Data Catalog is in preview, allowing you to stream, query, and visualize dataincluding Amazon S3 Metadata tablesusing AWS analytics services such as Amazon Data Firehose , Amazon Athena , Amazon Redshift, Amazon EMR, and Amazon QuickSight. With AWS Glue 5.0,

Analytics 61

Analytics Data Lake Metadata Data Warehouse 61

Alation

APRIL 6, 2023

Data governance is traditionally applied to structured data assets that are most often found in databases and information systems. This blog focuses on governing spreadsheets that contain data, information, and metadata, and must themselves be governed. Simply put, metadata adds context.

Data Governance 52

Data Governance Metadata Cost-Benefit Structured Data 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 97

Analytics Data Warehouse Data Lake Metadata 97

AWS Big Data

AUGUST 15, 2024

Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data. The Central IT team implements data governance practices, providing data quality, security, and compliance with established policies.

Data Lake 122

Data Lake Data Warehouse Data Governance Publishing 122

Ontotext

JANUARY 10, 2024

Limiting growth by (data integration) complexity Most operational IT systems in an enterprise have been developed to serve a single business function and they use the simplest possible model for this. In order to integrate structured data, enterprises need to implement the data fabric pattern.

Metadata 72

Metadata Slice and Dice Data Integration Enterprise 72

AWS Big Data

MARCH 26, 2024

In this post, we discuss how you can use purpose-built AWS services to create an end-to-end data strategy for C360 to unify and govern customer data that address these challenges. Then, you transform this data into a concise format. The following screenshot shows an example C360 dashboard built on QuickSight.

Data Strategy 99

Data Strategy Strategy Data Warehouse Prescriptive Analytics 99

Alation

OCTOBER 21, 2021

But, on the back end, data lakes give businesses a common repository to collect and store data, streamlined usage from a single source, and access to the raw data necessary for today’s advanced analytics and artificial intelligence (AI) needs. A frequent and periodic data cleansing strategy is. Lack of metadata.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

AWS Big Data

JUNE 26, 2024

Administrators can customize Amazon DataZone to use existing AWS resources, enabling Amazon DataZone portal users to have federated access to those AWS services to catalog, share, and subscribe to data, thereby establishing data governance across the platform.

Data Lake 119

Data Lake Data Warehouse Unstructured Data Data Governance 119

AWS Big Data

JANUARY 22, 2024

Discussions with users showed they were happier to have faster access to data in a simpler way, a more structured data organization, and a clear mapping of who the producer is. A lot of progress has been made to advance their data-driven culture (data literacy, data sharing, and collaboration across business units).

Data-driven 118

Data-driven Advertising Metadata Data Architecture 118

Octopai

MAY 30, 2019

If the point of Business Intelligence (BI) data governance is to leverage your datasets to support information transparency and decision-making, then it’s fair to say that the data catalog is key for your BI strategy. At least, as far as data analysis is concerned. The Benefits of Structured Data Catalogs.

Metadata 40

Metadata Data Governance Data Lake IoT 40

Ontotext

MARCH 18, 2020

According to an article in Harvard Business Review , cross-industry studies show that, on average, big enterprises actively use less than half of their structured data and sometimes about 1% of their unstructured data. Finally, they combine classical technologies like data governance and data management with modern analytics.

Enterprise 59

Enterprise B2B Unstructured Data Machine Learning 59

Alation

JUNE 2, 2022

In part one of this series, I discussed how data management challenges have evolved and how data governance and security have to play in such challenges, with an eye to cloud migration and drift over time. A data catalog is a central hub for XAI and understanding data and related models. Other Technologies.

Modeling 52

Modeling Data Governance Statistics Unstructured Data 52

Octopai

SEPTEMBER 21, 2020

A crucial part of every company’s business intelligence (BI) is its data dictionary. When you have a well-structured data dictionary, you provide BI teams with an easy way to track and manage metadata throughout the entire enterprise. A data dictionary provides information about and context for your company’s data.

Metadata 52

Metadata Enterprise Structured Data Business Intelligence 52

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

Ontotext

MARCH 8, 2023

Specifically, the increasing amount of data being generated and collected, and the need to make sense of it, and its use in artificial intelligence and machine learning, which can benefit from the structured data and context provided by knowledge graphs. We get this question regularly. million users.

Enterprise 52

Enterprise Knowledge Discovery Risk Machine Learning 52

AWS Big Data

AUGUST 15, 2024

Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data. Amazon DataZone natively supports data sharing for Amazon Redshift data assets. In the post_dq_results_to_datazone.py

Data Quality 111

Data Quality Visualization Metadata Key Performance Indicator 111

erwin

APRIL 18, 2019

Data governance , thankfully, provides a framework for compliance with either or both – in addition to other regulatory mandates your organization may be subject to. Data Governance for Regulatory Compliance. Regulatory compliance remains a key driver for data governance. A Regulatory EDGE.

Data Governance 81

Data Governance Metadata Data Collection Data-driven 81

AWS Big Data

JULY 28, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. It is designed for analyzing large volumes of data and performing complex queries on structured and semi-structured data. Tags provide metadata about resources at a glance.

Snapshot 98

Snapshot Metadata Measurement Data Warehouse 98

O'Reilly on Data

DECEMBER 19, 2018

If you suddenly see unexpected patterns in your social data, that may mean adversaries are attempting to poison your data sources. Anomaly detection may have originated in finance, but it is becoming a part of every data scientist’s toolkit. Tim Kraska on “How machine learning will accelerate data management systems”.

Machine Learning 275

Machine Learning Software Metadata Testing 275

Cloudera

OCTOBER 7, 2021

Those decentralization efforts appeared under different monikers through time, e.g., data marts versus data warehousing implementations (a popular architectural debate in the era of structured data) then enterprise-wide data lakes versus smaller, typically BU-Specific, “data ponds”.

Metadata 124

Metadata Cost-Benefit Enterprise Interactive 124

erwin

AUGUST 31, 2023

Let’s explore the continued relevance of data modeling and its journey through history, challenges faced, adaptations made, and its pivotal role in the new age of data platforms, AI, and democratized data access. In response, modeling evolved to address these challenges.

Data-driven 98

Data-driven Modeling Enterprise Structured Data 98

AWS Big Data

DECEMBER 21, 2023

To ingest the data, smava uses a set of popular third-party customer data platforms complemented by custom scripts. After the data lands in Amazon S3, smava uses the AWS Glue Data Catalog and crawlers to automatically catalog the available data, capture the metadata, and provide an interface that allows querying all data assets.

Data Lake 115

Data Lake Data Warehouse Data-driven B2B 115

BI-Survey

FEBRUARY 27, 2025

However, a closer look reveals that these systems are far more than simple repositories: Data catalogs are at the forefront of bringing AI into your business for at least two reasons. Second, AI governance has become a priority just recently, driven by the sudden ubiquitous surge in (Generative) AI use cases on the one hand.

Unstructured Data 52

Unstructured Data Metadata Data Quality Data Governance 52