Alation

JUNE 14, 2021

Indeed, automation is a key element to data catalog features, which enhance data security. Selecting a Data Catalog. To support data security, an effective data catalog should have features, like a business glossary, wiki-like articles, and metadata management. And, finding data is only half the battle.

Data Governance 97

Data Governance Recreation/Entertainment Data Lake Digital Transformation 97

Ontotext

MARCH 8, 2023

Solution Outcomes: A semantic recommendation service that is beating accuracy benchmarks and replacing manual processes aggregating content – that is supporting higher-quality, more advanced, and targeted recommendations with clear reasons. million users. A risk issue in one financial institution could result in a domino effect for many.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

AWS Big Data

MARCH 1, 2024

One of the bank’s key challenges related to strict cybersecurity requirements is to implement field level encryption for personally identifiable information (PII), Payment Card Industry (PCI), and data that is classified as high privacy risk (HPR). Only users with required permissions are allowed to access data in clear text.

Data Lake 95

Data Lake Data Warehouse Management Risk 95

DataKitchen

OCTOBER 11, 2021

First, you must understand the existing challenges of the data team, including the data architecture and end-to-end toolchain. Second, you must establish a definition of “done.” In DataOps, the definition of done includes more than just some working code. Definition of Done. Monitoring Job Metadata.

Testing 157

Testing Metadata Dashboards Statistics 157

Alation

JANUARY 13, 2022

Thoughtworks says data mesh is key to moving beyond a monolithic data lake. Spoiler alert: data fabric and data mesh are independent design concepts that are, in fact, quite complementary. Thoughtworks says data mesh is key to moving beyond a monolithic data lake 2. Gartner on Data Fabric.

Data Lake 59

Data Lake Metadata Data-driven Data Governance 59

Alation

AUGUST 11, 2022

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. We chatted about industry trends, why decentralization has become a hot topic in the data world, and how metadata drives many data-centric use cases.

Metadata 52

Metadata Data Warehouse Data Quality Data Lake 52

AWS Big Data

DECEMBER 18, 2023

Solution overview One of the common functionalities involved in data pipelines is extracting data from multiple data sources and exporting it to a data lake or synchronizing the data to another database. There are multiple tables related to customers and order data in the RDS database.

Metadata 117

Metadata Visualization Data Lake Data-driven 117

AWS Big Data

JUNE 12, 2023

It’s important to note that the schema in the Data Catalog table serves as the source of truth for the AWS Glue streaming job. Therefore, it’s crucial to keep the schema definition in the Schema Registry and the Data Catalog table in sync. Upon success, update the AWS Glue Data Catalog table using the updated schema.

Management 75

Management Metadata Testing Internet of Things 75

Alation

MARCH 21, 2023

When it embarked on a digital transformation and modernization initiative in 2018, the company migrated all its data to AWS S3 Data Lake and Snowflake Data Cloud to provide accessibility to data to all users. Using Alation, ARC automated the data curation and cataloging process. “So

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

erwin

AUGUST 31, 2023

It delivers the ability to capture and unify the business and technical perspectives of data assets, enables effective collaboration between a variety of stakeholders, and delivers metadata-driven automation to accelerate the creation and maintenance of data sources on virtually any data management platform.

Data-driven 98

Data-driven Modeling Enterprise Structured Data 98

Alation

FEBRUARY 17, 2023

Reichental describes data governance as the overarching layer that empowers people to manage data well ; as such, it is focused on roles & responsibilities, policies, definitions, metrics, and the lifecycle of the data. In this way, data governance is the business or process side.

Data Governance 52

Data Governance Data Quality Metadata Cost-Benefit 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

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