Andrew White

OCTOBER 22, 2021

Monetization/Link data to outcome (value pyramid) business value of data/business impact 20. Business Information Model/Arch compared to classic enterprise data model and how to relate it to catalogs and marketplaces and enterprise data models 13. Data Management Infrastructure/Data Fabric 5.

IT 52

IT Data Lake Strategy Data Science 52

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 74

Metadata Data Lake Data Processing Data-driven 74

Cloudera

JANUARY 15, 2021

Cloudera Data Warehouse is a highly scalable service that marries the SQL engine technologies of Apache Impala and Apache Hive with cloud-native features to deliver best-in-class price-performance for users running data warehousing workloads in the cloud. Remote read optimizations: IMPALA-8341: Data cache for remote reads.

Data Warehouse 92

Data Warehouse Cost-Benefit Consulting Interactive 92

AWS Big Data

OCTOBER 4, 2023

An Amazon DataZone domain contains an associated business data catalog for search and discovery, a set of metadata definitions to decorate the data assets that are used for discovery purposes, and data projects with integrated analytics and ML tools for users and groups to consume and publish data assets.

Metadata 100

Metadata Data Lake Publishing Data Governance 100

Domino Data Lab

APRIL 3, 2019

Data governance shows up as the fourth-most-popular kind of solution that enterprise teams were adopting or evaluating during 2019. That’s a lot of priorities – especially when you group together closely related items such as data lineage and metadata management which rank nearby. in lieu of simply landing in a data lake.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

IBM Big Data Hub

JANUARY 18, 2023

In another decade, the internet and mobile started the generate data of unforeseen volume, variety and velocity. It required a different data platform solution. Hence, Data Lake emerged, which handles unstructured and structured data with huge volume. Data lakehouse was created to solve these problems.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

IBM Big Data Hub

APRIL 27, 2022

Gartner defines a data fabric as “a design concept that serves as an integrated layer of data and connecting processes. The data fabric architectural approach can simplify data access in an organization and facilitate self-service data consumption at scale.

Management 87

Management Metadata Data Architecture Data Lake 87

Ontotext

FEBRUARY 12, 2024

In a centralized architecture, data is copied from source systems into a data lake or data warehouse to create a single source of truth serving analytics use cases. This quickly becomes difficult to scale with data discovery and data version issues, schema evolution, tight coupling, and a lack of semantic metadata.

IT 64

IT Metadata Data Quality Data Lake 64

Alation

APRIL 6, 2023

Other forms of governance address specific sets or domains of data including information governance (for unstructured data), metadata governance (for data documentation), and domain-specific data (master, customer, product, etc.). Data catalogs and spreadsheets are related in many ways.

Data Governance 52

Data Governance Metadata Cost-Benefit Structured Data 52

DataKitchen

OCTOBER 11, 2021

Figure 2: Example data pipeline with DataOps automation. In this project, I automated data extraction from SFTP, the public websites, and the email attachments. The automated orchestration published the data to an AWS S3 Data Lake. Monitoring Job Metadata.

Testing 152

Testing Metadata Dashboards Statistics 152

IBM Big Data Hub

MAY 9, 2023

The answer is that generative AI leverages recent advances in foundation models. Unlike traditional ML, where each new use case requires a new model to be designed and built using specific data, foundation models are trained on large amounts of unlabeled data, which can then be adapted to new scenarios and business applications.

Data Warehouse 109

Data Warehouse Cost-Benefit Machine Learning Modeling 109

Cloudera

APRIL 22, 2021

Storage plays one of the most important roles in the data platforms strategy, it provides the basis for all compute engines and applications to be built on top of it. Businesses are also looking to move to a scale-out storage model that provides dense storages along with reliability, scalability, and performance.

Data Lake 98

Data Lake Cost-Benefit Testing Metadata 98

IBM Big Data Hub

JULY 17, 2023

is our enterprise-ready next-generation studio for AI builders, bringing together traditional machine learning (ML) and new generative AI capabilities powered by foundation models. With watsonx.ai, businesses can effectively train, validate, tune and deploy AI models with confidence and at scale across their enterprise. IBM watsonx.ai

Machine Learning 67

Machine Learning Data Warehouse Modeling Cost-Benefit 67

Domino Data Lab

AUGUST 8, 2019

Across the board, organizations struggle with hiring enough data scientists. Meanwhile, many organizations also struggle with “late in the pipeline issues” on model deployment in production and related compliance. then building machine learning models to recommend methods and potential collaborators to scientists.

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

AWS Big Data

FEBRUARY 2, 2023

Since its launch in 2006, Amazon Simple Storage Service (Amazon S3) has experienced major growth, supporting multiple use cases such as hosting websites, creating data lakes, serving as object storage for consumer applications, storing logs, and archiving data. This could be your data lake or application S3 bucket.

Reporting 84

Reporting Data Lake Management Optimization 84

Alation

JUNE 21, 2022

Why start with a data source and build a visualization, if you can just find a visualization that already exists, complete with metadata about it? Data scientists went beyond database tables to data lakes and cloud data stores. Data scientists want to catalog not just information sources, but models.

Metadata 52

Metadata Data Quality Visualization Data Lake 52

Cloudera

JUNE 4, 2018

Unstructured content lacks a predefined data model; it must first undergo text extraction, classification, and enrichment to provide intelligence. the client needed an approach to: Simplify data hub ingestion, especially for large volumes of unstructured content. How can they tackle this challenge? compliance reporting.

Unstructured Data 45

Unstructured Data Metadata Big Data Enterprise 45

AWS Big Data

NOVEMBER 29, 2023

We have seen a strong customer demand to expand its scope to cloud-based data lakes because data lakes are increasingly the enterprise solution for large-scale data initiatives due to their power and capabilities. The team uses dbt-glue to build a transformed gold model optimized for business intelligence (BI).

Data Lake 102

Data Lake Management Metrics Data Warehouse 102

erwin

AUGUST 31, 2023

Q: Is data modeling cool again? In today’s fast-paced digital landscape, data reigns supreme. The data-driven enterprise relies on accurate, accessible, and actionable information to make strategic decisions and drive innovation. A: It always was and is getting cooler!!

Data-driven 98

Data-driven Modeling Enterprise Structured Data 98

AWS Big Data

MAY 1, 2024

Solution overview OneData defines three personas: Publisher – This role includes the organizational and management team of systems that serve as data sources. Responsibilities include: Load raw data from the data source system at the appropriate frequency. This enables high-quality data available to each consumer.

Dashboards 111

Dashboards Data-driven Publishing Cost-Benefit 111

Cloudera

OCTOBER 7, 2021

The need for a decentralized data mesh architecture stems from the challenges organizations faced when implementing more centralized data management architectures – challenges that can attributed to both technology (e.g., need to integrate multiple “point solutions” used in a data ecosystem) and organization reasons (e.g.,

Metadata 122

Metadata Cost-Benefit Enterprise Interactive 122

AWS Big Data

JULY 14, 2023

This enabled producers to publish data products that were curated and authoritative assets for their domain. For example, the AR team created and governed their cash application dataset in their AWS account AWS Glue Data Catalog. Data source locations are registered with Lake Formation.

Finance 80

Finance Metadata Big Data Recreation/Entertainment 80

Andrew White

JANUARY 11, 2021

This was for the Chief Data Officer, or head of data and analytics. Gartner also published the same piece of research for other roles, such as Application and Software Engineering. Where does the Data Architect role fits in the Operational Model ? This would be part of a Data Literacy program. Fusion teams.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

Jet Global

FEBRUARY 23, 2024

Data mapping is essential for integration, migration, and transformation of different data sets; it allows you to improve your data quality by preventing duplications and redundancies in your data fields. Source-to-target mapping integration tasks vary in complexity, depending on data hierarchy and structure.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

Jet Global

SEPTEMBER 19, 2023

What are the best practices for analyzing cloud ERP data? Data Management How do we create a data warehouse or data lake in the cloud using our cloud ERP? How do I access the legacy data from my previous ERP? Self-service BI How can we rapidly build BI reports on cloud ERP data without any help from IT?

Cost-Benefit 52

Cost-Benefit Data Warehouse Reporting Enterprise 52