erwin

MARCH 21, 2019

As part of a data governance strategy, a BPM tool aids organizations in visualizing their business processes, system interactions and organizational hierarchies to ensure elements are aligned and core operations are optimized. The lack of a central metadata repository is a far too common thorn in an organization’s side.

Modeling 75

Modeling Metadata Data Governance IT 75

AWS Big Data

NOVEMBER 15, 2023

As the organization receives data from multiple external vendors, it often arrives in different formats, typically Excel or CSV files, with each vendor using their own unique data layout and structure. DataBrew is an excellent tool for data quality and preprocessing. Choose Create project.

Metadata 115

Metadata Sales Data Lake Big Data 115

AWS Big Data

MARCH 26, 2024

Customer 360 (C360) provides a complete and unified view of a customer’s interactions and behavior across all touchpoints and channels. This view is used to identify patterns and trends in customer behavior, which can inform data-driven decisions to improve business outcomes. Then, you transform this data into a concise format.

Data Strategy 100

Data Strategy Strategy Data Warehouse Prescriptive Analytics 100

AWS Big Data

FEBRUARY 1, 2023

This introduces the need for both polling and pushing the data to access and analyze in near-real time. From an operational standpoint, we designed a new shared responsibility model for data ingestion using AWS Glue instead of internal services (REST APIs) designed on Amazon EC2 to extract the data.

Optimization 52

Optimization Forecasting Data Lake Metadata 52

Cloudera

JULY 20, 2021

So relying upon the past for future insights with data that is outdated due to changing customer preferences, the hyper-competitive world and emphasis on environment, society and governance produces non-relevant insights and sub-optimized returns. Quality data needs to be the normalizing factor.

Manufacturing 106

Manufacturing Forecasting IoT Insurance 106

AWS Big Data

MARCH 7, 2023

Flexible and easy to use – The solutions should provide less restrictive, easy-to-access, and ready-to-use data. They should also provide optimal performance with low or no tuning. The source data is usually in either structured or semi-structured formats, which are highly and loosely formatted, respectively.

Analytics 97

Analytics Data Warehouse Data Lake Metadata 97

Cloudera

APRIL 1, 2024

We scored the highest in hybrid, intercloud, and multi-cloud capabilities because we are the only vendor in the market with a true hybrid data platform that can run on any cloud including private cloud to deliver a seamless, unified experience for all data, wherever it lies.

Unstructured Data 105

Unstructured Data Cost-Benefit Metadata Machine Learning 105

AWS Big Data

JUNE 14, 2023

This dashboard helps our operations team and end customers improve the data quality of key attribution and reduce manual intervention. This framework can be described as follows: Findable – Metadata and data should be easy to find for both humans and computers.

Dashboards 104

Dashboards KPI Scorecard Metadata 104

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

MARCH 17, 2021

According to the Forrester Wave: Machine Learning Data Catalogs, Q4 2020 , “Alation exploits machine learning at every opportunity to improve data management, governance, and consumption by analytic citizens. MLDCs improve upon traditional metadata management systems by injecting intelligence. Tracking and Scaling Data Lineage.

Machine Learning 52

Machine Learning Metadata Data Governance Data Quality 52

AWS Big Data

NOVEMBER 16, 2023

Performance It is not uncommon for sub-second SLAs to be associated with data vault queries, particularly when interacting with the business vault and the data marts sitting atop the business vault. String-optimized compression The Data Vault 2.0 Support of transactional data lake frameworks Data Vault 2.0

Enterprise 111

Enterprise Data Warehouse Snapshot Cost-Benefit 111

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.” Yet finding data is just the beginning.

Metadata 64

Metadata Data Governance Dashboards Software 64

Jet Global

JULY 2, 2019

For example, Azure Data Lake includes all the capabilities required to make it easy for developers, data scientists, and analysts to store data of any size, shape, and speed—and do all types of processing and analytics across platforms and languages. Future-Proofing your Data.

Data Lake 73

Data Lake Data Warehouse Big Data Machine Learning 73

Ontotext

DECEMBER 1, 2023

Atanas Kiryakov presenting at KGF 2023 about Where Shall and Enterprise Start their Knowledge Graph Journey Only data integration through semantic metadata can drive business efficiency as “it’s the glue that turns knowledge graphs into hubs of metadata and content”.

Metadata 78

Metadata Sales Machine Learning Consulting 78

Octopai

AUGUST 11, 2024

Just as a navigation app provides a detailed map of roads, guiding you from your starting point to your destination while highlighting every turn and intersection, data flow lineage offers a comprehensive view of data movement and transformations throughout its lifecycle. Open Source Data Lineage Tools 1.

Metadata 40

Metadata Visualization Data Quality Data Governance 40

AWS Big Data

AUGUST 14, 2023

Earlier in their lifecycle, data products may be measured by alternative metrics, including adoption (number of consumers) and level of activity (releases, interaction with consumers, and so on). Legal & Compliance C Legal & Compliance Officer Consults on permissibility of data products with reference to local regulation.

Management 98

Management Risk Measurement Optimization 98

Alation

AUGUST 20, 2021

In this way, data lineage is a powerful tool for understanding. Knowing the data lineage helps you find the source of errors, determine the data’s suitability for usage, understand how processes can be optimized or improved, speed the time to insights, and much more. Why is Data Lineage Important? Was it updated?

Metadata 52

Metadata Data Quality Data Governance Data-driven 52

AWS Big Data

FEBRUARY 13, 2023

To assess the nodes and find an optimal RA3 cluster configuration, we collaborated with AllCloud , the AWS premier consulting partner. A set of queries from the production cluster – This set can be reconstructed from the Amazon Redshift logs ( STL_QUERYTEXT ) and enriched by metadata ( STL_QUERY ).

Snapshot 95

Snapshot Data Warehouse Analytics Testing 95

AWS Big Data

JUNE 12, 2023

Therefore, it’s crucial to keep the schema definition in the Schema Registry and the Data Catalog table in sync. To avoid this, it’s recommended to use a data quality check mechanism to identify such anomalies and take appropriate action in case of unexpected behavior. The following diagram illustrates our solution architecture.

Management 98

Management Metadata Internet of Things Testing 98

IBM Big Data Hub

AUGUST 4, 2023

Architecture for data democratization Data democratization requires a move away from traditional “data at rest” architecture, which is meant for storing static data. Traditionally, data was seen as information to be put on reserve, only called upon during customer interactions or executing a program.

Data Architecture 59

Data Architecture Data Lake Machine Learning Data Governance 59

Ontotext

JULY 6, 2023

This shift of both a technical and an outcome mindset allows them to establish a centralized metadata hub for their data assets and effortlessly access information from diverse systems that previously had limited interaction. There are four groups of data that are naturally siloed: Structured data (e.g.,

Cost-Benefit 52

Cost-Benefit Metadata Experimentation Risk 52

Ontotext

MARCH 8, 2023

Here, I will draw upon our own experience from client projects and lessons learned to provide a selection of optimal use cases for knowledge graphs and semantic solutions along with real world examples of their applications. For many organizations, however, the question remains, “Is it the right solution for us?” million users.

Enterprise 52

Enterprise Knowledge Discovery Risk Machine Learning 52

Andrew White

JANUARY 11, 2021

For a time, I believed simulation was more useful a capability than optimization, at the time that larger firms were seeking optimization solutions. where performance and data quality is imperative? We cannot of course forget metadata management tools, of which there are many different. Do you play SimCity?

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

O'Reilly on Data

JULY 28, 2020

If this sounds fanciful, it’s not hard to find AI systems that took inappropriate actions because they optimized a poorly thought-out metric. CTRs are easy to measure, but if you build a system designed to optimize these kinds of metrics, you might find that the system sacrifices actual usefulness and user satisfaction.

Marketing 364

Marketing Experimentation Metrics Testing 364

Domino Data Lab

JULY 22, 2019

By virtue of that, if you take those log files of customers interactions, you aggregate them, then you take that aggregated data, run machine learning models on them, you can produce data products that you feed back into your web apps, and then you get this kind of effect in business. You know what?

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

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 Visualization 52

David Menninger's Analyst Perspectives

JANUARY 9, 2025

Business software providers are already incorporating data stores on applications and platforms optimized for specific users and use cases. We refer to this somewhat tongue-in-cheek as a data pantry. By automating the collection of data, reports and dashboards can be timelier.

Finance 130

Finance Forecasting Data Warehouse Interactive 130

AWS Big Data

DECEMBER 19, 2024

As data lakes increasingly handle sensitive business data and transactional workloads, maintaining strong data quality, governance, and compliance becomes vital to maintaining trust and regulatory alignment. With this new feature, as you enable the Data Catalog optimizer.

Data Lake 98

Data Lake IoT Metadata Testing 98

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. However, lineage information and comprehensive metadata are also crucial to document and assess AI models holistically in the domain of AI governance.

Unstructured Data 52

Unstructured Data Metadata Data Quality Data Governance 52

CIO Business Intelligence

MAY 14, 2025

The collision of traditional EA with cognitive-driven data architectures Enterprise architecture has a storied history of providing organizations with a structured methodology for aligning IT systems with business goals, focusing on standardized business processes, data governance and technology stacks. On-demand data access.

Enterprise 59

Enterprise Data Architecture Data-driven Data Quality 59

AWS Big Data

APRIL 29, 2025

At the BMW Group, our Cloud Efficiency Analytics (CLEA) team has developed a FinOps solution to optimize costs across over 10,000 cloud accounts. While enabling organization-wide efficiency, the team also applied these principles to the data architecture, making sure that CLEA itself operates frugally.

Data Transformation 54

Data Transformation Cost-Benefit Testing Data Lake 54

BI-Survey

FEBRUARY 6, 2020

Modernizing and optimizing enterprise reporting – or classical BI – has not been such a priority for many of today’s organizations, even though it constitutes the backbone of information supply for decision support. Data management has always been a challenge for companies. Modernize data management to guarantee high data quality.

Reporting 59

Reporting Optimization Enterprise Data Quality 59

CIO Business Intelligence

MAY 6, 2025

This is where we blend optimization engines, business rules, AI and contextual data to recommend or automate the best possible action. Think of the next-best-offer algorithms in e-commerce, dynamic hospitality pricing or logistics route optimization. What do data quality issues look like in the real world?

Prescriptive Analytics 78

Prescriptive Analytics Predictive Analytics Descriptive Analytics ROI 78