Ontotext

MARCH 8, 2023

Use Case #1: Customer 360 / Enterprise 360 Customer data is typically spread across multiple applications, departments, and regions. Each team and system need to keep diverse sets of data about their customers in order to play their specific role – inadvertently leading to siloed experiences. million users.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

IBM Big Data Hub

DECEMBER 16, 2022

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

CIO Business Intelligence

APRIL 29, 2022

This would be straightforward task were it not for the fact that, during the digital-era, there has been an explosion of data – collected and stored everywhere – much of it poorly governed, ill-understood, and irrelevant. Further, data management activities don’t end once the AI model has been developed. Addressing the Challenge.

Data Governance 145

Data Governance IT Risk Data Lake 145

IBM Big Data Hub

JANUARY 5, 2023

Ill-timed business decisions and misinformed business processes, missed revenue opportunities, failed business initiatives and complex data systems can all stem from data quality issues. Several factors determine the quality of your enterprise data like accuracy, completeness, consistency, to name a few.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

Data Virtualization

MARCH 3, 2021

To remain competitive, organizations must have a data management strategy in place to effectively ingest, store, organize, and analyze data while ensuring that it is. The post Data Management Challenges for the Modern Enterprise appeared first on Data Virtualization blog.

Enterprise 75

Enterprise Management Strategy Data Lake 75

AWS Big Data

MARCH 29, 2024

You can slice data by different dimensions like job name, see anomalies, and share reports securely across your organization. With these insights, teams have the visibility to make data integration pipelines more efficient. An AWS Glue crawler scans data on the S3 bucket and populates table metadata on the AWS Glue Data Catalog.

Metrics 106

Metrics Visualization Dashboards Interactive 106

erwin

JANUARY 11, 2019

Organizations have spent a lot of time and money trying to harmonize data across diverse platforms , including cleansing, uploading metadata, converting code, defining business glossaries, tracking data transformations and so on. If you want more control over and more value from all your data, join us for a demo of erwin MM.

Data Governance 40

Data Governance Risk Metadata Management 40

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. Lakehouse (data warehouse and data lake working together) 8.

IT 52

IT Data Lake Strategy Data Science 52

Data Virtualization

MARCH 3, 2021

Data is the fuel of the digital economy, so data-centric organizations have a distinct advantage. To remain competitive, organizations must have a data management strategy in place to effectively ingest, store, organize, and analyze data while ensuring that it is.

Management 59

Management Enterprise Strategy IT 59

Data Virtualization

MARCH 3, 2021

Data is the fuel of the digital economy, so data-centric organizations have a distinct advantage. To remain competitive, organizations must have a data management strategy in place to effectively ingest, store, organize, and analyze data while ensuring that it is.

Management 52

Management Enterprise Strategy IT 52

Domino Data Lab

APRIL 3, 2019

It includes perspectives about current issues, themes, vendors, and products for data governance. My interest in data governance (DG) began with the recent industry surveys by O’Reilly Media about enterprise adoption of “ABC” (AI, Big Data, Cloud). for DG adoption in the enterprise. A brief pictorial history.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

AWS Big Data

NOVEMBER 29, 2023

In 2013, Amazon Web Services revolutionized the data warehousing industry by launching Amazon Redshift , the first fully-managed, petabyte-scale, enterprise-grade cloud data warehouse. Amazon Redshift made it simple and cost-effective to efficiently analyze large volumes of data using existing business intelligence tools.

Data Warehouse 101

Data Warehouse Data Lake Analytics Machine Learning 101

IBM Big Data Hub

APRIL 27, 2022

Data fabric and data mesh are emerging data management concepts that are meant to address the organizational change and complexities of understanding, governing and working with enterprise data in a hybrid multicloud ecosystem. The good news is that both data architecture concepts are complimentary.

Management 80

Management Metadata Data Architecture Data Lake 80

Cloudera

MARCH 23, 2022

By being a truly open table format, Apache Iceberg fits well within the vision of the Cloudera Data Platform (CDP). Let’s highlight some of those benefits, and why choosing CDP and Iceberg can future proof your next generation data architecture. . 4: Enterprise grade. 1: Multi-function analytics . 3: Open Performance.

Metadata 94

Metadata Data Architecture Machine Learning Cost-Benefit 94

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

AWS Big Data

NOVEMBER 29, 2023

Knowledge Bases works with popular vector databases and engines including Amazon OpenSearch Serverless , Redis Enterprise Cloud, and Pinecone, with support for Amazon Aurora and MongoDB coming soon. You also need services to store data for analysis and machine learning (ML) like Amazon Simple Storage Service (Amazon S3).

Data Warehouse 109

Data Warehouse Data Lake Data Integration Dashboards 109

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

FEBRUARY 21, 2023

Loading complex multi-point datasets into a dimensional model, identifying issues, and validating data integrity of the aggregated and merged data points are the biggest challenges that clinical quality management systems face. This is one of the biggest hurdles with the data vault approach. What is a data vault?

Data Warehouse 66

Data Warehouse Data Lake Cost-Benefit Metadata 66

AWS Big Data

MARCH 26, 2024

Data ingestion You have to build ingestion pipelines based on factors like types of data sources (on-premises data stores, files, SaaS applications, third-party data), and flow of data (unbounded streams or batch data). Then, you transform this data into a concise format.

Data Strategy 69

Data Strategy Strategy Data Warehouse Prescriptive Analytics 69

IBM Big Data Hub

OCTOBER 12, 2023

Ensuring compliance with governmental regulatory requirements as well as internal policies An AI model must be fully understood from every angle, inside and out—from what enterprise data is used and when , to how the model arrived at a certain output. Learn more about IBM watsonx 1.

Cost-Benefit 77

Cost-Benefit Metadata Data Governance Modeling 77

Grooper

MARCH 5, 2020

These stewards monitor the input and output of data integrations and workflows to ensure data quality. Their focus is on master data management , data lakes / warehouses, and ensuring the trackability of data using audit trails and metadata. How to Get Started with Information Stewardship.

Data Lake 98

Data Lake Metadata Data Quality Software 98

Ontotext

FEBRUARY 26, 2024

Firstly, on the data maturity spectrum, the vast majority of organizations I’ve spoken with are stuck in the information stage. They have massive amounts of data they’re collecting and storing in their relational databases, document stores, data lakes, and data warehouses. Let’s summarize very quickly.

Technology 52

Technology Cost-Benefit Data-driven Metadata 52

Cloudera

JUNE 6, 2019

The typical Cloudera Enterprise Data Hub Cluster starts with a few dozen nodes in the customer’s datacenter hosting a variety of distributed services. Over time, workloads start processing more data, tenants start onboarding more workloads, and administrators (admins) start onboarding more tenants. Cloudera Manager (CM) 6.2

Metadata 88

Metadata Data Lake Optimization Strategy 88

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.

Data Lake 104

Data Lake Management Metrics Data Warehouse 104

Ontotext

AUGUST 4, 2023

A data fabric utilizes an integrated data layer over existing, discoverable, and inferenced metadata assets to support the design, deployment, and utilization of data across enterprises, including hybrid and multi-cloud platforms. It also helps capture and connect data based on business or domains.

Metadata 52

Metadata Data-driven Data Architecture Data Quality 52

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. The continued federation of data in the enterprise resulted in data silos.

Data-driven 98

Data-driven Modeling Enterprise Structured Data 98

In(tegrate) the Clouds

MAY 1, 2016

SnapLogic published Eight Data Management Requirements for the Enterprise Data Lake. They are: Storage and Data Formats. Metadata and Governance. The company also recently hosted a webinar on Democratizing the Data Lake with Constellation Research and published 2 whitepapers from Mark Madsen.

Data Lake 40

Data Lake Enterprise Management Metadata 40

Cloudera

OCTOBER 7, 2021

In this blog, I will demonstrate the value of Cloudera DataFlow (CDF) , the edge-to-cloud streaming data platform available on the Cloudera Data Platform (CDP) , as a Data integration and Democratization fabric. In the Enterprise Data Management realm, such a data domain is called an Authoritative Data Domain (ADD).

Metadata 127

Metadata Cost-Benefit Enterprise Interactive 127

erwin

JULY 17, 2019

Part Two of the Digital Transformation Journey … In our last blog on driving digital transformation , we explored how enterprise architecture (EA) and business process (BP) modeling are pivotal factors in a viable digital transformation strategy. Analyze metadata – Understand how data relates to the business and what attributes it has.

Digital Transformation 98

Digital Transformation Strategy Metadata Data-driven 98

Cloudera

NOVEMBER 22, 2021

In legacy analytical systems such as enterprise data warehouses, the scalability challenges of a system were primarily associated with computational scalability, i.e., the ability of a data platform to handle larger volumes of data in an agile and cost-efficient way. Introduction. CRM platforms).

Data Processing 97

Data Processing Data Warehouse Enterprise Visualization 97

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. Data mapping helps standardize, visualize, and understand data across different systems and applications.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52