erwin

DECEMBER 12, 2019

Metadata is an important part of data governance, and as a result, most nascent data governance programs are rife with project plans for assessing and documenting metadata. But in many scenarios, it seems that the underlying driver of metadata collection projects is that it’s just something you do for data governance.

Metadata 52

Metadata Data Governance Digital Transformation Data Quality 52

AWS Big Data

APRIL 3, 2024

Apache Iceberg offers integrations with popular data processing frameworks such as Apache Spark, Apache Flink, Apache Hive, Presto, and more. AWS provides integrations for various AWS services with Iceberg tables as well, including AWS Glue Data Catalog for tracking table metadata.

Data Lake 91

Data Lake Snapshot Metadata Data Architecture 91

AWS Big Data

FEBRUARY 29, 2024

However, enterprise data generated from siloed sources combined with the lack of a data integration strategy creates challenges for provisioning the data for generative AI applications. As part of the transformation, the objects need to be treated to ensure data privacy (for example, PII redaction).

Data Governance 91

Data Governance Unstructured Data Metadata Data Lake 91

Ontotext

AUGUST 22, 2023

Poor data management, data silos, and a lack of a common understanding across systems and/or teams are the root cause that prohibits an organization from scaling the business in a dynamic environment. Beyond that, and without a way to visualize, connect, and utilize the data, it’s still just a bunch of random information.

Metadata 52

Metadata Knowledge Discovery Big Data Enterprise 52

CIO Business Intelligence

OCTOBER 26, 2023

Business intelligence (BI) analysts transform data into insights that drive business value. The role is becoming increasingly important as organizations move to capitalize on the volumes of data they collect through business intelligence strategies. What does a business intelligence analyst do?

Business Intelligence 126

Business Intelligence Data-driven Statistics Data Warehouse 126

Cloudera

AUGUST 31, 2021

Cloudera and Accenture demonstrate strength in their relationship with an accelerator called the Smart Data Transition Toolkit for migration of legacy data warehouses into Cloudera Data Platform. Accenture’s Smart Data Transition Toolkit . Are you looking for your data warehouse to support the hybrid multi-cloud?

Data Warehouse 84

Data Warehouse Cost-Benefit Metadata Data-driven 84

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. Creating a High-Quality Data Pipeline.

Data Governance 40

Data Governance Risk Metadata Management 40

IBM Big Data Hub

JANUARY 5, 2023

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases. Reduce data duplication and fragmentation.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

Cloudera

FEBRUARY 11, 2019

The January 2019 “Magic Quadrant for Data Management Solutions for Analytics” provides valuable insights into the status, direction, and players in the DMSA market. All this while the platform serves as the core foundation providing metadata and governance capabilities across these workloads.

Management 43

Management Metadata Analytics Machine Learning 43

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 101

Metrics Visualization Dashboards Interactive 101

IBM Big Data Hub

DECEMBER 16, 2022

For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance. It uses metadata and data management tools to organize all data assets within your organization. Improved trust and confidence in data.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

Alation

DECEMBER 15, 2022

March 2015: Alation emerges from stealth mode to launch the first official data catalog to empower people in enterprises to easily find, understand, govern and use data for informed decision making that supports the business. May 2016: Alation named a Gartner Cool Vendor in their Data Integration and Data Quality, 2016 report.

Metadata 52

Metadata Data Governance Data Quality Marketing 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.

Enterprise 75

Enterprise Management Strategy Data Lake 75

Octopai

JUNE 1, 2020

Data mapping is the cornerstone of many important business intelligence processes: Data Integration – Even if systems are compatible, combining two disparate data repositories still requires meticulous data mapping. Correct data mapping facilitates the creation of usable, searchable data warehouses.

Metadata 52

Metadata Data Warehouse Data Integration Finance 52

erwin

FEBRUARY 19, 2021

Metadata management is key to wringing all the value possible from data assets. However, most organizations don’t use all the data at their disposal to reach deeper conclusions about how to drive revenue, achieve regulatory compliance or accomplish other strategic objectives. What Is Metadata? Harvest data.

Metadata 110

Metadata Management Data Quality Cost-Benefit 110

erwin

APRIL 27, 2022

This award is especially significant because the winning information management solutions are chosen by the people who use them. In data warehousing, the data is extracted and transported from production database(s) into a data warehouse for reporting and analysis. Best Data Modeling Solution (erwin Data Modeler).

Data Governance 52

Data Governance Digital Transformation Metadata Data Warehouse 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

MAY 19, 2023

Reading Time: 11 minutes The post Data Strategies for Getting Greater Business Value from Distributed Data appeared first on Data Management Blog - Data Integration and Modern Data Management Articles, Analysis and Information.

Data Strategy 52

Data Strategy Strategy Data Integration Management 52

Octopai

JUNE 12, 2019

Data mapping is the process of relating fields in one data object (database, flat file, spreadsheet file, or other object containing data) to those in another data object. For instance, in a merger or acquisition , the data from the merged/acquired business might need to be integrated into existing systems. .

Metadata 40

Metadata Data Warehouse Data Integration Software 40

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

Alation

JULY 28, 2022

It’s costly and time-consuming to manage on-premises data warehouses — and modern cloud data architectures can deliver business agility and innovation. However, CIOs declare that agility, innovation, security, adopting new capabilities, and time to value — never cost — are the top drivers for cloud data warehousing.

Data Warehouse 69

Data Warehouse Cost-Benefit Data Governance Data-driven 69

Andrew White

OCTOBER 22, 2021

This time, since we were virtual I only managed to close out the week with the 1-1 summary. Lakehouse (data warehouse and data lake working together) 8. Data Literacy, training, coordination, collaboration 8. Data Management Infrastructure/Data Fabric 5. Data Integration tactics 4.

IT 52

IT Data Lake Strategy Data Science 52

erwin

FEBRUARY 7, 2019

Organization’s cannot hope to make the most out of a data-driven strategy, without at least some degree of metadata-driven automation. The volume and variety of data has snowballed, and so has its velocity. As such, traditional – and mostly manual – processes associated with data management and data governance have broken down.

Metadata 96

Metadata Insurance Data-driven Cost-Benefit 96

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 87

Management Metadata Data Architecture Data Lake 87

Ontotext

MARCH 8, 2023

Rich metadata and semantic modeling continue to drive the matching of 50K training materials to specific curricula, leading new, data-driven, audience-based marketing efforts that demonstrate how the recommender service is achieving increased engagement and performance from over 2.3 million users.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

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. Granted, I’m no expert in DG.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

datapine

MAY 29, 2019

One of the BI architecture components is data warehousing. Organizing, storing, cleaning, and extraction of the data must be carried by a central repository system, namely data warehouse, that is considered as the fundamental component of business intelligence. What Is Data Warehousing And Business Intelligence?

Business Intelligence 196

Business Intelligence Data Warehouse Dashboards Visualization 196

AWS Big Data

AUGUST 31, 2023

Amazon Redshift is a fast, fully managed petabyte-scale cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools. Amazon Redshift also supports querying nested data with complex data types such as struct, array, and map.

Data Lake 89

Data Lake Data Warehouse Metadata Data Architecture 89

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 97

Data Warehouse Data Lake Analytics Machine Learning 97

AWS Big Data

NOVEMBER 22, 2023

Apache Hudi is an open table format that brings database and data warehouse capabilities to data lakes. Apache Hudi helps data engineers manage complex challenges, such as managing continuously evolving datasets with transactions while maintaining query performance.

Data Lake 89

Data Lake Snapshot Metadata Optimization 89

Alation

AUGUST 11, 2022

The data warehouse and analytical data stores moved to the cloud and disaggregated into the data mesh. 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. Architectures became fabrics.

Metadata 52

Metadata Data Warehouse Data Quality Data Lake 52

CIO Business Intelligence

SEPTEMBER 22, 2023

Data management platform definition A data management platform (DMP) is a suite of tools that helps organizations to collect and manage data from a wide array of first-, second-, and third-party sources and to create reports and build customer profiles as part of targeted personalization campaigns.

Management 105

Management Advertising Data Lake Sales 105

AWS Big Data

MARCH 26, 2024

AWS provides different services for building data ingestion pipelines: AWS Glue is a serverless data integration service that ingests data in batches from on-premises databases and data stores in the cloud. Streaming data with low latency needs is stored in Amazon Kinesis Data Streams for real-time consumption.

Data Strategy 66

Data Strategy Strategy Data Warehouse Prescriptive Analytics 66

Alation

JANUARY 17, 2023

It is known to have benefits in handling data due to its robustness, speed, and scalability. A typical modern data stack consists of the following: A data warehouse. Data ingestion/integration services. Data orchestration tools. Today, data integration platforms like Rivery do just that.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Business Intelligence 52

CIO Business Intelligence

JUNE 9, 2022

A data management platform (DMP) is a group of tools designed to help organizations collect and manage data from a wide array of sources and to create reports that help explain what is happening in those data streams. Deploying a DMP can be a great way for companies to navigate a business world dominated by data.

Management 144

Management Advertising Data Lake Sales 144

AWS Big Data

NOVEMBER 29, 2023

These tools also need to be intelligent to remove the heavy lifting from data management. Comprehensive First, you need a comprehensive set of data services so you can get the price/performance, speed, flexibility, and capabilities for any use case. Customers have created hundreds of thousands of data lakes on Amazon S3.

Data Warehouse 109

Data Warehouse Data Lake Data Integration Dashboards 109

DataKitchen

SEPTEMBER 21, 2023

Data in Place refers to the organized structuring and storage of data within a specific storage medium, be it a database, bucket store, files, or other storage platforms. In the contemporary data landscape, data teams commonly utilize data warehouses or lakes to arrange their data into L1, L2, and L3 layers.

Testing 176

Testing Data Quality Predictive Modeling Metrics 176