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 80

Data Warehouse Cost-Benefit Metadata Data-driven 80

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. Perform data quality monitoring based on pre-configured rules.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

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. Technical metadata to describe schemas, indexes and other database objects.

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

erwin

MAY 2, 2022

This makes mastering basic data modeling techniques and avoiding common pitfalls imperative. This blog outlines a solid foundation for data modeling of online transaction processing (OLTP) systems as they move to the cloud. Other types of databases will be covered in subsequent blogs. What is an entity?

Modeling 98

Modeling Insurance Cost-Benefit Data Warehouse 98

erwin

APRIL 27, 2022

In data warehousing, the data is extracted and transported from production database(s) into a data warehouse for reporting and analysis. Change Data Capture identifies and processes only the data that has changed and stores the changed data in a form so as to be of further use.

Data Governance 52

Data Governance Digital Transformation Metadata Data Warehouse 52

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

Alation

APRIL 14, 2023

Last week, the Alation team had the privilege of joining IT professionals, business leaders, and data analysts and scientists for the Modern Data Stack Conference in San Francisco. Practitioners and hands-on data users were thrilled to be there, and many connected as they shared their progress on their own data stack journeys.

Data Warehouse 52

Data Warehouse Data-driven Digital Transformation Metadata 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. In this blog, we share our takeaways as they relate to the DMSA market trends. 3. Expansion beyond core data management. Cloudera’s Positioning.

Management 42

Management Metadata Analytics Machine Learning 42

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

If you follow my blog for any period of time you will know that for most years I have attended our annual Gartner IT Symposium I do a day-in-the-life blog of an analyst. Lakehouse (data warehouse and data lake working together) 8. Data Literacy, training, coordination, collaboration 8. Metadata Strategy 3.

IT 52

IT Data Lake Strategy Data Science 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

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

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

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 76

Enterprise Management Strategy Data Lake 76

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 92

Data Lake Data Warehouse Metadata Data Architecture 92

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

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 92

Data Lake Snapshot Metadata Optimization 92

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. 11 May 2021. . 3 March 2022.

Management 87

Management Metadata Data Architecture Data Lake 87

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

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 169

Testing Data Quality Predictive Modeling Metrics 169

Alation

JANUARY 17, 2023

The modern data stack is a combination of various software tools used to collect, process, and store data on a well-integrated cloud-based data platform. It is known to have benefits in handling data due to its robustness, speed, and scalability. Data ingestion/integration services. Reverse ETL tools.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

Alation

JANUARY 25, 2022

Data fabric is now on the minds of most data management leaders. In our previous blog, Data Mesh vs. Data Fabric: A Love Story , we defined data fabric and outlined its uses and motivations. The data catalog is a foundational layer of the data fabric. The Power of Social Metadata.

Metadata 52

Metadata IT Metrics Data-driven 52

Alation

JANUARY 13, 2022

Spoiler alert: data fabric and data mesh are independent design concepts that are, in fact, quite complementary. Data fabric has captured most of the limelight; it focuses on the technologies required to support metadata-driven use cases across hybrid and multi-cloud environments. Gartner on Data Fabric.

Data Lake 59

Data Lake Metadata Data-driven Data Governance 59

IBM Big Data Hub

OCTOBER 12, 2023

Among the tasks necessary for internal and external compliance is the ability to report on the metadata of an AI model. Metadata includes details specific to an AI model such as: The AI model’s creation (when it was created, who created it, etc.)

Cost-Benefit 83

Cost-Benefit Metadata Data Governance Modeling 83

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

AWS Big Data

NOVEMBER 29, 2023

dbt is an open source, SQL-first templating engine that allows you to write repeatable and extensible data transforms in Python and SQL. dbt is predominantly used by data warehouses (such as Amazon Redshift ) customers who are looking to keep their data transform logic separate from storage and engine.

Data Lake 102

Data Lake Management Metrics Data Warehouse 102

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

Smart Data Collective

OCTOBER 13, 2021

There is no disputing the fact that the collection and analysis of massive amounts of unstructured data has been a huge breakthrough. This is something that you can learn more about in just about any technology blog. We would like to talk about data visualization and its role in the big data movement.

Visualization 135

Visualization Cost-Benefit Big Data Prescriptive Analytics 135

IBM Big Data Hub

AUGUST 4, 2023

By leveraging data services and APIs, a data fabric can also pull together data from legacy systems, data lakes, data warehouses and SQL databases, providing a holistic view into business performance. It uses knowledge graphs, semantics and AI/ML technology to discover patterns in various types of metadata.

Data Architecture 64

Data Architecture Data Lake Machine Learning Data Governance 64

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.

Data Processing 89

Data Processing Data Warehouse Enterprise Visualization 89