CIO Business Intelligence

APRIL 27, 2022

All are ideally qualified to help their customers achieve and maintain the highest standards for data integrity, including absolute control over data access, transparency and visibility into the provider’s operation, the knowledge that their information is managed appropriately, and access to VMware’s growing ecosystem of sovereign cloud solutions.

Digital Transformation 108

Digital Transformation Metadata Risk Management 108

IBM Big Data Hub

JANUARY 9, 2024

Data ingestion must be done properly from the start, as mishandling it can lead to a host of new issues. The groundwork of training data in an AI model is comparable to piloting an airplane. The entire generative AI pipeline hinges on the data pipelines that empower it, making it imperative to take the correct precautions.

Enterprise 81

Enterprise Data Integration Data Quality Contextual Data 81

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

CIO Business Intelligence

MARCH 6, 2024

SAP announced today a host of new AI copilot and AI governance features for SAP Datasphere and SAP Analytics Cloud (SAC). The company is expanding its partnership with Collibra to integrate Collibra’s AI Governance platform with SAP data assets to facilitate data governance for non-SAP data assets in customer environments. “We

Unstructured Data 115

Unstructured Data Dashboards Business Intelligence Data Governance 115

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

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.

Metadata 85

Metadata Data Lake Optimization Strategy 85

Alation

JANUARY 17, 2023

What if, experts asked, you could load raw data into a warehouse, and then empower people to transform it for their own unique needs? Today, data integration platforms like Rivery do just that. By pushing the T to the last step in the process, such products have revolutionized how data is understood and analyzed.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

Andrew White

JANUARY 9, 2022

On Thursday January 6th I hosted Gartner’s 2022 Leadership Vision for Data and Analytics webinar. But I would search on our web site for AI and mid-size enterprise; or ask Anthony Mullen who leads our AI research in our data and analytics team. A data fabric that can’t read or capture data would not work.

Analytics 64

Analytics Measurement Modeling Data-driven 64

Octopai

NOVEMBER 13, 2022

Users of modern data stacks could use some X-ray vision to see inside the different components of the data stack and shed some light on its pieces, processes and the data flowing through it. It’s called enterprise data lineage. What enterprise data lineage lets you see.

Enterprise 77

Enterprise Data Warehouse Reporting Metadata 77

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 122

Metadata Cost-Benefit Enterprise Interactive 122

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

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 89

Data Processing Data Warehouse Enterprise Visualization 89

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

Jet Global

MAY 1, 2023

Traditional BI Platforms Traditional BI platforms are centrally managed, enterprise-class platforms. These sit on top of data warehouses that are strictly governed by IT departments. The role of traditional BI platforms is to collect data from various business systems. addresses). Do what you expect your customers to do.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52