erwin

MAY 18, 2022

First, erwin Data Intelligence 12.0 delivers new integrated data quality capabilities for customers. Customers then use the erwin Data Quality platform to automate the data discovery, profiling and quality assessment of their data sources. Figure 1: erwin Data Intelligence 12.0

Data Quality 52

Data Quality Metadata Data Governance Software 52

Octopai

JUNE 19, 2023

For business users Data Catalogs offer a number of benefits such as better decision-making; data catalogs provide business users with quick and easy access to high-quality data. This availability of accurate and timely data enables business users to make informed decisions, improving overall business strategies.

Metadata 98

Metadata Data Governance Measurement Risk Management 98

DataKitchen

FEBRUARY 21, 2023

Data Engineering teams often deliver to one or more self-service teams in a hub and spoke or data enablement organization model. This idea sometimes means sh** flows downhill to the data engineer team from self-service teams – your team gets all the blame and none of the glory from delivering business value.

Data-driven 130

Data-driven Testing Risk Cost-Benefit 130

TDAN

AUGUST 15, 2023

I just attended the 17th Annual Chief Data Officer and Information Quality Symposium in July, and there, I heard many creative suggestions for renaming data governance. Calling it data enablement, data trust, data utilization, and many other names to try and avoid the […]

Data Governance 52

Data Governance Data Enablement Data Quality IT 52

InsightOut

FEBRUARY 2, 2024

This is where InsightOut steps in, offering e-commerce companies the tools they need to clean, analyze, and report on key data metrics. Let's explore how InsightOut is leading the way and revolutionizing the way e-commerce businesses leverage data. Pristine Data Cleansing For e-commerce, data quality is non-negotiable.

Key Performance Indicator 40

Key Performance Indicator Metrics Dashboards Reporting 40

IBM Big Data Hub

DECEMBER 7, 2023

Initially, they were designed for handling large volumes of multidimensional data, enabling businesses to perform complex analytical tasks, such as drill-down , roll-up and slice-and-dice. Early OLAP systems were separate, specialized databases with unique data storage structures and query languages.

OLAP 57

OLAP Slice and Dice Cost-Benefit Data Warehouse 57

Alation

JANUARY 26, 2023

Offer the right tools Data stewardship is greatly simplified when the right tools are on hand. So ask yourself, does your steward have the software to spot issues with data quality, for example? 2) Always Remember Compliance Source: Unsplash There are now many different data privacy and security laws worldwide.

Data Governance 52

Data Governance Strategy Data Quality Data Collection 52

Grooper

AUGUST 19, 2019

Choosing the best analytics and BI platform for solving business problems requires non-technical workers to “speak data.”. A baseline understanding of data enables the proper communication required to “be on the same page” with data scientists and engineers. From here on out, I’ll refer to ML and data science as just AI.

Analytics 54

Analytics Machine Learning Data Science Data-driven 54

David Menninger's Analyst Perspectives

OCTOBER 8, 2024

Collibra was founded in 2008 by Chief Executive Officer Felix Van de Maele and Chief Data Citizen Stijn Christiaens. Data intelligence is fundamental to strategic data democratization initiatives to provide data analysts and business users with governed self-service access to data. Regards, Matt Aslett

Data Quality 130

Data Quality Data Governance Enterprise Visualization 130

erwin

JULY 17, 2019

Once you’ve determined what part(s) of your business you’ll be innovating — the next step in a digital transformation strategy is using data to get there. Constructing A Digital Transformation Strategy: Data Enablement. Many organizations prioritize data collection as part of their digital transformation strategy.

Digital Transformation 98

Digital Transformation Strategy Metadata Data-driven 98

DataKitchen

JUNE 24, 2021

In May 2021 at the CDO & Data Leaders Global Summit, DataKitchen sat down with the following data leaders to learn how to use DataOps to drive agility and business value. Kurt Zimmer, Head of Data Engineering for Data Enablement at AstraZeneca. Jim Tyo, Chief Data Officer, Invesco.

Metrics 211

Metrics ROI Measurement Cost-Benefit 211

Alation

NOVEMBER 11, 2021

It’s the one thing that can save data teams from the risk of processing data from their own circular references, as this framework is a credible check-and-balance. Data Sovereignty and Cross?Border International data sharing is essential for many businesses. and simply sharing data across borders is not permitted.

Data Governance 52

Data Governance Data Quality Metrics Metadata 52

Ontotext

AUGUST 4, 2023

After all, when businesses lack domain context, and unified semantics hinder data usage within the organization, a data fabric approach can be a game-changer. Major goals of data fabric include: Create smart semantic data integration and engineering: with governed access to improve findability and comprehensibility of data.

Metadata 52

Metadata Data-driven Data Architecture Data Quality 52

Andrew White

JANUARY 11, 2021

In our modern data and analytics strategy and operating model, a PM methodology plays a key enabling role in delivering solutions. Do you draw a distinction between a data-driven vision and a data-enabled vision, and if so, what is that distinction? where performance and data quality is imperative?

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

CIO Business Intelligence

MARCH 27, 2025

The consequences of getting identity wrong are substantial: Poor data quality = missed insights, operational inefficiencies, and wasted marketing spend. Slow digital adoption = inability to activate customer data reliably at scale. But often, they get stuck because they dont have a unified view of their customers and prospects.

Data Strategy 66

Data Strategy Strategy Digital Transformation Data-driven 66

Jet Global

MAY 9, 2024

A data pipeline is a series of processes that move raw data from one or more sources to one or more destinations, often transforming and processing the data along the way. Data pipelines support data science and business intelligence projects by providing data engineers with high-quality, consistent, and easily accessible data.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

Jet Global

OCTOBER 24, 2023

Why Finance Teams are Struggling with Efficiency in 2023 Disconnected SAP Data Challenges Siloed data poses significant collaboration challenges to your SAP reporting team like reporting delays, limited visibility of data, and poor data quality.

Reporting 52

Reporting Operational Reporting Finance Enterprise 52