O'Reilly on Data

JULY 28, 2020

It’s often difficult for businesses without a mature data or machine learning practice to define and agree on metrics. Some machine learning approaches (and many software engineering practices) are simply not appropriate for near-real time applications. Data Quality and Standardization.

Marketing 362

Marketing Experimentation Metrics Testing 362

CIO Business Intelligence

MARCH 29, 2022

It isn’t practical to save all your data, but it is important to realize data may be valuable for other projects. You lose that add-on value when you throw data away. . This type of data waste results in missing out on the second project advantage. And the problem is not just a matter of too many copies of data.

Cost-Benefit 52

Cost-Benefit Machine Learning Metadata Data Quality 52

erwin

JUNE 11, 2020

Transforming Industries with Data Intelligence. Data intelligence has provided useful and insightful information to numerous markets and industries. With tools such as Artificial Intelligence, Machine Learning, and Data Mining, businesses and organizations can collate and analyze large amounts of data reliably and more efficiently.

Key Performance Indicator 103

Key Performance Indicator KPI Data-driven Machine Learning 103

Domino Data Lab

JULY 22, 2019

data science’s emergence as an interdisciplinary field – from industry, not academia. why data governance, in the context of machine learning is no longer a “dry topic” and how the WSJ’s “global reckoning on data governance” is potentially connected to “premiums on leveraging data science teams for novel business cases”.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Cloudera

OCTOBER 1, 2022

While the word “data” has been common since the 1940s, managing data’s growth, current use, and regulation is a relatively new frontier. . Governments and enterprises are working hard today to figure out the structures and regulations needed around data collection and use.

Data Governance 73

Data Governance Strategy Enterprise Machine Learning 73

Alation

FEBRUARY 13, 2020

A modern data catalog includes many features and functions that all depend on the core capability of cataloging data—collecting the metadata that identifies and describes the inventory of shareable data. Benefits of a Data Catalog. Improved data efficiency. Improved data context.

Metadata 64

Metadata Data Lake Recreation/Entertainment Big Data 64

Cloudera

FEBRUARY 14, 2018

operations, and our CISO’s team while we invest in and form a stronger data and analytics team. Think about it – we have the top experts in the world in this company – experts at identifying use cases, building out clusters, ingesting data, and helping our customers with advanced analytics and machine learning.

Data-driven 43

Data-driven Data Quality Risk Interactive 43

Alation

MAY 16, 2023

This makes it easier to compare and contrast information and provides organizations with a unified view of their data. Machine Learning Data pipelines feed all the necessary data into machine learning algorithms, thereby making this branch of Artificial Intelligence (AI) possible.

Data Lake 69

Data Lake Data Governance Data Warehouse Data Processing 69

Alation

MAY 16, 2023

This makes it easier to compare and contrast information and provides organizations with a unified view of their data. Machine Learning Data pipelines feed all the necessary data into machine learning algorithms, thereby making this branch of Artificial Intelligence (AI) possible.

Data Lake 40

Data Lake Data Governance Data Warehouse Data Processing 40

CIO Business Intelligence

NOVEMBER 28, 2023

“By recognizing milestones, leaders give other stakeholders visibility into the progress being made, and also ensure that their team members feel appreciated for the level of effort they are putting in to make unstructured data actionable.” Quality is job one. Another key to success is to prioritize data quality.

Unstructured Data 130

Unstructured Data Data-driven Visualization Data Quality 130

Alation

DECEMBER 15, 2021

Yet high-volume collection makes keeping that foundation sound a challenge, as the amount of data collected by businesses is greater than ever before. An effective data governance strategy is critical for unlocking the full benefits of this information. Data governance requires a system.

Data Governance 52

Data Governance Strategy Metadata Data Strategy 52

Alation

MARCH 17, 2021

Key Features of a Machine Learning Data Catalog. Data intelligence is crucial for the development of data catalogs. At the center of this innovation are machine learning data catalogs (MLDCs). Unlike standalone tools, machine learning data catalogs have features like: Data search.

Machine Learning 52

Machine Learning Metadata Data Governance Interactive 52

Alation

MARCH 5, 2021

Data governance defines how data should be gathered and used within an organization. It address core questions, such as: How does the business define data? How accurate must the data be for use? Organizations have much to gain from learning about and implementing a data governance framework.

Data Governance 59

Data Governance Data Quality Dashboards Risk 59

Alation

JULY 6, 2021

Common Data Governance Challenges. Every enterprise runs into data governance challenges eventually. Issues like data visibility, quality, and security are common and complex. Data governance is often introduced as a potential solution. And one enterprise alone can generate a world of data.

Data Governance 52

Data Governance Metadata Data Quality Risk 52

IBM Big Data Hub

AUGUST 4, 2023

Data democratization instead refers to the simplification of all processes related to data, from storage architecture to data management to data security. It also requires an organization-wide data governance approach, from adopting new types of employee training to creating new policies for data storage.

Data Architecture 65

Data Architecture Data Lake Machine Learning Data Governance 65

Alation

AUGUST 26, 2021

It asks much larger questions, which flesh out an organization’s relationship with data: Why do we have data? Why keep data at all? Answering these questions can improve operational efficiencies and inform a number of data intelligence use cases, which include data governance, self-service analytics, and more.

Metadata 64

Metadata Data Governance Dashboards Software 64

Alation

OCTOBER 12, 2021

Nowadays, machine learning , AI, and augmented reality analytics are speeding up this process, so that collection and analysis are always on. Folks can work faster, and with more agility, unearthing insights from their data instantly to stay competitive. Implementing adaptive, active data governance.

Strategy 52

Strategy Enterprise Analytics Data Governance 52