TDAN

APRIL 30, 2019

Data collection is getting more dispersed and voluminous every day. Enterprises create and collect information from a variety of data sources which may include websites, mobile devices, customers, vendors, and other numerous sources.

Management 69

Management Data Collection Enterprise Data Governance 69

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

Alation

FEBRUARY 8, 2022

Middlemen — data engineering or IT teams — can’t possibly possess all the expertise needed to serve up quality data to the growing range of data consumers who need it. As data collection has surged, and demands for data have grown in the enterprise, one single team can no longer meet the data demands of every department.

Data Governance 52

Data Governance Data-driven Metadata Enterprise 52

Alation

FEBRUARY 20, 2020

With an on-premise deployment, enterprises have full control over data security, data access, and data governance. earthquake, flood, or fire), where the data collected does not need to be as tightly controlled. The Alation Data Catalog will automatically crawl and catalog metadata in your S3 bucket(s).

Data Lake 52

Data Lake ROI Metadata Cost-Benefit 52

Alation

JANUARY 17, 2023

In this article, I will explain the modern data stack in detail, list some benefits, and discuss what the future holds. What Is the Modern Data Stack? 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.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

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

Rocket-Powered Data Science

MARCH 20, 2023

We live in a data-rich, insights-rich, and content-rich world. Data collections are the ones and zeroes that encode the actionable insights (patterns, trends, relationships) that we seek to extract from our data through machine learning and data science. Source: [link] I will finish with three quotes.

Data Warehouse 325

Data Warehouse Metadata Digital Transformation Unstructured Data 325

IBM Big Data Hub

AUGUST 4, 2023

When workers get their hands on the right data, it not only gives them what they need to solve problems, but also prompts them to ask, “What else can I do with data?” ” through a truly data literate organization. What is data democratization?

Data Architecture 63

Data Architecture Data Lake Machine Learning Data Governance 63

Alation

SEPTEMBER 1, 2022

What’s worse, those best equipped to help are too busy: 55% of respondents stated that, “the few available data experts with business domain expertise have neither the time for nor the inclination to prioritize this task.”. Get the new IDC Marketscape for Data Catalogs to learn more. What goes into a Data Intelligence Platform?

Reporting 52

Reporting Metadata Data Governance Interactive 52

Alation

AUGUST 2, 2022

Legacy technologies, siloed data, and manual processes make securing data and protecting privacy much more expensive and risky. After investing to develop these critical customer insights, a security breach can quickly damage trust and compromise the value of that data. Data discovery was conducted 67% times faster.

Strategy 52

Strategy Cost-Benefit Metrics Data Lake 52