Business Leaders Make the Case for Data Science
Dataiku
MAY 20, 2024
Led by Conor Jensen of Dataiku, a panel of esteemed industry leaders discussed the case for strong data science foundations in their respective spaces.
Dataiku
MAY 20, 2024
Led by Conor Jensen of Dataiku, a panel of esteemed industry leaders discussed the case for strong data science foundations in their respective spaces.
DataKitchen
AUGUST 13, 2021
– Kurt Zimmer, AstraZeneca, Head of Data Engineering inside Data Enablement (CDO Summit 2021). Meta-orchestration is problematic for some because it requires an orchestration tool to connect seamlessly with data professionals’ vast ecosystem of tools.
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
DataKitchen
FEBRUARY 2, 2023
Central IT Data Teams focus on standards, compliance, and cost reduction. ’ They are data enabling vs. value delivery. Their software purchase behavior will align with enabling standards for line-of-business data teams who use various tools that act on data. Recession: the party is over.
CIO Business Intelligence
DECEMBER 20, 2024
Data architectures should integrate with legacy applications using standard API interfaces. They should also be optimized to share data across systems, geographies, and organizations. Real-time data enablement. Be decoupled and extensible.
Rocket-Powered Data Science
SEPTEMBER 18, 2018
In “data science language”, what we are describing are different segments (clusters) in the hyperspace of symptoms and causes in which the many causes (clusters) are projected on top of one another (overlap one another) in the symptom space.
Rocket-Powered Data Science
MARCH 10, 2020
All of that “metadata” (which is simply “other data about your data”) enables rich discovery of shortest paths, central nodes, and communities. Any node and its relationship to a particular node becomes a type of contextual metadata for that particular note.
DataKitchen
JANUARY 3, 2022
For example, teams working under the VP/Directors of Data Analytics may be tasked with accessing data, building databases, integrating data, and producing reports. Data scientists derive insights from data while business analysts work closely with and tend to the data needs of business units.
Let's personalize your content