Sisense

JULY 24, 2019

NLQ serves those users who are in a rush, or who lack the skills or permissions to model their data using visualization tools or code editors. So if we think about data access as a function of technical skills and the time it takes to get an answer, NLQ will be the first technology that users will turn to when looking for insights.

Analytics 89

Analytics Experimentation Metadata Big Data 89

O'Reilly on Data

MAY 21, 2019

Companies successfully adopt machine learning either by building on existing data products and services, or by modernizing existing models and algorithms. In this post, I share slides and notes from a keynote I gave at the Strata Data Conference in London earlier this year. A typical data pipeline for machine learning.

Machine Learning 234

Machine Learning Technology Deep Learning Data Science 234

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). More Policies Emerged” (2010-2018). In other words, #adulting.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

Alation

MARCH 21, 2023

To fully realize data’s value, organizations in the travel industry need to dismantle data silos so that they can securely and efficiently leverage analytics across their organizations. What is big data in the travel and tourism industry? They may also suffer from data duplication, which undermines their analytics models.

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

Cloudera

MAY 22, 2018

Cloudera Data Science Workbench (CDSW) makes secure, collaborative data science at scale a reality for the enterprise and accelerates the delivery of new data products. As data scientists iteratively develop models, they often experiment with datasets, features, libraries, and algorithms as well as tuning hyperparameters.

Data Science 41

Data Science Snapshot Machine Learning Metadata 41

Domino Data Lab

AUGUST 8, 2019

Across the board, organizations struggle with hiring enough data scientists. Meanwhile, many organizations also struggle with “late in the pipeline issues” on model deployment in production and related compliance. then building machine learning models to recommend methods and potential collaborators to scientists.

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

Alation

FEBRUARY 13, 2020

At Alation, we’ve seen triple digit revenue growth and added new customers like Daimler, Fox Networks, and Hilton Hotels to the growing list of brands in production with the Alation Data Catalog. When we started Alation six years ago, we saw a data landscape in desperate need of an access point.

Enterprise 52

Enterprise Data Lake Machine Learning Data-driven 52

Cloudera

FEBRUARY 11, 2019

Covering just one type of analytics and integrated with one or two other applications, organizations are still faced with a patchwork of siloed systems that each carry their own data, metadata, security, and governance. Experiments remain undocumented and model versioning is done haphazardly. Governing for compliance.

Digital Transformation 57

Digital Transformation Data Governance Data Warehouse Data-driven 57

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