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.

Data Warehouse 325

Data Warehouse Metadata Digital Transformation Unstructured Data 325

Cloudera

AUGUST 30, 2022

But while state and local governments seek to improve policies, decision making, and the services constituents rely upon, data silos create accessibility and sharing challenges that hinder public sector agencies from transforming their data into a strategic asset and leveraging it for the common good. . Towards Data Science ).

Data Architecture 78

Data Architecture Data Lake Metadata Data Warehouse 78

Cloudera

OCTOBER 11, 2022

A recent VentureBeat article , “4 AI trends: It’s all about scale in 2022 (so far),” highlighted the importance of scalability. The article goes on to share insights from experts at Gartner, PwC, John Deere, and Cloudera that shine a light on the critical role that data plays in scaling AI. . Data science needs analytics.

Snapshot 92

Snapshot Data Science Digital Transformation Metadata 92

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

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 60

Data Architecture Data Lake Machine Learning Data Governance 60

Cloudera

FEBRUARY 16, 2022

In this article, we explore model governance, a function of ML Operations (MLOps). We can think of model lineage as the specific combination of data and transformations on that data that create a model. This maps to the data collection, data engineering, model tuning and model training stages of the data science lifecycle.

Machine Learning 83

Machine Learning Modeling Metadata Recreation/Entertainment 83

Alation

JANUARY 26, 2023

These data requirements could be satisfied with a strong data governance strategy. Governance can — and should — be the responsibility of every data user, though how that’s achieved will depend on the role within the organization. This article will focus on how data engineers can improve their approach to data governance.

Data Governance 52

Data Governance Strategy Data Quality Marketing 52