Remove 2008 Remove Analytics Remove Clustering
article thumbnail

t-SNE (t-distributed stochastic neighbor embedding)

Dataconomy

t-SNE (t-distributed stochastic neighbor embedding) has become an essential tool in the realm of data analytics, standing out for its ability to unravel the complexities inherent in high-dimensional data. t-SNE was developed by Laurens van der Maaten and Geoffrey Hinton in 2008 to visualize high-dimensional data.

article thumbnail

Analyzing the history of Tableau innovation

Tableau

In this blog post, I'll describe my analysis of Tableau's history to drive analytics innovation—in particular, I've identified six key innovation vectors through reflecting on the top innovations across Tableau releases. And with this work, I invite discussions about this history, my analysis, and the implications for the future of analytics.

Tableau 145
professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Live Patching Is Invaluable To Data Development In Linux

Smart Data Collective

Live patching is one of the most important technologies for developers working on data analytics projects on Linux. Amazon AWS reported that they developed a new live patching process that could handle large clusters of servers, which is important for working on big data applications. But how does live patching work?

Big Data 125
article thumbnail

Analyzing the history of Tableau innovation

Tableau

In this blog post, I'll describe my analysis of Tableau's history to drive analytics innovation—in particular, I've identified six key innovation vectors through reflecting on the top innovations across Tableau releases. And with this work, I invite discussions about this history, my analysis, and the implications for the future of analytics.

Tableau 98
article thumbnail

Why Open Table Format Architecture is Essential for Modern Data Systems

phData

These systems are built on open standards and offer immense analytical and transactional processing flexibility. However, this feature becomes an absolute must-have if you are operating your analytics on top of your data lake or lakehouse. It provided ACID transactions and built-in support for real-time analytics.

article thumbnail

A review of purpose-built accelerators for financial services

AWS Machine Learning Blog

The financial services industry (FSI) is no exception to this, and is a well-established producer and consumer of data and analytics. This mostly non-technical post is written for FSI business leader personas such as the chief data officer, chief analytics officer, chief investment officer, head quant, head of research, and head of risk.

AWS 114
article thumbnail

Cassandra vs MongoDB

Pickl AI

Released as an open-source project in 2008 and later becoming a top-level project of the Apache Software Foundation in 2010, Cassandra has gained popularity due to its scalability and high availability features. Cassandra’s architecture is based on a peer-to-peer model where all nodes in the cluster are equal.