All Things Distributed
MARCH 11, 2015
AWS is enabling innovations in areas such as healthcare, automotive, life sciences, retail, media, energy, robotics that it is mind boggling and humbling. Many of these innovations will have a significant analytics component or may even be completely driven by it. Cloud analytics are everywhere.
All Things Distributed
SEPTEMBER 6, 2013
Shell leverages AWS for big data analytics to help achieve these goals. When Tom Tom launched the LBS platform they wanted the ability to reach millions of developers all around the world without having them invest a lot of capital upfront in hardware and building expensive data centers so turned to the cloud.
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All Things Distributed
MARCH 13, 2017
Job openings for machine learning scientists, data analytics experts, IT security experts or developers are already difficult to fill, and the demand for this knowledge will increase significantly in the next few years as customers show their demand for digital engagements.
The Agile Manager
MAY 31, 2020
It isn't difficult to imagine the DIY retailers lobbying congress to create legislation that allows employees to set aside up to x-thousand-dollars of annual income as tax exempt for use on home improvement. Testing, treatments and analytics may result in far less draconian methods of containment.
Scalegrid
MAY 13, 2020
Greenplum Database is an open-source , hardware-agnostic MPP database for analytics, based on PostgreSQL and developed by Pivotal who was later acquired by VMware. This feature-packed database provides powerful and rapid analytics on data that scales up to petabyte volumes. What Exactly is Greenplum? At a glance – TLDR.
Dynatrace
NOVEMBER 22, 2022
For retail organizations, peak traffic can be a mixed blessing. Traditionally, teams achieve this high level of uptime using a combination of high-capacity hardware, system redundancy, and failover models. The nightmare scenario for online retailers during peak periods, such as Black Friday and Cyber Monday, is a system crash.
O'Reilly
OCTOBER 11, 2022
Andrew Ng , Christopher Ré , and others have pointed out that in the past decade, we’ve made a lot of progress with algorithms and hardware for running AI. Our current set of AI algorithms are good enough, as is our hardware; the hard problems are all about data. The data available to our retail business is much more limited.
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