CTOvision

JANUARY 18, 2015

Implementing an Enterprise Data Hub — Technical perspectives for implementing enterprise data hub architectures, converged analytics for workflow optimization, and the essential role of open standards and frameworks to ensure continuous innovation. Opening Keynote. Implementing an Enterprise Data Hub. Eddie Garcia.

Fractional CTO 113

Fractional CTO Program Management Programming Big Data 113

Netlify

SEPTEMBER 30, 2021

Automating our enterprise billing: we need it to be manageable while providing us a lot of different ways to sell at the enterprise level. or a picture of cute animal” or “A picture of a cute animal (not mandatory but encouraged)” (you can check it out in our open source repo too!).

Engineering 52

Engineering Technical Review Software Review Systems Review 52

Brainvire

OCTOBER 22, 2018

So, what about the enterprises or large-scale organisations? On February 8, 2010, an open-source search engine called Elastic Search was released to meet this need. Why Do Enterprises Require an Exclusive Search Engine? Engineering Manager at ShopBack. Licensed under the Apache License 2.0,

Industry 40

Industry Case Study Automotive Healthcare 40

Netlify

SEPTEMBER 25, 2019

The JAMstack at scale – how large companies and enterprises can successfully employ JAMstack techniques. After her work as an engineering manager at a number of technology companies she has emerged as a leading voice in strategies for UI frameworks and architectures. Community and ecosystem growth and adoption.

Conference 8

Conference Technical Cofounder Web Development Serverless 8

Cloudera

JUNE 30, 2022

As the first hybrid data platform to offer an open data lakehouse, CDP enables multi-function analytics at petabyte scale on both streaming and stored data in a cloud-native object store across multiple clouds and on premises. Read why the future of data lakehouses is open.

Data 89

Data Analytics Machine Learning Artificial Inteligence 89

O'Reilly Media - Ideas

OCTOBER 19, 2021

This is both frustrating for companies that would prefer making ML an ordinary, fuss-free value-generating function like software engineering, as well as exciting for vendors who see the opportunity to create buzz around a new category of enterprise software. The new category is often called MLOps. Software Development Layers.

DevOps 141

DevOps Data Software Review Technical Advisors 141

O'Reilly Media - Ideas

JUNE 19, 2019

First, the machine learning community has conducted groundbreaking research in many areas of interest to companies, and much of this research has been conducted out in the open via preprints and conference presentations. Demand for tools for managing ML in the enterprise. Source: Ben Lorica, using data from a Twitter poll.

Government 79

Government Artificial Inteligence Machine Learning Testing 79

Altexsoft

APRIL 26, 2022

The main idea of any data warehouse (DW) is to integrate data from multiple disjointed sources (e.g., CRMs, OLAP/OLTP databases, enterprise applications, etc.) But Enterprise users can choose a period of time up to 90 days. In this case, it includes Delta Lake storage and a SQL engine called Databricks SQL Analytics.

Weak Development Team 59

Weak Development Team Data Storage Technical Review 59

TechCrunch

JULY 13, 2021

Expensify founder and CEO David] Barrett, a self-proclaimed alpha geek and lifelong software engineer, was actually Red Swoosh’s last engineering manager, hired after the failure of his first project, iGlance.com , a P2P push-to-talk program that couldn’t compete against Skype. By 2007, Beevers had completed his Ph.D.

Innovation 249

Innovation Internet Engineering Engineering Culture 249