Erik on Software

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software engineering

A collection of 150 issues

Media Query Source: Part 23

The responses I provided to a media outlet on December 18, 2019: Media: Software changes so rapidly, but do developers think about the implications of this in the back of their mind while developing? For example, do they lose motivation when they think about how whatever they're developing

Media Query Source: Part 21

The responses I provided to a media outlet on December 4, 2019: Media: Technical debt is the added cost that's incurred when software is developed quickly with little or no regard to quality and must be reworked to reach its intended objectives. Looking for experts who can answer

Media Query Source: Part 20

The responses I provided to a media outlet on October 8, 2019: Media: Attributes to Look for in a Coder Beyond Coding Skills Gfesser: Note: I use the term "developer" throughout my response, since "coder" brings certain connotations likely not intended by the questions, and "

Media Query Source: Part 19 AngelList Talent (US digital magazine)Scrum methodology primerProducts evolve, so no deadlines or rigid plansStory points

My responses ended up being included in an article at AngelList (November 6, 2019). Extent of verbatim quote highlighted in orange, paraphrased quote highlighted in gray. Above image from cited article. The responses I provided to a media outlet on September 17, 2019, and the journalist's follow up

New Book Review: Machine Learning at Enterprise Scale

New book review for Machine Learning at Enterprise Scale: How Real Practitioners Handle Six Common Challenges, by Piero Cinquegrana and Matheen Raza, O'Reilly, 2019, reposted here: Copy provided by Qubole. This freely available O'Reilly text discusses six common challenges the authors have identified with respect to

Implementing Databricks for Data Science and Engineering Teams: Part 2

This post is the second part of a soon to be published case study I wrote about a recent client project implementing Azure Databricks with my team for data science and engineering teams (the first part can be found here). The analytics arm of a large midwestern U.S. insurance

Amazon re:MARS 2019 Day 2-4 (June 5-7, 2019)

Amazon re:MARS 2019 Aria Resort & Casino Day 2-4 (June 5-7, 2019) From the promotional materials: KEY2: Opening remarks & Innovation Spotlights (Day 2 / 9:00am – 11:30am) Amazon keynote led by Jeff Wilke, CEO of Worldwide Consumer. Keynote to include Innovation Spotlight talks by: 1) Tom Soderstrom, IT

Amazon re:MARS 2019 Day 1 (June 4, 2019)

Amazon re:MARS 2019 Aria Resort & Casino Day 1 (June 4, 2019) From the promotional materials: KEY1: Opening remarks & Innovation Spotlights (5:30pm – 6:30pm) Opening remarks by Dave Limp, SVP Amazon Devices and Services. Keynote to include innovation spotlights talks by (1) Marc Raibert, CEO, Boston Dynamics,

Implementing Databricks for Data Science and Engineering Teams: Part 1

A case study I wrote about a recent client project implementing Azure Databricks for data science and engineering teams was recently published (April 9, 2019). This write-up is the first of a two part series covering the first half of a client engagement with my team. (The original post can

Media Query Source: Part 17 ITPro Today (US digital magazine)Reaction to Facebook Chief AI ScientistPython's popularity is relatively recent"Best" pro

My responses ended up being included in an article at ITPro Today (June 27, 2019). Extent of verbatim quote highlighted in orange, paraphrased quote highlighted in gray. Above image from cited article. The responses I provided to a media outlet on February 27, 2019: Media: Facebook's chief AI