I think that Wayne Eckerson was the first to define the "purple person" in a 2010 blog post--someone with the mix of business and technology skills that is present in many successful business intelligence and analytics people.1 The same idea also came up--independently, I believe--at insurance company XL Catlin. Jim Wilson, a lead data engineer at the company, was chatting with his boss, Kimberly Holmes, about the people issues the company's "strategic analytics" group faced every day. As Holmes describes the situation, Wilson used the "purple people" analogy to describe a particular problem: "The business people, the actuaries, know what data they need and can define requirements, but typically don't have the skill set to design a data architecture that gives them the data they need. Technology people typically don't understand the business requirements, but they can design the data architectures. It's like the people in IT speak blue, the people in business speak red, but we need people who speak purple in order to create an appropriate solution."

Investment in intelligent business systems and automation is well underway across the globe, findings of an independent global study, carried out by analyst firm Freeform Dynamics. Top current application deployment areas cited by respondents include digital customer engagement systems (55 percent), process automation and workflow systems (52 percent), and automated risk monitoring and management solutions (50 percent). Commissioned by Ipswitch, the research further reveals that 45 percent have adopted intelligent IoT (Internet of Things) platforms and services, with 34 percent saying these technologies are on the agenda. Forty-two percent are utilising autonomous apps and bots, and 32 percent say they plan to do so. Forty-five percent are using cognitive computing and inference engines and a further 30 percent are looking to deploy in the near future.

The full information about Work Awesome is on the dedicated site. WORK AWESOME is here to connect you with the most inspiring people and thought-provoking insights into what work will be like tomorrow. And what are the learnings of self-organizing, hierarchy-abandoning firms? Charlene Johnson-Hadley, Executive Chef, Samuelsson's American Table Café and Bar Dan Charnas, Journalist, "Work Clean - The life-changing power of mise-en-place to organize your life, work, and mind" Moderator: Sam Sifton, Food Editor, The New York Times Dennis R. Mortensen, CEO, x.ai Chris Wiggins, Chief Data Scientist, The New York Times How do we make the best out of it. Jeff Wald, Co-founder, Work Market John Vars, CPO, Taskrabbit Devin Fidler, Director, Institute for the Future; Co-founder, Rethinkery Labs Steven Hill, "Raw Deal: How the "Uber Economy" and Runaway Capitalism Are Screwing American Workers" Moderator: Neil Irwin, Senior Economics Correspondent, The New York Times And can we do without it?

The first spark of the idea that would go on to become Tech City, surfaced on the last night of a UK trade mission to India in July 2010. At a British Government-hosted reception in Delhi, Matt Webb, then CEO and cofounder of design consultancy BERG, struck up a conversation with Rohan Silva, then a senior special advisor to the prime minister. Their chat soon turned to London and the best way to get the small cluster of startups that were scattered around Old Street to take off, and ultimately become a viable ecosystem. "Matt said there [wasn't] a Silicon Valley-type ethos in Old Street, where you can all come together," Silva told Wired magazine at the time. "So he asked for our help." A few months later, the Prime Minister delivered a speech in which he declared that "something [was] stirring in east London", which could one day "be one of the world's great technology centres".

Mac OS X has been around so long that Nickelback had the number one single the year it launched. OS X is officially dead, and has been renamed macOS. The first version of macOS, codenamed Sierra, launches this fall as a free update for most Macs. But there's a public beta version out now, and I've been testing it for the last week or so. There are tons of changes in Sierra, and they all add up to a big, significant update for the Mac.

There are a few places where you can find Siri in macOS, and each feels intuitive. For starters, you'll find the familiar purple Siri shortcut in the Dock, right next to Finder. That lower-left corner is the same place we already expect to find Cortana on Windows 10. If you like, though, Siri also lives in the tray, in the upper-right area of the screen, right next to where the search bar already lives. Or -- and this is my personal favorite -- you can use the keyboard shortcut Fn-spacebar to bring it up without using your cursor.

Last week, at the annual news extravaganza/coding demo/Beats 1 jam sesh that is WWDC, Apple launched a new version of its desktop operating system. There was a funny slide about naming conventions, another California-centric name (Sierra) and a bunch of new features. And Craigy With The Good Hair announced a small but long overdue change: Mac OS X is now called macOS. One day after the event, not two minutes after booting up a MacBook Pro that Apple pre-loaded with a preview build of macOS Sierra, I asked Siri some existential questions. Then I asked which version of OS X she was running, expecting a gentle chiding about macOS and silly questions.

From Siri to photo memories, here are five new features of the MacOS Sierra, coming to the public as a beta in July. NEW YORK--Siri evaded my question for what took Apple's voice assistant so long to get onto the Mac. "Who, me?" responds the voice familiar to anyone who uses an iPhone. However tardy Siri's arrival, the debut of Apple's loquacious personal helper on the company's computers is arguably the most welcome new feature coming to Macs that will be running macOS Sierra. Sierra is the latest iteration of Apple's operating system for its PCs and is the first version in years without the OS X moniker.

As the manufacturing industry is moving away from the traditional long term service contract to an'Analytics-as-a-Service' model, big data applications are increasingly being used to collect data from manufacturing operations. Using big data, you can accurately predict failure in operations well ahead of time, increasing the service revenue and reducing the cost of service. In addition, you can predict the health of your equipment in real time, and release equipment for maintenance only when necessary. Through the use of neural networks, support vector machines, and decision trees, you can identify complex interdependencies within operational parameters and detect anomalies that lead to equipment failures.

In financial services, access to big data and analytics is creating a huge opportunity to improve everything from efficiency, accuracy and speed to fraud prevention. Specialising in analytics, business intelligence and data management, SAS aims to help its customers make important decisions faster, better and with more confidence. Here Vincent Kilcoyne, Fintech Innovation Lead at SAS UK & Ireland, talks about the firm's new Fintech Incubator and what's next for financial services. Where is biggest opportunity for analytics in finance? I see a huge amount of it within the Fintech space.