One of the most anticipated features that came on the iPhone 4S was a new thing called: Siri. Zooming out before concentrating on Siri, mobile assistants were the new rage. Beforehand, people were fascinated by the cloud, and how you could store your files in the Internet and retrieve it from anywhere. You could store your file at home, and get it at your workplace to make a presentation. However, next came virtual assistants. When you’re in the car, it’s hard to send text messages. It’s hard to call people. It’s hard to set reminders that just popped into your head onto your phone. Thus, came the virtual assistant: a new way to be able to talk to your phone to be able to do what you want it to do, and in this case, text message, or call people, and many other features. Apple jumped onto the bandwagon with the iPhone 4S and came out with the new feature: Siri, a virtual assistant that is tailored to assist you in your endeavours by your diction.

Getting started with Siri

To get Siri in the first place, you need an iPhone 4S; although you may have the latest updates on your iPhone 4 or earlier, having an iPhone 4S means you have the hardware that is required to run Siri on your phone. Therefore, if you are interested in using Siri, check into getting an iPhone 4S, as they are getting cheaper every single day.

People are optimistic about problem solving, but in most cases this is easier said than done. How do you do it?

In Adobe’s 2016 global study on creativity in business, 96% of people identified creativity as essential to their success, both in terms of their income and the value they bring to the world. Moreover, 78% wished they were capable of thinking differently, believing that they would progress through their careers more quickly if they did.

According to Malcom Gladwell, the world's most successful people have one thing in common: they think differently from most everyone else.  In his book, How Successful People Think, Malcom opens with the following:        “Good thinkers are always in demand.  A person who knows how may always have a job, but the person who knows why will always be his boss. Good thinkers solve problems, they never lack ideas that can build an organization, and they always have hope for a better future”
Too often we attribute creative and “different” thinking to natural, innate characteristics that belong only to the lucky. The truth is that you can study how ridiculously successful people think and incorporate their approach into your world.

Snippets and Quotes from Tech Innovators.
 

When businesses are trying to expand and require professionals to lead teams, terminology may get in the way of who performs what roles. When it comes to information technology (IT), new and vital professionals may seem hard to differentiate between one another. However, there are key differences between specific professionals needed with IT departments. Here are the responsibilities that differentiate between an IT manager and an IT project manager.

IT Managers

IT managers are the leaders of the entire IT infrastructure a business has to function properly. The IT manager must lead the entire IT department to regulate and maintain the IT network for the business. As a manager, this IT professional corresponds with other departments in the business about how the IT department is implementing the goals the business is aiming toward. In addition, the manager must be fiscally responsible and answer to executives and financial officers in the business the reasons behind certain costs and investments. Because of the dual computer technology and business acumen this profession requires, many IT managers have a Master of Business Administration (MBA) related to information technology.

IT Project Managers

The interpreted programming language Python has surged in popularity in recent years. Long beloved by system administrators and others who had good use for the way it made routine tasks easy to automate, it has gained traction in other sectors as well. In particular, it has become one of the most-used tools in the discipline of numerical computing and analysis. Being put to use for such heavy lifting has endowed the language with a great selection of powerful libraries and other tools that make it even more flexible. One upshot of this development has been that sophisticated business analysts have also come to see the language as a valuable tool for those own data analysis needs.

Greatly appreciated for its simplicity and elegance of syntax, Python makes an excellent first programming language for previously non-technical people. Many business analysts, in fact, have had success growing their skill sets in this way thanks to the language's tractability. Long beloved by specialized data scientists, the iPython interactive computing environment has also attracted great attention within the business analyst’s community. Its instant feedback and visualization options have made it easy for many analysts to become skilled Python programmers while doing valuable work along the way.

Using iPython and appropriate notebooks for it, for example, business analysts can easily make interactive use of such tools as cohort analysis and pivot tables. iPython makes it easy to benefit from real-time, interactive researches which produce immediately visible results, including charts and graphs suitable for use in other contexts. Through becoming familiar with this powerful interactive application, business analysts are also exposing themselves in a natural and productive way to the Python programming language itself.

Gaining proficiency with this language opens up further possibilities. While interactive analytic techniques are of great use to many business analysts, being able to create fully functioning, independent programs is of similar value. Becoming comfortable with Python allows analysts to tackle and plumb even larger data sets than would be possible through an interactive approach, as results can be allowed to accumulate over hours and days of processing time.

This ability can sometime allow business analysts to address the so-called "Big Data" questions that can otherwise seem the sole province of specialized data scientists. More important than this higher level of independence, perhaps, is the fact that this increased facility with data analysis and handling allows analysts to communicate more effectively with such stakeholders. Through learning a programming language which allows them to begin making independent inroads into such areas, business analysts gain a better perspective on these specialized domains, and this allows them to function as even more effective intermediaries.

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Who Are the Main Players in Big Data?