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.
 

Let’s face it, fad or not, companies are starting to ask themselves how they could possibly use machine learning and AI technologies in their organization. Many are being lured by the promise of profits by discovering winning patterns with algorithms that will enable solid predictions… The reality is that most technology and business professionals do not have sufficient understanding of how machine learning works and where it can be applied.  For a lot of firms, the focus still tends to be on small-scale changes instead of focusing on what really matters…tackling their approach to machine learning.

In the recent Wall Street Journal article, Machine Learning at Scale Remains Elusive for Many Firms, Steven Norton captures interesting comments from the industry’s data science experts. In the article, he quotes panelists from the MIT Digital Economy Conference in NYC, on businesses current practices with AI and machine learning. All agree on the fact that, for all the talk of Machine Learning and AI’s potential in the enterprise, many firms aren’t yet equipped to take advantage of it fully.

Panelist,  Michael Chui, partner at McKinsey Global Institute states that “If a company just mechanically says OK, I’ll automate this little activity here and this little activity there, rather than re-thinking the entire process and how it can be enabled by technology, they usually get very little value out of it. “Few companies have deployed these technologies in a core business process or at scale.”

Panelist, Hilary Mason, general manager at Cloudera Inc., had this to say, “With very few exceptions, every company we work with wants to start with a cost-savings application of automation.” “Most organizations are not set up to do this well.”

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.

Related:

Who Are the Main Players in Big Data?

IT jobs are without a doubt some of the highest paying jobs with information architects, data-security analysts and UX designers taking home $100,000 or more a year. But then again, these are high demand; high expertise jobs so don’t jump with joy as yet. But like every job and IT industry to be specific, not everyone commands such higher salaries. There are a large number of IT professionals who at some point of their career feel that their salaries have hit a standstill. Even if you are an IT professional and a great one at that, your technical expertise alone may not help you exceed the IT earning barrier. To continuously exceed your salaries, you need to work hard and smart. Here is how you can exceed the earning barrier in IT.

·         Gain Business Knowledge and Move Up The Management Ladder: IT departments for the most part are considered a part of “back office” operations. What this means is that despite being a core part of the business, IT professionals do not often get enough say in revenue generating components of the business and as a result seldom have a chance to take up senior management roles.  So if you do not want to stay content with a project manager or senior project management salary, invest time and money in gaining business knowledge. It could be through a formal business degree, online training courses or just by keeping your eyes and ears open while in the organization. Having the technical experience with business knowledge will instantly make you stand apart and open the doors for you to draw senior management salaries. For example, a survey conducted highlighted that CIOs were the biggest salary winners which clearly demonstrates the value of technical and business knowledge

·         Gain expertise on the “Hot” Technologies and Keep Learning: Say you are an expert in Java and draw a respectable salary in the industry. However, someone with less years of experience than you joins the organization and draws a higher salary than you! Why you ask. It could very well be because he/she is an expert in say big data technology such as Hadoop. Information Technology is one of the most dynamic industries with new technologies and languages coming up every now and then. When a new technology comes to the foray and gains traction, there is an instant demand-supply gap created which means that those with the specific skill sets are in a position to demand high salaries. If you have to break the IT earning barrier, always be ready to reinvent yourself by learning new technologies and this way you will be well positioned to jump on the high paying opportunities in the IT industry

·         Work On Your Own Side Projects: This one might seem controversial but let me clarify that I do not mean doing freelance work because even though your organization may never find out, it is ethically in breach of contract with your contract. If you have been lucky enough to be trained in some web based technologies such as Java, .NET or even HTML etc. spare sometime after office to build your own side projects. They could be very small projects tackling some problem that only you might have but there are multiple benefits of developing side projects. Worst case scenario, you will improve your technical skills. On the up side, you might end up creating your own business. A lot of technology start-ups were actually side projects the founders tinkered on with while they were employed full-time. You may not always succeed but there is no downside to the same