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.
 

C# PROGRAMMING –MAIN DESIGN GOALS

C# is a popular programming language these days, and it was designed from inception to provide a simple, clean, general purpose programming language for those intending to work within the confines of Microsoft’s .NET framework.  Since then, it has been approved as one of the standard languages by both ECMA and ISO, making C# programming an essential tool in every programmers’ kit.

Different languages have different uses and specialties, and C# was designed for programmers to be able to use it to create different components for use in software that would be deployed and distributed en masse, to live use environments.  This means that designers had to really put an emphasis on making the actual source code extremely compatible and portable.  Those already familiar with C or C++ should definitely notice this emphasis.

Another particular point of emphasis during design was focus on internationalization of the language; it was intended from inception to be available all over the world, and to see all sorts of different implementations based on variance in regional programming technique.  The resultant use should help the language develop sophistication as it is refined throughout different versions.

Python programming language is general purpose open source programming language. One of its main features is flexibility and ease of use. Python has a variety of useful set of utilities and libraries for data processing and analytical tasks. Currently due to the rise in demand of big data processing python has grown in popularity because its features are easy to use which are core to the processing of huge chunks of information.

Guido Van Rossum, the pioneer of python, introduced python in the year 1980 and then implemented it in 1989. The intention behind the development of python was to make it open source language that can also be used for commercial projects. The fundamental principle of python is to write the code that is easy to use, highly readable and embrace writing fewer lines of code for achieving a particular task. One of the most popular standard libraries which have ready to use tools for performing a various work is Python Package Index. It was introduced in January 2016 and contains more than 72,000 packages for third-party software usage.

Python plays a critical role in linking data to customers. Recently python has found few entry barriers and many people have had access to have experienced the power of python in the past. So, what makes python the best language for big data analytics?

One of the reasons to choose python is that python ecosystem is very vibrant, the ratings at Redmonk are a proof of the strength python community. The Redmonk ranking is based on StackOverflow discussions and contribution made in Github to determine the popularity of programming language on the method used by users to ask questions about Python and the number of the open source projects contributions.

A business rule is the basic unit of rule processing in a Business Rule Management System (BRMS) and, as such, requires a fundamental understanding. Rules consist of a set of actions and a set of conditions whereby actions are the consequences of each condition statement being satisfied or true. With rare exception, conditions test the property values of objects taken from an object model which itself is gleaned from a Data Dictionary and UML diagrams. See my article on Data Dictionaries for a better understanding on this subject matter.

A simple rule takes the form:

if condition(s)

then actions.

An alternative form includes an else statement where alternate actions are executed in the event that the conditions in the if statement are not satisfied:

if condition(s)

then actions

else alternate_actions

It is not considered a best prectice to write rules via nested if-then-else statements as they tend to be difficult to understand, hard to maintain and even harder to extend as the depth of these statements increases; in other words, adding if statements within a then clause makes it especially hard to determine which if statement was executed when looking at a bucket of rules. Moreoever, how can we determine whether the if or the else statement was satisfied without having to read the rule itself. Rules such as these are often organized into simple rule statements and provided with a name so that when reviewing rule execution logs one can determine which rule fired and not worry about whether the if or else statement was satisfied. Another limitation of this type of rule processing is that it does not take full advantage of rule inferencing and may have a negative performance impact on the Rete engine execution. Take a class with HSG and find out why.

Rule Conditions