I’ll get straight to the point.  Why should companies invest more in management training?  Here are 10 simple reasons.

1) An employee’s relationship with his or her direct manager is the most important single factor in employee engagement.

2) Engaged employees are happier and more productive.  Disengaged employees are frustrated and more disruptive.

3) Because there’s no widely agreed-on skillset for management (good managers come in all shapes and sizes), there’s an assumption everyone knows how to do it.  This is akin to someone who’s never driven before being given keys to a car and told: “Drive.”  (Many many years ago, this is how I first learned to manage.  I blundered my way through it.  Trial and error.  It wasn’t pretty.)

Companies have been collecting and analyzing data forever, pretty much.” So what’s really new here? What’s driving the data-analytics revolution and what does it mean for those that choose to postpone or ignore the pivotal role big-data is currently having on productivity and competition globally?

General Electric chairman and CEO Jeff Immelt explains it best when stating that “industrial companies are now in the information business—whether they like it or not.”  Likewise, digital data is now everywhere, it’s in every industry, in every economy, in every organization and according to the McKinsey Global Institute (MGI), this topic might once have concerned only a few data geeks, but big data is now relevant for leaders across every sector as well as consumers of products and services.

In light of the new data-driven global landscape and rapid technological advances, the question for senior leaders in companies now is how to integrate new capabilities into their operations and strategies—and position themselves globally where analytics can influence entire industries. An interesting discussion with six of theses senior leaders is covered in MGI’s article, “How companies are using big data and analytics,” providing us with a glimpse into a real-time decision making processes.

Java still has its place in the world of software development, but is it quickly becoming obsolete by the more dynamically enabled Python programming language? The issue is hotly contested by both sides of the debate. Java experts point out that Java is still being developed with more programmer friendly updates. Python users swear that Java can take up to ten times longer to develop. Managers that need to make the best decision for a company need concrete information so that an informed and rational decision can be made.

First, Java is a static typed language while Python is dynamically typed. Static typed languages require that each variable name must be tied to both a type and an object. Dynamically typed languages only require that a variable name only gets bound to an object. Immediately, this puts Python ahead of the game in terms of productivity since a static typed language requires several elements and can make errors in coding more likely.

Python uses a concise language while Java uses verbose language. Concise language, as the name suggests, gets straight to the point without extra words. Removing additional syntax can greatly reduce the amount of time required to program.  A simple call in Java, such as the ever notorious "Hello, World" requires three several lines of coding while Python requires a single sentence. Java requires the use of checked exceptions. If the exceptions are not caught or thrown out then the code fails to compile. In terms of language, Python certainly has surpassed Java in terms of brevity.

Additionally, while Java's string handling capabilities have improved they haven't yet matched the sophistication of Python's. Web applications rely upon fast load times and extraneous code can increase user wait time. Python optimizes code in ways that Java doesn't, and this can make Python a more efficient language. However, Java does run faster than Python and this can be a significant advantage for programmers using Java. When you factor in the need for a compiler for Java applications the speed factor cancels itself out leaving Python and Java at an impasse.

While a programmer will continue to argue for the language that makes it easiest based on the programmer's current level of knowledge, new software compiled with Python takes less time and provides a simplified coding language that reduces the chance for errors. When things go right, Java works well and there are no problems. However, when errors get introduced into the code, it can become extremely time consuming to locate and correct those errors. Python generally uses less code to begin with and makes it easier and more efficient to work with.

Ultimately, both languages have their own strengths and weaknesses. For creating simple applications, Python provides a simpler and more effective application. Larger applications can benefit from Java and the verbosity of the code actually makes it more compatible with future versions. Python code has been known to break with new releases. Ultimately, Python works best as a type of connecting language to conduct quick and dirty work that would be too intensive when using Java alone. In this sense, Java is a low-level implementation language. While both languages are continuing to develop, it's unlikely that one language will surpass the other for all programming needs in the near future.

As the cloud buzz is getting louder with every passing day you are tempted to take the big leap into the cloud but may have restrained yourself paranoid by ad infinitum cloud security discussions floating on the web. No one can deny the fact that your data is the lifeblood your business. So, undoubtedly its security is of paramount importance for survival of your business.  As cloud computing is a paradigm shift from the traditional ways of using computing resources, you must understand its practical security aspects.

Is Cloud Computing Safe?

There can’t be a binary answer (Yes or No) to this question. But with my experience and as an authority on the subject I can tell you that technologies enabling Cloud services are not in any way less secure than the traditional or on-premise hosting model.  Also, with the evolution of technology, the cloud providers are getting matured and almost all the providers are offering built-in security, privacy, data backups and risk management as a part of their core service.If you are not a big IT company then you must ask yourself:

·         Can an on-premise solution or a traditional hosting provider match the same level of standard security and privacy requirement as provided by the specialist cloud provider whose core competency lies in providing state of the art security and privacy?