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

There has been and continues to be a plethora of observational studies by different researchers in the publishing industry focused on how e-books have affected hard-copy book sales. Evidence from these studies has indicated that there is a significant and monumental shift away from hard-copy books to e-books.[1]These findings precipitate fears that hard-copy books might become more expensive in the near future as they begin to be less available.  This scenario could escalate to the point where only collectors of hard-copy books are willing to pay the high price for ownership.

The founder of Amazon, Jeff Bezos, made a statement in July 2010 that sales of digital books had significantly outstripped U.S. sales of hard-copy. He claimed that Amazon had sold 143 digital books for its e-reader, the Kindle, for every 100 hard-back books over the past three months. The pace of this change was unprecedented;  Amazon said that in the four weeks of June 2010, the rate of sales had reached 180 e-books for every 100 hard-backs sold. Bezos said sales of the Kindle and e-books had reached a "tipping point", with five authors including Steig Larsson, the writer of Girl with a Dragon Tattoo, and Stephenie Meyer, who penned the Twilight series, each selling more than 500,000 digital books.[2] Earlier in July 2010, Hachette said that James Patterson had sold 1.1m e-books to date.

According to a report made by Publishers Weekly, for the first quarter of 2011, e-book sales were up 159.8%; netting sales of $233.1 million. Although adult hard-cover and mass market paperback hard-copies had continued to sell, posting gains in March, all the print segments had declined for the first quarter with the nine mass market houses that report sales. Their findings revealed a 23.4% sales decline, and that children’s paper-back publishers had also declined by 24.1%.[3] E-book sales easily out-distanced mass market paperback sales in the first quarter of 2011 with mass market sales of hard-copy books falling to $123.3 million compared to e-books’ $233.1 million in sales.

According to .net sales report by the March Association of American Publishers (AAP) which collected data and statistics from 1,189 publishers, the adult e-Book sales were $282.3 million in comparison to adult hard-cover book sales which counted $229.6 million during the first quarter of 2012. During the same period in 2011, eBooks revenues were $220.4 million.[4] These reports indicate a disconcerting diminishing demand for hard-copy books.

Welcome to the career field of Business Intelligence. Business Intelligence is a concept that involves a certain level of interaction within an organism, analytically and dynamically, to come to business solutions which implement better, more effective and timely decision making. These solutions are reached by establishing an understanding of the right kinds of user data: what is going well, what is going wrong, taking and monitoring certain actions, previously unknown trends, and patterns, and improved collaboration. When all of this data is taken into account, the entire decision-making process, within a business, will inevitably improve. As an Oracle BI developer, there are specific skills which will drastically make your job easier and results more effective. As time goes on and technology changes, the list is constantly being updated. The following are skills an Oracle Business Intelligence Developer might need to know or learn in 2019.

Communication

The original article was posted by Michael Veksler on Quora

A very well known fact is that code is written once, but it is read many times. This means that a good developer, in any language, writes understandable code. Writing understandable code is not always easy, and takes practice. The difficult part, is that you read what you have just written and it makes perfect sense to you, but a year later you curse the idiot who wrote that code, without realizing it was you.

The best way to learn how to write readable code, is to collaborate with others. Other people will spot badly written code, faster than the author. There are plenty of open source projects, which you can start working on and learn from more experienced programmers.

Readability is a tricky thing, and involves several aspects:

1. Never surprise the reader of your code, even if it will be you a year from now. For example, don’t call a function max() when sometimes it returns the minimum().
2. Be consistent, and use the same conventions throughout your code. Not only the same naming conventions, and the same indentation, but also the same semantics. If, for example, most of your functions return a negative value for failure and a positive for success, then avoid writing functions that return false on failure.
3. Write short functions, so that they fit your screen. I hate strict rules, since there are always exceptions, but from my experience you can almost always write functions short enough to fit your screen. Throughout my carrier I had only a few cases when writing short function was either impossible, or resulted in much worse code.
4. Use descriptive names, unless this is one of those standard names, such as i or it in a loop. Don’t make the name too long, on one hand, but don’t make it cryptic on the other.
5. Define function names by what they do, not by what they are used for or how they are implemented. If you name functions by what they do, then code will be much more readable, and much more reusable.
6. Avoid global state as much as you can. Global variables, and sometimes attributes in an object, are difficult to reason about. It is difficult to understand why such global state changes, when it does, and requires a lot of debugging.
7. As Donald Knuth wrote in one of his papers: “Early optimization is the root of all evil”. Meaning, write for readability first, optimize later.
8. The opposite of the previous rule: if you have an alternative which has similar readability, but lower complexity, use it. Also, if you have a polynomial alternative to your exponential algorithm (when N > 10), you should use that.

Use standard library whenever it makes your code shorter; don’t implement everything yourself. External libraries are more problematic, and are both good and bad. With external libraries, such as boost, you can save a lot of work. You should really learn boost, with the added benefit that the c++ standard gets more and more form boost. The negative with boost is that it changes over time, and code that works today may break tomorrow. Also, if you try to combine a third-party library, which uses a specific version of boost, it may break with your current version of boost. This does not happen often, but it may.

Don’t blindly use C++ standard library without understanding what it does - learn it. You look at std::vector::push_back() documentation at it tells you that its complexity is O(1), amortized. What does that mean? How does it work? What are benefits and what are the costs? Same with std::map, and with std::unordered_map. Knowing the difference between these two maps, you’d know when to use each one of them.

Never call new or delete directly, use std::make_unique and [cost c++]std::make_shared[/code] instead. Try to implement usique_ptr, shared_ptr, weak_ptr yourself, in order to understand what they actually do. People do dumb things with these types, since they don’t understand what these pointers are.

Every time you look at a new class or function, in boost or in std, ask yourself “why is it done this way and not another?”. It will help you understand trade-offs in software development, and will help you use the right tool for your job. Don’t be afraid to peek into the source of boost and the std, and try to understand how it works. It will not be easy, at first, but you will learn a lot.

Know what complexity is, and how to calculate it. Avoid exponential and cubic complexity, unless you know your N is very low, and will always stay low.

Learn data-structures and algorithms, and know them. Many people think that it is simply a wasted time, since all data-structures are implemented in standard libraries, but this is not as simple as that. By understanding data-structures, you’d find it easier to pick the right library. Also, believe it or now, after 25 years since I learned data-structures, I still use this knowledge. Half a year ago I had to implemented a hash table, since I needed fast serialization capability which the available libraries did not provide. Now I am writing some sort of interval-btree, since using std::map, for the same purpose, turned up to be very very slow, and the performance bottleneck of my code.

Notice that you can’t just find interval-btree on Wikipedia, or stack-overflow. The closest thing you can find is Interval tree, but it has some performance drawbacks. So how can you implement an interval-btree, unless you know what a btree is and what an interval-tree is? I strongly suggest, again, that you learn and remember data-structures.

These are the most important things, which will make you a better programmer. The other things will follow.