Data has always been important to business. While it wasn't long ago that businesses kept minimal information on people who bought their products, nowadays companies keep vast amounts of data. In the late 20th century, marketers began to take demographics seriously. It was hard to keep track of so much information without the help of computers.

Only large companies in the '60s and '70s could afford the research necessary to deliver real marketing insight. The marketers of yesteryear relied upon focus groups and expensive experiments to gauge consumer behavior in a controlled environment. Today even the smallest of companies can have access to a rich array of real-world data about their consumers' behavior and their consumers. The amount of data that is stored today dwarfs the data of only a few years ago by several orders of magnitude.

So what kind of information are businesses storing for marketing purposes? Some examples include:

- Demographic information — age, gender, ethnicity, education, occupation and various other individual characteristics.

Due to the advancements in technology, teens and adults alike can now partake in virtual worlds thanks to video games. Video games are enjoyed as a hobby all over the globe, but some gamers have made it their career with help from the ever-growing e-sport community. This is an inside look at the professional level of gaming from an ex-MLG participant, and what I remember going through when starting to play video games at an elite level.

One of the premiere and most popular leagues within the United States happens to be Major League Gaming or MLG for short. This is a league that usually involves more of the most recent games out, and they create circuits for each major title and its subsequent releases. Two of the most major game circuits within the MLG league were the Halo series and the Call of Duty series, both which happened to be first person shooters (FPS). There were a potential hundred or so teams within each circuit, but much like other competitions, the circuits were ran with winner’s brackets and losers brackets. This means that out of all the teams that would show up to MLG events, about the top eight of each bracket would really be known as the "elite" players. I personally played in the Gears of War circuit at venues like MLG Raleigh and MLG Toronto, and we had very few teams compared to Call of Duty and Halo. The amount of participants at each event usually varies in each circuit based on the popularity of the game being played.

When you win tournaments, the payouts are split between the team members. This means that looking at playing in the MLG for a life career is an ill-advised move. The cost to get to events and buy team passes usually negates the prizes you win most of the time, considering by the time that the prize money is split you are left with about $800 in a popular circuit (Like Call of Duty). The payouts are usually only high in special and certain occasions, one for example being the million dollar showdown that Infinity Ward hosted for Call of Duty: Modern Warfare 3 a couple years back. The way that players that make professional gaming their career get the big money now is by being sponsored by the big companies that back the league like Red Bull and Hot Pockets. MLG players like "Walshy" and "FeaR Moho" were sponsored early on in the league and were able to make a living off of the games they played. I would imagine them getting around $60K in a good year off of sponsors alone. I would go even as far as to say that if you do not have a sponsor in e-sports, you will not be financially successful in the career.

Being an MLG gamer requires passion and understanding for the games. If you just want to make money, then you are better off working at McDonalds.

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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

It is said that spoken languages shape thoughts by their inclusion and exclusion of concepts, and by structuring them in different ways. Similarly, programming languages shape solutions by making some tasks easier and others less aesthetic. Using F# instead of C# reshapes software projects in ways that prefer certain development styles and outcomes, changing what is possible and how it is achieved.

F# is a functional language from Microsoft's research division. While once relegated to the land of impractical academia, the principles espoused by functional programming are beginning to garner mainstream appeal.

As its name implies, functions are first-class citizens in functional programming. Blocks of code can be stored in variables, passed to other functions, and infinitely composed into higher-order functions, encouraging cleaner abstractions and easier testing. While it has long been possible to store and pass code, F#'s clean syntax for higher-order functions encourages them as a solution to any problem seeking an abstraction.

F# also encourages immutability. Instead of maintaining state in variables, functional programming with F# models programs as a series of functions converting inputs to outputs. While this introduces complications for those used to imperative styles, the benefits of immutability mesh well with many current developments best practices.

For instance, if functions are pure, handling only immutable data and exhibiting no side effects, then testing is vastly simplified. It is very easy to test that a specific block of code always returns the same value given the same inputs, and by modeling code as a series of immutable functions, it becomes possible to gain a deep and highly precise set of guarantees that software will behave exactly as written.

Further, if execution flow is exclusively a matter of routing function inputs to outputs, then concurrency is vastly simplified. By shifting away from mutable state to immutable functions, the need for locks and semaphores is vastly reduced if not entirely eliminated, and multi-processor development is almost effortless in many cases.

Type inference is another powerful feature of many functional languages. It is often unnecessary to specify argument and return types, since any modern compiler can infer them automatically. F# brings this feature to most areas of the language, making F# feel less like a statically-typed language and more like Ruby or Python. F# also eliminates noise like braces, explicit returns, and other bits of ceremony that make languages feel cumbersome.

Functional programming with F# makes it possible to write concise, easily testable code that is simpler to parallelize and reason about. However, strict functional styles often require imperative developers to learn new ways of thinking that are not as intuitive. Fortunately, F# makes it possible to incrementally change habits over time. Thanks to its hybrid object-oriented and functional nature, and its clean interoperability with the .net platform, F# developers can gradually shift to a more functional mindset while still using the algorithms and libraries with which they are most familiar.

Related F# Resources:

F# Programming Essentials Training