Imagine being able to go about your day and know that a computer is making you money. You don’t need to sit in front of it, you can go golfing or into the office and know that back home you are potentially scoring extremely valuable stocks. This is now being accomplished through trading algorithms.
Algorithms are a clear set of instructions telling a computer what to do and when to do it. Algorithmic trading is a new use of Big Data in finance. The theory behind algorithmic trading is that a computer is set up with algorithms giving defined rules and parameters on when to trade or sell. Computers can scan through stocks and pick out stocks that have dropped or risen in price to buy or sell at the precise time to ensure optimal earnings.
Through this process investors are learning how to rely on these algorithms to make trading decisions and act much quicker than any human can. Using computers also takes the human emotion element out of the equation, leaving objective data to make decisions. Although this sounds like an intriguing way to make money, one must also be very cautious when trusting a computer with their money. Investors are encouraged to learn coding to make their own customized algorithms and systems that have set perimeters and conditions. This would be the only way to securely trade without a high risk of a possibly devastating malfunction.
This trading process is just another way Big Data is revolutionizing the financial industry. To learn other ways Big Data is influencing the Finance industry make sure you read Business Optimization, Customer Satisfaction and ROI.
Almost every physical object can be connected to the internet.
We are racing forward to an era of hyper-connectivity. Objects now have the ability to communicate with each other, all using DATA!
The Internet of Things is happening now!
The Internet of Things (IoT) is a term that has been thrown around for a few years now, but many of us may still not fully understand what it means.
The IoT refers to a network of physical objects or “things” that have the capabilities to both collect and exchange any amount of data. They do this through a variety of software, electronics, sensors, and network connectivity.
So many devices that we own are connected to this “Internet of Things”, and we are using this network of data everyday to make our lives easier. This includes everything from cell phones, coffee makers, washing machines, headphones, wearable devices and almost anything else you can think of. If it has an on and off switch, then chances are good that it is connected to the IoT.
Now that more and more objects are connected to the IoT, those objects can all communicate to optimize day-to-day practices, create new opportunities, and save us money!
This is a great video looking at 7 bind-blowing facts of the Internet of Things.
“In 2008, there were already more objects connected to the internet than people.”
“The ATM was one of the first objects of the Internet of Things, dating back to 1974.”
“This year we will have 4.9 Billion connected things.”
“By 2020, we will have 6.1 Billion smartphone users.”
“The global market for wearable devices has grown 223% in 2015.”
“By 2020, a quarter of a billion vehicles will be connected to the internet.”
“All of these devices collect and transmit data, contributing to our Big Data world!”
The traveling industry is welcoming Big Data with open arms for they can use it to track traveling trends and determine when they will be the busiest. This type of information allows companies such as Southwest to determine the optimal time to raise prices or offer deals. Depending on the demand for flights during a certain time period, the airline companies can raise prices and be confident that people will still buy purchase them. This is why we are always told to book our flights with plenty of time in advance; the airlines know that those who wait until the last minute to buy a flight are desperate and will pay whatever is necessary.
Airlines look at the big data to determine which days throughout the year tend to be most heavily traveled and which days people prefer not to travel on. The cheapest days to fly are Tuesdays, Wednesdays, and Saturdays. These days are less expensive than the others because these are the days people don’t necessarily like to travel on. They are inconvenient and therefore less desirable. More sought after days will cost more money, especially around the holidays. Data has shown that there is the most widespread travel between Thanksgiving and New Years. The holidays are when people take extra time to visit family and loved ones they don’t otherwise get to see. Airlines know this and increase their prices knowing that people won’t put a price on seeing their family for the holidays.
Not only the airline industry can use big data to rake in some extra cash. Consumers can look up the data on when airlines raise and drop flights to save themselves some dough on booking their next travel accommodations. As we are right around the corner from this holiday season, hopefully everyone has been proactive, looked at the data and have scored great prices on their tickets home!
You can pretty much look anywhere on the internet today and find an article, post, or book written on the benefits of Big Data. It is on the mind of every executive out there, and rightfully so. While the benefits do greatly outweigh the downsides, it still needs to be brought to attention that there often remains a weak link in big data- the data itself.
Without good data, the business intelligence gained from it can all be deemed useless. Without good data, companies find themselves spending unnecessary time and money in an attempt to clean it up. So, rather than focusing right now on how much data we could possibly gather, shouldn’t we be focusing on how to retrieve the ‘correct’ data?
Annual BI and Big Data expenditures are expected to reach $114 billion by the end of 2018- not a number to be taken lightly! It is estimated that almost $65 Billion of that is absorbed or unrealized by businesses each year due to return mail/bad data. Poor data is prevalent in nearly every major industry, from healthcare to retail and finance to telecommunications.
USPS gave us a perfect example of how crucial good data is when they incurred $1.5 Billion in costs processing “undeliverable as addressed” mail. While there were many other factors, over half a billion dollars in expense was due to businesses having wrong addresses in their databases.
Organizations can continue to go along as many are today, gathering all of the data they can get their hands on, because somewhere within that, the good data will fall. However, in an age of efficiency and desire to save as much time and money as possible, executives should drive their organizations to ensure data is properly entered from the beginning or corrected within the systems and databases. Thankfully, there are many products already on the market that can help companies with this today.
After getting rid of the crud in the data and spending our time retrieving only what matters, we will begin to see Big Data being used to its fullest potential. Oh, the possibilities!
The music industry has gone through huge changes over the last 10 years, and finding a “fair” way for artists to make money for their work has become something of a project. CD sales plummeted ever since digital downloads became so popular and readily available. Recently, digital downloads have been steadily declining as music-streaming platforms such as Pandora, Spotify, and Apple Music have gained a rapid following.
Simply put, the industry is changing. So, how can we help artists receive the compensation and recognition they deserve? The answer to that lies within big data.
Pandora’s recent acquisition of Ticketfly gives us a glimpse at the future of the streaming industry- a future that is evolving to include live music. And that’s where the money is- if Pandora can manage the big data.
When streaming was introduced, it gave previously unheard artists a new opportunity to be heard and put the listeners in the driver’s seat. Streaming companies may now be able to drive those changes by using data and directing listeners straight to live events.
Traditionally, ticketing companies have used purchased data along with associated demographic data to target their customers for upcoming events. That should be enough right? Wrong. To accurately use predictive analytics to target these music lovers, streaming companies need to use their years of data from their millions of users. This data is rich with usable information, whether it be demographics from registration, what artists one skips, or what time of day they prefer certain music. Combining this with fan data from ticketing companies benefits both the artist and the listener. So far, Pandora is on the right track with this.
Selling concert tickets to fans based on the types of music they enjoy is not a breakthrough advancement in this industry. However, what can act as a radical change is going to revolve around what data is being used and in conjunction with what.
With Pandora’s recent acquisition, they will not only be able to suggest artists similar to those you already like, but they will also be able to notify you of upcoming concerts that they predict you will like.
By using big data to grow and monetize these fan bases, more live event tickets will be sold and artists will have the opportunity to gain the credit they deserve.
Big Data and Aliens have little in common other than IBM, NASA and SETI’s interest in them.
IBM has announced that they will be lending their Big Data analytics systems to SETI ( Search for Extra-Terrestrial Intelligence) Institute to aid in their hunt for extra terrestrial life. NASA is also working with IBM and SETI, providing deep space radio signals that may contain signals that lead to a discovery of other life forms.
How can IBM help SETI look for aliens?
SETI will be utilizing IBM’s Spark system for it’s machine learning qualities. Spark is an open source data system that is continually improving, making it a wonderfully useful tool in searching for the unknown. The deep space radio signals can be processed by Spark to potentially catch any signals that human analysts may have missed.
SETI is extremely excited about the partnership with IBM as their resources have vastly improved. SETI can now search for extra terrestrial life faster and more meticulously. Instead of relying on stargazers and fanatics, SETI now has the help of NASA which means they will receive data on the far out places of space they never had access to before.
This unique partnership is an innovative way to use Big Data. Many companies today are engaging in Big Data Anlalytics to extract information to better their business, but this is the first we are hearing of Big Data working with SETI. Big Data is such a dynamic tool that can be used in almost any realm. From healthcare to banking Big Data is helping people make decisions and discover more accurate information. With IBM, NASA and SETI working together we are making major leaps in the search for intelligence beyond our world.
Just like its effect on other industries, the use of a Big Data analytics system like Spark saves time and money. SETI is now discovering evidence they have been searching for for years! SETI is especially lucky to have their partnership with IBM so that they do not need to run their own Spark system and can simply use IBM’s.
Who knows, maybe in the next ten years we will be tracking extra terrestrial signals in real time, becoming faster and smarter on our hunt to find life forms beyond ourselves.
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