Let big data help you find your true love

Today, almost 20% of all relationships start online, more than 40% of America’s single population use online dating services, and one popular dating website, eHarmony.com, alone claims to be responsible for nearly 5% of marriages in the US.

So where does the success of online dating come from? 

Easy answer: the increasing use of big data helps online dating website to improve their matching results. Depending on the website, between 15 and up to 200 questions about personality, interests, education, likes and dislikes, etc. need to be answered to sign-up for their services.

After answering the questionnaires, the websites make billion of calculations for each new member by comparing their answers to the website’s existing members using extensive algorithms to provide new users with several matches. Even after the questionnaire is filled out; the matches are continuously refined based on changing preferences, user activity on the website, or feedback on proposed matches. By using these sophisticated calculations based on the big data about their members, online dating websites aim to propose the best matches to their members.

You’re alone at home at the moment? Let big data help you find your true love and try out online dating websites like www.eharmony.com or www.match.com

And now, the ladies will find you sexy because of Big Data too!

Big Data is a hot topic - so hot that recently Harvard Business Review called data science “the sexiest job in the 21st century”.

Today there is a scarcity for professionals, and companies are fighting for talents. In the next five years, this scenario will be much worse. In the US alone, according to a report by McKinsey Global Institute, 500,000 new jobs will be created but there will still be a shortage of 190,000 specialized professional to fill up them. In addition to that, the market will need over 1.5 million executives and support staff with at least basic knowledge in data related technology.

Probably know what you are thinking:

“Interesting, but how much money can a data professional make?”

Michael Rappa – Director of the Institute for Advanced Analytics in the North Carolina State University – gives us a reference; the average salary for a graduated student is $89,100 - $100,000 but for those with more experience, the answer is a classic economics theory: higher the demand higher the price.

"What does a data specialist do?" 
Here is a list of the principal Big Data Job titles:

-Data scientists: The top level in big data. This role is probably closest to what a 2011 McKinsey report calls "deep analytical talent."

- Data architects: Programmers who are good at working with messy data, disparate types of data, undefined data and lots of ambiguity.

- Data visualizers: Technologists who translate analytics into information a business can use.

- Data change agents: People who drive changes in internal operations and processes based on data analytics.

- Data engineers/operators: The designers, builders and managers of the big data infrastructure.

Now, if you want to be the next talent in big data and don’t know how to start, several of the top world universities are offering a good range of courses and degree in this field.

And if the numbers don’t attract you to the job, remember a job in Big Data is going to make the girls find you sexier!

Fashion trend forecasting, the new big thing in fashion

Imagine as a fashion retailer having access to a large set of data that forecast fashion trends, colors, fabrics and cuts in order to determine what is going to be produce next and displayed on the catwalks. This looks like something extremely futuristic, but for our surprise, retailers are currently taking advantage of this data mining technology. Retailers are  paying a fee that ranges between seven and fifteen thousand dollars to get access this technology. This technology is being developed by companies such as Worth Global Style Network (WGSN). WGSN is based on the UK and according to its CEO, Julie Harris, fashion forecasting have seen double digit growth in the last couple of years and for 2013 it is expected to grow even more.

Retailers are using this source of information to tackle customer demands and needs. Forecasting is and will play an extremely important role in the future success of the retail business. This information has become important in order to tap customers who shop online that demand the latest trends of outfits. Retailers have been able to cut down costs by reducing traveling expenses, freelance such as photographers for photo-shooting, and reduce on time spent on data gathering from the internet.

WGSN generates data by relying on blogs, fashion websites, traveling to fashion cities and attending to world known catwalk events. This data mining process is currently helping companies such as WGSN grow. WGSN will launch a retail analytics tool that will help with comparison shopping. Retailers will be able to check upon competitors and gauge demand for similar products with the use of the analytic tool.

As it can be seen is a win-win situation for retailers, since they are going to be able to cut down costs by having an accurate forecast on trends. Customer satisfaction will be improved by offering customers the latest fashionable tendency and reliability. 

"A satisfied customer is the best business strategy of all" - Michael LeBoeuf

Harnessing GPS data from 3.3M cars in Japan, Toyota sets to change the face of traffic management

Imagine if we could capture all the data on cars' movements, location and speed. Well this is exactly what Toyota has come up with, in there latest system Big Data Traffic Information Service.Toyota is taking advantage of big data by using a Digital Communication Module (DCM), this tool constantly monitors and transmits real time data to Toyota for scrupulous data mining. This data has been harvested from 3.3 million of integrated telecommunication and informatics users in Japan and 700,000 Toyota customers that are equipped. The system can provide users with helpful information such as routes, evacuation routes, the possible heights of tsunamis in case if one strikes, etc.

Having a car connected into a cloud system is relatively new in the market but is quickly moving from concept to reality, it promises safer roads and other benefits. Big data could potentially give the following benefits to the car users in a near future:

• If customers are willing to share their driving habits, more cloud connectivity could offer GPS updates tailored depending on which ones are the driving habits of the drivers.
  
  
• A human-auto interaction will lead to work in progress, it could be achieved by having a better human machine point of interaction.
  
• Cloud usage, would give the ability to store car data on the cloud in order to digitalize the business process. Maintenance checks would be easier to perform due to the data gathering. Tackling a potential problem would be easier. 
  
• A cloud connected information and entertainment system that personalizes your settings and automatically download content. 
  
• Data mining of information, based on driving behavior will include information to help you navigate the last mile of your trips accurately. 
  

Lose Big at the Casino? Big Data Helps Draw Customers Back to the Casino after Losses

Casinos specialise in customer service, they seek to provide the best environment and experience for you to spend money on tables, slot machines, entertainment and hotels. To provide the best customer services requires differentiation of service. This commonly relies on Parento’s rule where, “for many events, roughly 80% of the effects come from 20% of the causes” (Wikipedia 2013). Meaning it pays to look after the highest value customers.

The journey of differentiation of customer service started with the collection of data through customer loyalty programs. These programs have been around since the 1990s, and collect data on preferences, personal data and importantly payment transactions. Big data goes a step further to combine customer loyalty data with hotel booking data, restaurant bookings and even CCTV footage on the preferences and choices of bets. 

Caesars Entertainment is leading the curve in the adoption of these big data practices to provide tailored services to different customer groups. Tariq Shaubkat, Chief Marketing Officer of Caesars Entertainment explains in this short video how if you lose too quickly, Caesars will often intervene to offer to buy you dinner or tickets to a Celine Dion concert in order to improve your customer experience and stop customers defecting to a competitor’s casino.

Interestingly, the Flamingo Hotel (part of Ceasars Entertainment) employs 200 Data Scientists alone to analyse, manage and make decisions about the insights! This hot new job title coined by DJ Patil and Jeff Hammerbacher, is part of a growing profession in the field of big data. 

So next time you are at the casino, look out, as big  data ‘brother’ will be watching your every move.

Big Data algorithm and analytics in professional sports

Professional sports are going through a reformation by using technology and adapting sensor technology to it's development in order to obtain the largest set of data as possible. This set of data would bring competitive advantage to the team that adopts it well. Professional teams in the National Football League (NFL), National Basketball Association (NBA) and the English Premier League are using this technology and achieving great results as well as improving their learning curve regarding the topic. 

USA Professional Teams Logo

Big data in sports is relatively new, but now a days some professional teams are taking advantage of it. The Baltimore Ravens of the NFL is a clear example on how big data might be used in order to win a really competitive championship. The Raven's have won the Super Bowl XLVII by being able to prevent injuries, performance optimization, advanced scouting by usage of big data analysis. By having a large set of data available, it is easier to predict trends and patterns that at first sight are not easy to perceive.These set of data provides a competitive advantage that helps differentiate the good from the best. 

Baltimore Ravens Superbowl XLVII

Adidas have developed the MiCoach technology that helps you track your performance with the addition of an intelligent chip to a soccer boot in the case of soccer. It helps to improve performance on professional and amateur players with a really user friendly software. This chip lets you track the distance that the player moved on the pitch, how many sprints where taken, the active time, the maximum speed achieved. The data can be compiled in a historical trend in order to see evolution. By having access to these set of data players and coaches can focus in the weakness and work on improvements. It is a great way on comparing physical activity and capacity of players from the whole squad. The way on how trainings should be conducted could be modified accordingly to the necessity of the squad. 

Big data is playing and will play an extremely important role in the future of sports. Do not let the lack of technology bring your A-game down, take advantage of it and start boosting your performance and train like a champion.

"I hated every minute of training, but I said, "Don't quit. Suffer now and live the rest of your life as a champion". (Muhammad Ali)

Big Data in Banking

Banks are currently generating and collecting a gargantuan amount of data each day. There is the potential to use this data in real time to determine consumer risk profiles, detect fraudulent actions across the world improving customer relationship management and customer experience. In the following info-graphic you can see the role that big data plays in this industry. 

http://www.alacergroup.com/big-data-in-banking-infographic/

Due to the large quantity of data that is being manipulated, establishing and maintaining trust in data represents a challenging task as the sources and data variety grows. A bank that can harness big data can derive more insight about their business and build competitive advantage. 

According to a recent study by Thomas Davenport and Jill Dyché at the International Institute for Analytics working with SAS Institute, several US banks are using big data in order to understand how customers use their different channels such as branches, online, mobile, call centers and ATMs.

As it can be seen, banks are getting a better understanding of the consumer, but there is still along way yo go. The Financial Technology Innovation Lab is run by Accenture in collaboration with a group of the UK's leading financial service institutions, angel investors and venture capital firm. Six finalist will join the program from January to March in the City, London and pitch their ideas at the "Investors Day".

Interested entrepreneurs need to enter before 8 September 2013 at the following address:

http://www.fintechinnovationlablondon.co.uk/

How did Big Data help Gareth Bale become the most expensive footballer ever?!

The English Premier League is by the far the most well known and richest league in the world. For participating teams, everything is at stake. EPL attracts the best talent from all over the globe and clubs spend astronomical sum to hire players in hopes to improve or maintain their ranking and many a times only to avoid being at the bottom – which would mean relegation to the lower ranked league. Clubs spend big money to boost their team-sheets and many spend close to 94% of their total earnings disbursing players’ salaries.

Spotting a great talent is a huge undertaking for every club. All clubs employ talent spotters who travel around the globe to find the right players at best price. Until recently their technique was pretty old fashioned – spend hours watching lower league matches in hope of finding a rising star that would change their clubs’ fortune. But now these talent spotters are facing a tough competition from new age data analytics firms, such as Prozone and Opta, which collect realms of (massive) data and sell that to Football clubs for a fee. These Performance analysis systems, as they are known in the industry, use digital cameras to track every movement of every player, and this information is then used to produce the most precise player tracking systems available and they log every tackle, pass and goal, typically collecting 2000 or so events per match.

The objective information captured by these tools offer a completely new perspective on a player's performance. Take Gareth Bale, last season’s outstanding EPL player. Many of his talents are obvious and easy to spot: he is strong, fast with the ball, and scores lots of long distance shots. But crunching data suggests other attributes that are equally important. Gareth regularly intercepts opponents’ passes and makes many successful ones himself. The fact that he is good at getting and keeping the ball contributes a lot to his team’s defence. And this helps Tottenham Hotspur, his club, as much as his actual goals do.

Tottenham isn’t the only big club taking making the use of big data to analyze team’s performance. Chelsea, another top EPL club, has data for all the players playing in top 15 leagues across the world. Liverpool has also recruited a data scientist in the last year. Similarly Real Madrid, a top Spanish football club, has access to performance data form all major leagues. And it was only after analyzing Gareth's performance via one of these data analytics tool, real Madrid decided to offer a cool $133 million and add another shining star in their galacticos ensemble.

While big data and data analytics tools will not replace scouts entirely, one thing is for sure – data analytics, and big data in particular, will increasingly play an ever crucial role in identifying raw and hidden talent and will help many clubs save their place in their respective football leagues!!

Are you studying medicine, or are a doctor or physician? Now, you can use Big Data to help you save lives.

Most of the time the focus is on cost-savings by using Big Data. But Big Data is much more than that, it can now help save lives along with money. This idea could revolutionise the healthcare business by offering more relevant information to the healthcare network.

Imagine making real time data available of various forms of tests, or of patient history so that by the time you, an emergency case, arrives at a hospital, all of your medical records are right there and and there are no delays in your physical examination. In so many parts of the world, this could be a real life-saver.

Harnessing big data could help achieve three critical objectives in healthcare:

• Build sustainable healthcare systems
• Collaborate to improve care and outcomes
• Increase access to healthcare

With a growing need for efficient and accessible healthcare, companies and healthcare organisations are starting to invest in applications and analytical tools that help healthcare stakeholders identify value and opportunities. Dell currently places an emphasis on healthcare, they have been working with big data for a while now in areas such as genomics and personalized medicine. Dell's main goal is to help doctors in making the most accurate diagnose as possible in order to perform the best treatment to ill patient. As it can be seen in the following process image, here is an example on how big data comes to play an important role in the near future.

However, do note that this is contingent on the accuracy of data provided to the physicians. This is critical. Any form of inaccuracy can be fatal. While looking for examples on how data can fail healthcare facilities, I found this:
"My younger brother was born under circumstances that caused him to be transferred immediately to a neonatal ICU. In the same unit, another infant had been born with all of his organs outside his body. He had survived surgery and his vital signs were being monitored with a pressure mat in his incubator. On one visit, his father lifted him out of the incubator and noticed the monitor was still registering the baby. He gave the child to the mother, placed a stuffed animal in the incubator, and covered it with the blanket. You can imagine what happened when the father called the nurse to check on the baby and she discovered a stuffed tiger instead."
(Source: Making Data Meaningful, Lucrum, Dec 10 2012)
Imagine if the data a physician was meant to use was completely non-existent in real life, and imagine the consequences!

Despite the various concerns with using Big Data, it is clear about the extremely important role it will play in Healthcare in the near future. If used correctly, it will help physicians and the healthcare sector to reduce uncertainty, hence improving the quality of life patients.

"I don't expect to get yesterdays medicine. If I can help it, I'd like to get tomorrow's medicine". (Elizabeth Edwards)
We strongly believe that big data is tomorrow's medicine.

Big Data in the Retail Industry

Imagine as a business being able to create competitive advantage by using Big Data. Imagine being able to predict the hottest trends for the season in the busiest time of the year. Big data together with prediction models trends can be a very powerful tool to use. Business will be able to predict demand and target customers in a smart way. With this information, business can create value by adding insights for price optimization, having real time inventory data and other key aspects that are relevant to the business.

Big data is here to stay and to help businesses perform deeper analysis on all types of data. It helps finding meaningful patterns and insights in order to create competitive advantage, by being able to provide a smart shopping experience to customers.

Take a quick look to the video on how retailers could use big data in order to create competitive advantage.

http://www.youtube.com/watch?v=aZXVWOAcXjA

Is this plain creepy stalking or a big opportunity that’s still untapped? You decide.

Big Data is everywhere, Big Data is useful, Big Data is awesome. Yeah, yeah we hear you.
Watch this video, and you might just change your mind.

The video caters to any service provider who could potentially use Big Data to assess the effectiveness of his marketing campaign. For example, a cafè has just released a promotion of some sort, or opened a new store at a particular location. Or done both of them together and wants to find out if it has really worked or not.

In comes in the wonderful communications provider who provides all sorts of data to the cafè’s marketing department so that the cafè can examine the effectiveness of their campaign.

Data like – which route does John, your customer, who uses my communications service to tweet about your cafè takes to work? Does he stop by your cafè on the way or is it close to somewhere like a cinema that he had visited? And how many likes, reposts or other social platforms has he used to communicate this?

Wow, I think I’d be quite worried if a random cafè I was a patron of had this much information about me. The communications provider gives the cafè data about the route I take to their cafè? Is that sort of detail necessary? Personally, that comes as close to privacy invasion as anything can.

Then again, we are probably being too skeptical about this too quickly. Perhaps we need to be aware but not worried.
I’d like to quote a fellow, random internet user to conclude:
“I am an optimist, a humanist, and a futurist so I welcome our new digital age and all the good it can do for society. Technology is not the problem. The problem is how we use it.”

Can you trust the data you use? We tell you the truth.

Thus far, we have gone over how Big Data is extremely useful in analytical decision making and the cases in which it can have unwanted consequences.

Surely though, Big Data is not the panacea to all our problems. It comes with its own set of problems, one of the biggest ones being reliability of the data you use to make your decisions. Clearly, if you use the wrong set of data, the outcome is going to be an undesirable one. We will take you through the factors you need to go over before using Big Data for decision making.

Big Data's characteristics are usually described by using the 3Vs:

The above is a popular, ubiquitous 3V framework that is usually used to show the capacity and potential that Big Data can hold in terms of its speed, volume and variety for our decision making processes.

However, what may be the shortcomings of this process?

The decisions we make must be based on truthful data otherwise we will end up wasting our time, money and may have dire consequences. Hence, we put in the next V you need to consider VERACITY.

Example, you may have found the data on social networking sites possibly useful to decide which promotions to use to market your product. But social media data can be quite uncertain and unreliable, one may find it doubtful to project his/her sales based on the data from social media.

We also need to consider VARIABILITY of data. Do not confuse it with Variety, they are completely different. For example, the chocolate cake you order from the cake shop near you will be the same chocolate you order over the next 3 days. However, the chocolate cake may taste different on each of the 3 days. This is variability. In technology terms, it means the data is possibly undstrcutured or keeps changing rapidly. This can be a very worrying proposition for someone who has to make a decision on this sort of data.

The other V of data you want to consider is VALUE. Self-explanatory you might think but people forget this very often. You want to ensure that the data you use creates value for you and you need to ensure this by using data that correlates and is applicable to the business process and business decision you want to make.

Hence, all the data you use may not be 100% accurate. Some amount of it is bound to have some 'noise' because you want the widest sample size possible before you sort them. However, the truth is that you can only trust the data if you pick the right ones and understand completely to what purpose and how you will be analyzing and using the data. We need to able to understand the trade-offs of using certain vs uncertain data.

Big Data vs Business Analytics?

Big Data can change your world and we aim to tell you how over the next few weeks.

But before we get into that, lets take a step back and understand what the terms surrounding Big Data really mean.

Big Data, Business Analytics, and Business Intelligence are terms that are generally used to refer to processing data.

But is ‘big data’ just another way of saying ‘business analytics’?

The answer is an emphatic NO. 

Wikipedia defines Business Analytics as the “discovery and communication of meaningful patterns in data”. Business analytics has been in use since the late 1960s, when computer based information systems were used to support decision-making activities. Firms commonly apply analytics to business data, to describe, predict, and improve business performance.


For instance, Banks have long been using business analytics to differentiate customers by characteristics such as credit risk and usage. Similarly, Financial services firms have been using analytics to identify future growth trends on the basis of historic data.

Business Analytics needs data to identify trends. But the traditional business analytics software struggles with Big Data. Its tools were not designed to sift through massive data warehouses storing enormous data in a variety of different formats. Millions of dollars and enormous amounts of time and energy have been spent to develop these software programs, but it is still a Herculean task to identify meaningful data and ignore the useless bits.

The term Big data is self explanatory – it is literally data that is too big to be handled by conventional data management softwares. According to Edd Dumbill of O’Reilly media, Big Data is defined as “data that exceeds the processing capacity of conventional data processing systems. The data is too big, moves too fast, and doesn’t fit the structure of conventional database architectures. To gain value form this data, you must choose an alternative way to process it.”

In the coming posts we will start digging deep into the big data universe and explore other aspects of the big data landscape…

Stay tuned!

What is Big Data again?

Big Data is defined – literally – as large amounts of data that companies worldwide are gathering today. It is ubiquitous, prevalent in every industry, every sector and there is a world of technology that has been created to simplify all of this data in order to create value for the users.

But if all of this is just data, what is all the hype about it for, and why is this relevant to your life?

Imagine you walk into a coffee place that you visit frequently. However, unlike before, you walk in and a pretty blonde waitress greets you with your first name, immediately seats you at your favourite location (right by the window that looks onto a beautiful street), which happens to be empty. While you are still blinking and wondering how she knows your preferences so well, she surprises you yet again and asks you if you would like your favourite Irish nut coffee with whipped cream, exactly the way you always have it!

No, this is not a scene straight out of a movie.

This is exactly what Big Data has set out to do.

Did you know that 12 terabytes of tweets created each day are turned into improved product sentiment analysis? 

And that the best video games are produced after analyzing over 500GB of structured data and 4TB of operational logs daily?

Big Data has become an exciting scene in the world of technology.

It is about utilizing a world of information in the simplest manner to add to the user experience.

It is about speed; making processes efficient, especially for real-time applications. Think stock markets.

It is about innovation – adding variety and creativity to existing processes. Remember Google glasses?

And last but not least, Big Data is for YOU, it is for the future leaders, managers and CEOs of today. Big Data will give you the ability to make decisions quickly, rationally and the power to generate unique solutions for the rapidly changing global scenario.

Big Data is about adding value. Stay tuned in to our blog to find out how.