My Experience

Over the past almost two months or so, I have been blogging about the topic of big data analytics within a variety of different industries and how it is being utilize. I started this blog for a data analytics class at Sacred Heart University; and before entering this class I had no knowledge of really what analytics were or how much they are being used in today’s world. I have learned a lot through the research I have done for this blog and I hope that I was able to teach something to my readers.

Like everything in life, there are pros and cons to big data analytics. However, for some people one of the cons may outweigh any pro and that is the concern of security. I am however a little nervous about the amount of data collected about me. I don’t care if companies want to know what I am google to send me targeted ads, I do care about my personal information getting out. With hackers and really smart techy people, that information can easily get into the wrong hands. I’m sure that I am not the only person who feels this way. Especially learning how the healthcare industry plans to take advantage of data.    

I am not surprised how many industries are using big data, after what I have learned, I am shocked why some companies and industries are so far behind in applying the use of data analytics. With all the data that gets collected now, if analysed and implemented properly, it can and will increase revenue for every company. Along with increasing the revenue, big data will also help to determine trends and improve on products, services, and the overall customer experience. In a world of social media, a company's image is extremely important.

Fun Facts About Big Data

I have spent the past couple of months writing blog posts about big data in different industries. I have learned a lot about big data and how companies are using it to their advantage when making business decisions. In this blog post I thought I would share some interesting facts that I have come across.

Fact Number One:

“The data volumes are exploding, more data has been created in the past two years than in the entire previous history of the human race.” Honestly that is crazy to me. You think about all the information that companies have access to today about us that a couple of years ago they never had. Imagine how much will be collected in the future.

Fact Number Two:

“Data is growing faster than ever before and by the year 2020, about 1.7 megabytes will be created every second for every human being on the planet.” Like WHAT? If they are going to be creating that much data every single second they better start working now on making sure that they have great security because otherwise a lot of people are going to be worrying.

Fact Number Three:

“Bad data costs US businesses alone $600 billion annually.” That is a lot of money for companies to spend a year on information that is wrong. Even though companies can really benefit from big data, they can also lose a lot of money when it isn’t analyzed correctly or is used incorrectly. No industry, company, or organization is immune to it.

I could go on and on with facts about big data, but these were the three that i came across that really were interesting to me. It is crazy how far data has come and it has such great opportunities to be used in the future. The question isn’t is data here for good, the question really is are people ready for what is to come with data in the future? Honestly I think that people like their privacy and as data continues to get collected, privacy goes out the window.

http://www.datasciencecentral.com/profiles/blogs/15-astonishing-tweetable-facts-about-analytics

https://www.forbes.com/sites/bernardmarr/2015/09/30/big-data-20-mind-boggling-facts-everyone-must-read/#12a8203317b1

Why You Should Choose a Career in Big Data Analytics

Big data is the new thing, it is everywhere and companies are trying to keep up with all the data that is collected everyday but this is hard because of the volume. Companies are scrambling to analysis the data coming in as quickly as possible so that they don’t miss out on anything important that they can use to their advantage. Data analytics has now become a crucial part in business to make smarter decisions, improve products and customer experiences, and getting a leg up on their competitors.  

If you are trying to figure out what industry you want to go into, a career in data analytics is a great choice. With more and more companies now implementing big data, the demand for people to analyze it continues to increase because all the data is useless when you don’t have the knowledge and skills to analyze it.

There is a high demand for highly skilled data analysts, and big data jobs pay big money. The skills that you need to analyze data are very specific and companies are willing to train and invest the money in you because not a lot of people have the skills that are required. Someone is data analytics can make anywhere from $50,000-$165,000 and more depending on the company, what job you are doing, and your level of experience.

There are many different jobs someone can get within the field of data analytics. One option is to become a data analyst. Data analysts look at the data that a company collects and provides reports and visualizations to explain the data and what it may be hiding. This is done by using charts and graphs to make the data easier for everyone within a company to look at and understand instead of just looking at a bunch of numbers on a computer. For this role someone must have good knowledge of data manipulation using programs such as excel. A job as a data analyst is an entry level position due to the fact that they have a lower skill set than others in the industry and therefore someone in this position makes around $65k.

Other option is to be a data scientist. They make the data easy to understand by interpreting it, they collect the information they need to tell a story. Someone in this role fine-tunes the mathematical and statistical models that are applied onto data. They use their knowledge of algorithms and statistics to solve the problems and questions that they want answers to. A person in this position needs to have a lot of skills in order to be successful. Knowledge in mathematics, algorithms, statistics, and programming language like Python and R. As a result of having to have a large skill set, people in this role make $115,000 and up a year.

You could also be a data engineer, these are the techy, computer savvy people. They use computer science to process a large amount of data. They are responsible for cleaning up data sets, implementing requests that come from the data scientist, and focus on coding. Data engineers have a broad knowledge of programming language from Python to Java and more. The have to know programs like Hadoop and Spark that source data and process it so that it is useful to the company. They also need to know a lot about warehousing solutions and data storage which is why they are paid around $100,000 a year because they have a lot of skills they need in order to do the job.   

The QuinStreet research found that 77% of companies said that big data analytics is a top priority within their company to improve the performance of the organization. Big data is being used to make smart decisions on how to market, where to spend money, find the patterns and trends within industries and just be all around more successful as a company.

So with companies seeing the value in big data and starting to use it more, there is a big need for people in big data analytics. Not only is it a good paying career, but there will always be a need within companies to have someone who knows how to read and make use of all the data that is collected. So if you are a recent high school student heading off to college or someone in the work world that is looking for a career change; big data is the industry to get into now!

https://www.springboard.com/blog/data-science-career-paths-different-roles-industry/

https://www.edureka.co/blog/10-reasons-why-big-data-analytics-is-the-best-career-move

http://blog.udacity.com/2014/11/data-analysts-what-youll-make.html

Big Data Changing the World of Psychology and Research

Psychological research in the past has always relied on people completing surveys and questionnaires. However, when relying on people to fill things out, most people are not completely honest about everything which can lead to misinformation and research conclusions. When asked on a form “do you smoke cigarettes, if so how often?” Many people are not going to be honest, they will answer the way they think they should. People always want to portray themselves as better than they really are, but with big data now being used more and more, people are not able to lie as easily about their everyday behaviors.  

According to Eric Schmidt, the CEO of Google, “every two days now we create as much information as we did from the dawn of civilization up until 2003.” That is a lot of data, however if it is not analyzed properly and understood then it is useless. Since data analysis is fairly new, it will take a lot of time and people to sort through all the data that has been collected and make sense of it.

With all this data now available, it has the potential to change the way psychological scientists observe human behaviors. Big data means that the field of psychology can work faster, more efficiently, and reveal new things that they never thought was possible before. With the help of existing databases, wearable devices, social media, and smartphones, researchers are able to collect data that they never had access to before.

Michael Jones, a researcher at Indiana University Bloomington stated that, “each little piece of data is a trace of human behavior and offers us a potential clue to understanding basic psychological principles. But we have to be able to put all those pieces together correctly to better understand the basic psychological principles that generated them.” Jones is utilizing big data to help in his research on language development, specifically in infants and children.

“Big Data might help researchers get to a point where they can collect behavioral information without sampling human participants at all,” said Tanzeem Choudhury, an information scientist at Cornell University. As technology continues to advance, more and more data will be collected and eventually it will get to a point where researchers will get continuous updates of people’s behaviors and patterns. As a result, researchers will no longer have to bother people to fill out surveys and questionnaires, they will be methods of the past.

Tanzeem has been a part of a number of different developing smartphone apps that use big data to help with little everyday things to improve people’s lives. MyBehavior is one of the them, which looks at your physical activity patterns and then suggests ways to stay in shape. For example, taking hikes at locations that the person seems to enjoy. The next one that i thought was very interesting is called StressSense. This app will track where and when they experience the most stress throughout their day to help them avoid anxious situations. The last is called MoodRhythms which will help people who have bipolar to monitor social interactions and sleep to help maintain the person’s energy levels and keep their mood balanced throughout the day.

Big data can always be used by researchers to look at past research and get a fresh perspective on things. It could also help to support or abandon past theories and conclusions in the field of psychology. Researchers no longer have to rely on people’s word, the have clear data that is collected of behavior and patterns that may not line up with the things people say on paper. So it will help to get the raw truth.

Big data has been used a lot to help market and advertise brands and companies. However, it is really nice to hear that researchers and psychologists are able to utilize all this data that is collected in order to improve lives and make a bigger impact. Hopefully in the future, psychologists and researchers will be able to have all the information they need to prove ideas and theories not only in the future, but also for research that has been done in the past.

http://dataconomy.com/2016/04/big-data-tackles-personality-behavior-psychology/

https://www.psychologicalscience.org/observer/what-big-data-means-for-psychological-science#.WRtgXOvyuUk

https://www.forbes.com/sites/martinzwilling/2015/03/24/what-can-big-data-ever-tell-us-about-human-behavior/#6bd7eb5c61f9

https://techcrunch.com/2010/08/04/schmidt-data/

5 Steps to Protect your Data (Part 2)

3. Delete Browser Cookies

It is no surprise that your internet browser tracks all the websites that you visit while online. This digital footprint that you leave behind every time you search the web is used to create a personal folder about you and what your interests and preferences are based on your internet history. From this data that is collect, companies can use this information to tailor specific offers and advertisements to you. Some think that this is a benefit but it can get annoying as well. The simple fix to not have companies bothering you with advertisements is to delete your browser cookies multiple times a day to make surveillance more difficult.   

4. Be Careful of Mobile Apps

Our smartphones are stalking us also. There are apps for everything now, you want to know what song is playing, there is an app for that. You want to know what time your train is coming, there is an app for that. Most of these apps collect a lot of data, including your pictures, emails, contacts, and so on. The plus side is that these apps do ask for permission to collect this data, so be aware of what your apps are asking for and what you are saying okay to.

5. Limit Social Media Usage

Every millennial loves using their social media. Do it for the insta! Well, like everyone knows, once it is online that’s it. We all love sharing our lives and pictures on social media sites, be very careful because all this information is collecting data about your life. Personally, I don’t really do any shopping online but I follow companies on social media and like pictures and in turn, I get a lot of advertisements popping up. Everything you like on facebook, every tweet, every tag, it can be seen by everyone. Social media is the easiest and faster way to collect data about you. In order to protect your privacy, you need to limit the amount that you use social media. I know it might be hard to do this, but this is where a lot of data is collected.

There will never be a way to completely protect your personal data. As technology continues to advance, more data will be collected. There is no hiding from data unless you never touch a computer or phone and even then data can still be completed. However, these last two blog posts are 5 ways to limit the amount of data collect and protect your own privacy and information as much as possible.

http://www.alecbjazz.com/5-hacks-for-avoiding-big-data-surveillance/

5 Steps to Protect your Data (Part 1)

Big data is all around us whether we are aware of it or not. Everything you do on the internet, every single search is collected and can be used to help companies market products and services to you. It isn’t just companies looking at this data, the government looks at it too. The scary thing is, they actually collect very accurate data that can say a lot about who you are. With data being collected and used more and more today, people are becoming very concerned about having personal information collected about them. People are now trying to find ways to prevent the amount of personal data that is collected on them. If you are the kind of person who cares about the data that is collected about you, below are five ways to limit your internet footprint.

1. Use Privacy Enhancing Technologies

Privacy Enhancing Technologies (PET) will not completely stop surveillance from happening, however it can make it more difficult to get access to the monitor. PETs can be as easy as a browser plug-in, some of these simply block websites that track your activity. This is an easy way to not have all your activity on websites tracked. The reason for PETs is to allow users to protect the privacy of all of their personal information.

2. Use Virtual Private Networks

This is very similar to the PETs, however many Virtual Private Networks (VPN) are free and easy to use for people like me who are not tech savy. The VPNs can be downloaded as browser extensions or plug-ins. Things like this are fairly easy to use because all you have to do is download them and then they do their job. VPNs wears a hat as an intermediary server between you and the website that you are busy.

Keep your eyes out for my next blog post, where I will discuss the three other steps you can take to protect your personal information and the amount of data collected about you.

Big Data in Big Travel

 

The internet has opened up a whole new world for people. Customers now demand personalized experiences with great customer service and they turn to the internet to voice their opinions and reviews of different products and services. Therefore companies need to always put their best foot forward so that customers return. This is true for every industry but especially the travel industry.

The travel industry has access to a wide variety of data from different actions and sources, such as itineraries, reservations, transportation, cancellations, inquiries, customer feedback, price, geolocation and so on. Big data is now being used by travel companies to wisely process all this data in order to target campaigns to different types of customers. Companies are able to make more money because they are using the data to produce better products and services leading to a better customer experience. In this post I am going to discuss some of the ways that the travel industry is optimizing their data.

Personalization

As someone who loves to travel this one is huge to me. Planning a trip can be very overwhelming with all the different options for flights, hotels, locations and so on. So the fact that travel companies are personalizing the travel experience will definitely bring in the dollars. When you travel you leave behind a data trail of your personal preferences, behaviors, previous interactions, and reviews and pictures on social media platforms. All this information can be useful to companies so that they are able to offer service that fit a person’s needs and wants, for example, offer hotels that have shuttle services to the airport. Making the travel experience personal to each individual person increases customer loyalty which every company knows is very important.

Pricing

As a recent college graduate who loves to explore, finding the best price on flights and accommodations is the most important thing. I will not stay in one hotel if it means there is one that is even cheaper. For me, the hotel is the place you sleep and that is about it, so the cheaper the better. Many people have the same mindset, they will pick on location or flight over another based solely on price. Travel companies are using data analytics to track and analyze competitors prices to notice trends from multiple sources. Kayak uses analytical models to make sure that the airplane ticket prices are the same on their site as they are on the airline sites. Companies like Kayak and Tripadvisor have made comparing the prices of flights and hotels extremely easy.   

Competitive Differentiation

With all the different types of companies within the travel industry, setting your company apart from the others is very important; this is when big data comes in. A Global Distribution System called Amadeus, has features available such as ‘feature results’ and ‘extreme searches’. This system gives travelers the ability to get very specific results to their questions without even having to submit them. Questions like “what is the cheapest flight to Ireland?” or “Can I fly out of the United States for $600?” One company that has seen good results from utilizing data is British Airlines. They are using the information on their website to offer exclusive and relevant offers to their most loyal customers. Getting your company to stand out from the crowd is extremely important in the travel industry since there are so many different companies to choose from whether it is airlines, hotels, you name it.

All of this shows how big data has reshaped the travel industry. The use of big data is not only making the customer experience better and easier, it is also improving the services, products and overall sales for companies in the travel industry. This is just the beginning of the use of big data in this industry, they still have a lot more that they can/ will do.

https://www.exastax.com/data-analytics/how-big-data-analytics-is-transforming-the-travel-industry/

https://www.forbes.com/sites/centurylink/2014/04/30/how-big-data-is-transforming-the-travel-industry/#5873d2fc56f0

Recruiters Need to Get on the Data Wagon

Finding the perfect candidate for a job in a company is a lot like finding your true love. There are so many people but it isn’t always the perfect match. Just like dating sites are using big data to match people up, recruiting needs to begin using big data to match up a candidate with their perfect job. Why is it that so many recruiters are still having to follow their gut feeling about a candidate when there is so much data available, and so many different tools to help analyze it? Yes, it is true that when it comes to recruiting, the relationship you develop with a candidate is an important part. However, with the use of data recruiters can stop wasting time on the bad candidates and get to the perfect candidate more quickly. Data analytics is all about looking at behavior, and in recruiting behavior is huge. Data can help answer questions such as what are your applicants doing? How are they being found? How many days does it take from start to finish to fill a job? How many positions do we have? These are all important factors that would be helpful for recruiters to have the answers to. There are many Applicant Tracking Systems that helps recruiters look at the company’s data and statistics but they need to utilize the information and tools that are available to them.

http://www.yoh.com/blog/big-data-recruiting-smarter-not-harder

https://www.wired.com/insights/2014/01/big-data-brings-big-changes-recruiting/

Big Data Fighting Big Crimes

In the world we live in today, criminals are everywhere and there is a huge pressure on law enforcement to keep communities safe. With the advancements of technology in the past several years, specifically the use of data analytics, law enforcement is now able to fight, solve and even prevent crime far more accurately. Data makes it possible for agencies to identify crime patterns on a very detailed level in a safe and secure way. Law enforcement agencies are using a program called Microsoft Azure Data Lake to store data such as video, images and text in one single storage location. Police officers then use the Microsoft Cortana Analytics in order to analyze all the data that is collected. Officers are using these tools to predict, anticipate, and even prevent crimes. That is so crazy that with the help of data, officers can predict human behaviors and criminal patterns and act before a crime is even committed. Imagine how many lives can be saved if they are able to do this accurately. The Los Angeles police department has reduced burglaries by 33 percent, violent crimes by 21 percent and property crimes by 12 percent since they starting using big data models. Big data is also being used to identify white collar criminals involved in financial crimes such as insurance fraud, money laundering and others. Big data has opened up a new way to effectively fight against crime, and although it hasn’t eliminated crime completely from our society, it is helping to keep the streets more safe than ever before. As we learn more about big data, law enforcement will continue to find new ways to use the data collected to their advantage. I would love to live in a world where I don’t have to worry about all the strangers who walk around me, and maybe with the help of data this could be possible one day. Only time will tell.          

https://enterprise.microsoft.com/en-us/articles/industries/government/fighting-crime-with-big-data-analytics/

http://bigdata-madesimple.com/how-big-data-helps-us-in-the-fight-against-crime-beyond-minority-report/

Data is Finding Your Soulmate

With about 9% of American adults turning to online dating sites to find love, and now 33% of marriages involved some form of online dating. With these numbers, it is no surprise that data is playing a significant role in this industry. You walk into a bar now and sit down, and instead of people looking around and trying to meet people around them, they pull out their phone and open Tinder. It blows my mind that dating sites ever existed before data analytics.

Data can be collected many different ways. The most common way is by having the users of the site fill out questions to help explain who they are as a person, like interests, dislikes, passions and other important and helpful information. This sounds simple and easy right? WRONG. Some of these dating sites can have 400 plus questions to answer touching on a wide variety of topics from favorite music to political views. That is a lot of questions, but dating agencies said that they need all this information because the more data they have, the more successful they can be in finding your soulmate. Online dating business generates more than $2 billion dollars a year, so using the data collected correctly is very important to the future and reputation of the dating agencies.

The questionnaire definitely helps to collect data, but I think you can guess the biggest problem that dating agencies run into. If you guess that the issue is that people are liars on dating sites, you’re correct. We have all heard those nightmare online dating stories where they looked one way in their picture but totally different in person, or they say they are one age but are actually older. People lie, which is dumb because those people are on there usually to find love, which means people are eventually going to meet you. Studies have shown that people tend to lie most about their physical appearance, weight, height, age and even their income. When people lie it obviously is generating inaccurate data. Dating agencies are well aware of this flaw in the way people present themselves and try to get around it. They try to grab data from other sites such as Netflix, Facebook and online shopping sites because this data tends to be more accurate. They also watch the users behaviors while on the dating site and what profiles they view in order to get a better idea about what/ who the user is interested in.   

Match.com is using facial recognition technology to determine user’s “type”. The company says that even if people do not have a preference for height, hair color, race, or eye color. The company says by analysing the faces of users exes, they can figure out the person’s type and match them up with people they are more likely to have a physical attraction to. Match.com hopes to master this so that they can have something to separate them from competitors. It’s like they are finding literally everything you want in a person just by asking a bunch of questions and stalking your exes. This service is not cheap but it is worth the investment if it means matching people with not only the same interests, but have some type of physical attraction to each other.

Online dating websites still have a long way to go in terms of data. They need to fine tune their algorithms to make better matches. They also need to find different ways to collect data while filtering out the information that is not accurate. Just like every other industries, they also have to make sure that there is secure privacy and people are not able to hack in and gather people’s personal information.    

Big Data is a Lifesaver

Imagine if big data was able to help to save people’s lives… well this isn’t far off. Besides using data to cut down on costs, big data in healthcare is being used to predict epidemics, cure diseases, improve quality of life and avoid preventable deaths. With the advancement of technology and medicine as well as people living longer, the way we are receiving treatment is rapidly changing. The focus now in healthcare is to know as much about a person as early on in life as possible. Cell phone apps and wearable devices for monitoring health have become very popular over the recent years, and very soon patients will be able to share all this information directly with their doctors. This data will be compared and analyzed alongside thousands of others identifying specific threats and issues from patterns that emerge through comparisons.

Soon enough the interaction between a patient and a doctor will be different as well with the use of big data. We all know how it works, you call the doctor office and make an appointment and then sit there waiting sometime over an hour until the doctor sees you. This will soon be something of the past. Instead, you will soon be able to receive medical attention remotely from the comfort of your own home. We all have that one friend who freaks out whenever they get a headache and they go to the doctor. Soon they will be able to save some gas and not have to make weekly doctor visits.

Although these changes can be very beneficial and prevent future illnesses, there is the issue of privacy and personal information potentially getting hacked. Let's be honest, there is nothing more personal or revealing than our medical records. They will have to make sure that the information is heavily secured. Despite the potential bad that can come from big data in healthcare the good definitely outweighs the bad.

https://www.forbes.com/sites/bernardmarr/2015/04/21/how-big-data-is-changing-healthcare/2/#35500304140c

  

Data changing the way college students schedule classes

Big data is now being used in higher education to help universities to improve students all around college experience. The focus so far with data has really been on retention and graduation. As a recent college graduate I can easily remember how stressful it was scheduling classes, I wanted to make sure I was taking classes I would enjoy as well as classes that would still count for my major and graduation. I have so many friends that ended up having to do a fifth year because they took classes they thought counted for their major but didn’t. This is the reason a lot of people end up dropping out of college because they end up getting too far behind.

Ever since Arizona State University started using predictive-analytics almost a decade ago, the graduation rate has gone up 20 percent. One tool that Arizona State and many other universities are using to help retention rates is a program called College Scheduler. This is like Match.com for students. When students use College Scheduler the first thing they do is fill out personal information on the dashboard and then the program gives options for classes that work with your personal and academic schedule. It is now super easy for students to build their class schedule around obligations that they already have and that they know count towards their major. Aside from this making it a lot easier and less stressful for students, it has been proven to raise the rates of the amount of students who graduate. I just graduated last year, and I think that this would have been an excellent tool for my university to have accessible to students. Especially for students who have to work part time in order to pay to go to college. Not only does the system give you the options of what classes to take when, it goes a step further to suggests classes that you would most likely be interested in based on your personal information.

Some students may still want to meet with their advisors every semester to make sure that they stay on track, it all depends on the person. Personally I never met with my advisor for scheduling but my major was psychology so there were a lot of classes that worked towards my major and not too many required classes, however a student who is a nursing major may have a lot of required courses they must take in order to graduate on time. Universities could use data in so many different aspects to take some of the extra stress off students and faculty.  

https://www.theatlantic.com/education/archive/2016/11/the-colleges-are-watching/506129/

https://infocus.emc.com/william_schmarzo/what-universities-can-learn-from-big-data-higher-education-analytics/

How data is helping the Fashion industry

In an industry like fashion, where things go out of style just as quickly as they came in, data is extremely important. With the fashion industry being as unpredictable as it is, data can really help to show the trends in fashion as well as what customers like and dislike. With the internet and social media being used so frequently, fashion companies now are posting their exclusive lines on Facebook, Instagram, Twitter, Pinterest, before anyone else sees it. Then they use sentiment analytics from likes, shares, comments, re-tweets collected to understand the customer demands. As a fashion designer and a clothing company, it is difficult to be successful if you aren’t aware of the latest trends.

Julia Fowler, a fashion designer, struggled a lot with the lack of knowledge about the latest trends and she decided to do something to change this. She left her designer days behind and became co-founder of EDITD which helps fashion designers predict the latest fashion trends using big data. EDITD collects fashion trends and sales information from various different web platforms, social media, retail websites, designer runway reports, fashion blogs and then makes it available in real-time. The well known fashion brand Asos, increased their sales by 33% after they started using the data analysis services provided by EDITD. Julia Fowler said that “a product on sale/ discounted is the result of wrong decisions” but now that companies know the trends and their customer’s demands, sales willing increase and less will end up going on sale. The success of Asos is a great example as to how helpful this tool is to the fashion industry.      

http://fortune.com/2014/09/22/fashion-industry-big-data-analytics/

Data and Facebook

As we all know, Google has collected enough data about us to have detailed information about our lives. What other website do we all use just as much as Google…. Yep, you guessed right, Facebook. The Social Media Marketing Industry report in 2015 stated that Facebook was the number 1 social platforms for marketers. Facebook has a lot of detailed information about their users thanks to data. Facebook knows our lives, our likes and dislikes, our friends, where we are, what we are doing, what we look like and so on. Now, when you put a picture up on Facebook and go to tag someone Facebook already has them as a suggestion to tag, thanks facial recognition. Have you ever been looking through Facebook and then decide you want to do some shopping? You go open a new tab and begin shopping your favorite sites, but wait, I don’t really have $100 to spend on those beautiful pointed toe heels I came across. So you make the adult decision to exit out of the tab and return to your Facebook browsing. Well now those beautiful heels are haunting me on Facebook thanks to their tracking cookies they have installed to track my web activity while on a different tab. Facebook can apparently also accurately predict my satisfaction with life, intelligence, religion, sexual orientation, emotional stability, drug use and alcohol use, gender, age, relationship status, race, political views, and probably the sex of my future unborn baby. They do this through simply analyzing the things that you ‘like’ on the site. Facebook is like that crazy stalker girlfriend that just won’t let you forget anything in your life. Yes, I liked an article about the struggles of being single, thanks for reminding me everyday since that I am in fact single, appreciate the constant reminder of that Facebook. It really is crazy how sites like Google and Facebook can know when you are cheating on your spouse months or even years before your spouse ever finds out. However, like I have discussed in one of my previous blog posts, they must be smart about how they use all this data otherwise it is just plain creepy.

https://www.simplilearn.com/how-facebook-is-using-big-data-article

Monetization of Analytics Data

Data monetization is the process of unlocking the financial value behind data. With all of us turning to the internet everyday, companies have access to a ton of data that can really help them to make a lot more money than they did before. Monetization isn’t just a way of making money, it also allows companies to save money and even cut costs to make spending more effective. When companies collect data about customers, they can sell it or charge a fee for others to access it. In order to monetize from your company’s data, it is important to use the information gathered from the data correctly. The following are four ways on how a company can internally monetize their company’s data.

The first way to monetize data is targeted offers; this may be pretty obvious however for those of you who are new to data this is important to know. The overall purpose of data is to make it easier for companies to make smarter marketing decisions based off of the data they have collected. The best way to monetize your company’s data is to simply divide your audience into sections and target them based on their interests, demographics, browsing behavior, buying patterns and so on.  

The second way to monetize data is by having advanced analytics. As I am sure you can imagine, companies collect an overwhelming amount of data everyday which means that traditional methods no longer work as well as they once did. In order to get the most out of the data, it is important to have advanced analytics to really optimize the information. When it comes to data, speed and volume go hand in hand. The more amount of data that comes in, the faster it will need to be analyzed. Therefore, the more advanced the analytics are, the more you can utilize the data that is collected.

The third way to monetize data is by retargeting. When a customer comes to your company’s website, it is because they are already somewhat interested in what you do or sell. However, research has shown that before customers buy anything or become loyal to one specific brand, they have been influenced by the brand via multiple different touch points. Retargeting can help companies reach new customers.

The last way to monetize data is by simply getting closer. A big mistake that companies make is when they first set up their company’s website, they install google analytics or some other type of tracking software and then they never really look back. The data that is collected by these softwares are important and should be used. Not only can they help companies to expand to a bigger audience, they also help companies get to know their existing customers on a more in depth and personal way. Getting new customers to look at your site is easy, but getting them to stay is not as easy. The data that is collected gives companies an insight to who their customers are and what they want, and in order to monetize data companies need to keep their already existing customers.

There are many ways to monetize data externally however I think that it is more important to look at the ways to do it internally. It’s crazy to think about how much work it takes for a company to be able to use the data that is collected. The first steps are easy, create a website, have some type of tracking software attached to it and you are good to go, right? Wrong! There is so much more that has to happen beyond that. Although optimizing all the data collected is not easy, it is definitely worth it for companies to do because when it is analyzed and used properly, it can bring in a lot of money.

http://www.informationbuilders.com/blog/terri-white/20053

https://datafloq.com/read/4-ways-how-monetize-big-data-your-company/2020

Data and Privacy

Data and Privacy

It is no surprise that as data analytics continues to develop, companies will learn more and more information about consumers, including private information about them. Companies need to be really careful about using the data they collect appropriately, otherwise it can really be creepy. Every time I get into my car now at work, my phone comes up with an alert telling me how long it will take me to get home. It started doing this after my first week on the job, and honestly, it kind of creeps me out. I know very well that google has a lot of information on me, but I like to not think about it.

Every time you go shopping you allow companies to gather intimate details about your consumption patterns. Companies can use this information to their advantage but need to be really careful in doing so. The company that learned this lesson the hard way was Target. The marketing analytics team at Target correctly guessed the pregnancy of a teenage girl in Minnesota, based on a formula involving the rates of buying cotton balls, unscented location, and mineral supplements. From this information, Target started sending her coupons that were geared toward baby products. Which in turn is how her father ended up finding out about her pregnancy. Her father went to Target demanding to speak to a manager, saying “my daughter got this in the mail! She’s still in high school, and you’re sending her coupons for baby clothes and cribs? Are you trying to encourage her to get pregnant?”

Although Target ended up being correct with the information they collected about this girl being pregnant, this is a lesson all companies can learn from. Just because they were correct that time doesn’t mean that each person who buys those products is pregnant. Data analytics has gotten to the point where companies now have enough data to figure out personal information about people based on patterns. How scary is it that, in this world of data, Target knew about a teenage girl’s pregnancy before her own parents, who live with her. Start shopping with cash my friends if you are buying things you are embarrassed about, or trying to hide.

https://www.forbes.com/sites/kashmirhill/2012/02/16/how-target-figured-out-a-teen-girl-was-pregnant-before-her-father-did/#10dbdc626668

http://www.slate.com/blogs/how_not_to_be_wrong/2014/06/09/big_data_what_s_even_creepier_than_target_guessing_that_you_re_pregnant.html

Four Types of Data Analytics

Four Types of Data Analytics

1) Descriptive

Descriptive analysis, also known as data mining, is describing what happened. It looks at past events for insight on how to approach things in the future and to uncover patterns over time. Descriptive analysis is known as being the easiest type because it allows you to change big data into bite-sized pieces to make it easier to understand. Descriptive models analyze a variety of different relationships between products or customers.

2) Diagnostic

Diagnostic analysis looks at past patterns to discover or determine why something happens. Once a business figures out the why behind something, they can use that information to their advantage and make the changes necessary to be more successful. This type of analytics gives decision makers at organizations real actionable and difference-making insight.

3) Predictive

Predictive analysis looks at past data patterns and comes up with a list of different outcomes for situations. This is very helpful for setting realistic and reachable goals as well as planning and girding your expectations. Properly tuned predictive analysis can be used to help support sales, marketing, and other types of complex future events.

4) Prescriptive

Prescriptive analysis provides the actions that should be taken and what steps are recommended. Prescriptive analysis is like predictive analysis, expect it goes beyond just predicting, it gives the likely outcomes for several different scenarios.  

When combining these four different types of data analytics, the data turns from pointless numbers to important information that can tell a story. It can describe what happened, why it happened, what could happen, and what should happen. All four of these pieces are important for businesses to know in order to grow.

http://www.ingrammicroadvisor.com/data-center/four-types-of-big-data-analytics-and-examples-of-their-use

http://www.rosebt.com/blog/descriptive-diagnostic-predictive-prescriptive-analytics

http://www.smartshifttech.com/big-data-and-analytics-which-type-analytics-does-your-business-need

http://www.insightsquared.com/2014/11/4-types-of-analytics-you-cant-survive-without/