Big Data has become very popular and therefore is being made into a “hype”. The Big Data hype gives the impression that Big Data is a magical tool that can be implemented into any company and voila!- instant solutions to all problems. Society has started to place unrealistic expectations on Big Data and the results it can produce.
It is human nature to project our interests onto others. Like the football dad who never made it to the big leagues, companies also place their desires into their data. This is why studies and surveys are supposed to be objective, because as soon as someone biases the data, the results are compromised. Big Data takes a long time to be analyzed properly to find relationships that can be translated into valuable information. When companies jump at the first correlation because it is in line with their desired result is when Big Data becomes biased.
It is extremely important to ensure your data is clean, or else it is going to lead to a lot of wasted money. Companies buy into the Big Data hype, purchase expensive big data technologies and hope that it is going to magically reaffirm all of their dreams and provide a golden staircase to them. This is not how it works.
Big Data is essentially a lot of information. When looking at a lot of information you cannot form a conclusion by simply looking at a portion of it. You must consider every piece of information and how it fits together. This is where Data science comes in. Many are moving away from the term “Big Data” because of the hype surrounding it and are embracing data science. Data science speaks more to the volume of analytical scrutiny big data must go through to provide any useful and unbiased results.
This is why we have data scientists, they are the geniuses who can look through mass amounts of data and find correlations without biasing them. If a company is going to spend the money on implementing big data they must also hire data scientists if they hope to profit from their investment.
The take home point to this would be that companies must allow the data to create new ideas and not try to drive the data with their own thinking.
There is data that can be found in every industry and profession out there- from healthcare to professional sports. If the legal profession is meant to be involved in all of these as well, one question comes to the front of my mind: how can big data help the legal profession?
Let’s start of by stating that there is so much data being collected around the world, and depending on how it is stored, catalogued and indexed, it can take a person days or weeks to sort through. Thankfully in today’s world, however, we have the luxury of programs and computers- computers that can go through this data instantly. Having these programs and applications accessible to us can instantly bring down the cost of analyzing the data, provided you get it into the right format.
Let’s take an example of a case involving product liability. There is a product that is defective. Where does big data come in?
Well now you have all of the records from the creation of that product: the memos, the mockups, and drawings. You have everything that had to do with the end product. You may even have the reviews and testimonials- good or bad. What would have taken months to go through by hand may now take an hour with some computer application. This is because the computer is going to search for certain words, and if the attorney picks the right words and the data is set up in the right format, the attorney now has everything they need at their fingertips. And all in a matter of minutes!
One may think it would be enough as an attorney to go out there and say ‘this product is defective and here are 500,000 complaints about it.’ The reality is that you can actually go one step further with the tools that are now given to us. The attorney can go back into all of the 500,000 complaints and determine what the common component is- and maybe that common component is user error. Then the tables suddenly turn and it is not the product- it is the user!
Big data can now help lead attorneys to answers that they may have never gotten a chance to come to with time and money constraints. Whatever side may be benefitting, information is power and big data is providing just that!
The student loan debt in the United States has reached $1.2 trillion and the average graduate is released into the real world $24,000 in debt. Does it sound like student loans are becoming a problem? I think it is safe to say, YES!!!!
As a somewhat recent graduate it is sad to see my generation accepting student debt as just a way of life. People constantly say, ” It”s good debt”. What?! There is nothing good about owing banks thousands of dollars. Not to mention that many undergraduate degrees these days do very little to actually land recent grads career worthy, well paid jobs. Many degrees don’t get graduates anywhere unless they go to grad school as well. It is difficult enough for a new graduate to learn how to live on their own, paying rent and bills, only to tell them they need to pay off their student loans quickly or else interest will bury them alive. Oh and this is all while making about a $30,000/ year salary.
Now that my rant is finished we can discuss if there is a possible light at the end of the tunnel for this crisis. Thankfully there are some new Startups that are helping re think the way student loans work. Traditionally student loans are granted based on credit score and have a very strict repayment schedule. New companies like Earnest are going against the lending rules and not considering credit scores when accepting borrowers. Instead, the new company looks at a borrower’s bank records, credit cards and even social media profiles to decide if they are a trustworthy person.
You may be wondering how a company can decide what makes someone a trustworthy person? Well, Earnest uses a big data approach, looking at many different parts of an individual rather than simply one credit score that may not fairly represent that person. Earnest takes the data a potential borrower provides and puts it into their underwriting program to find what they call the “highest quality clients”. Earnest’s philosophy is not over charging financially responsible individuals with high interest rates just because they wanted an education. Earnest also allows borrowers to pay in a much more flexible fashion, choosing the length and frequency of payments as well as the option of fixed or variable interest rates.
The reason Earnest can offer lower interest rates and flexible payment schedules is because of big data. The company uses big data to make quicker, more informed decisions on who to lend to, ultimately saving the client money by skipping and extra labor or middle men. It never ceases to amaze me how many different areas big data can be used in to create efficiency and reel in savings. Maybe if other lending companies adopted the big data approach to determine which of their clients are financially responsible then they could charge them less interest. This would be a great incentive for people to pay their loans on time every month!
Let us know what you think! Student loans are a heavily debated topic, we know you have an opinion, and odds are you have student debt as well!
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Everyone wants to save money. I have never heard someone say they would like to pay more for something. What is one great way to save money? Lowering your energy bill of course. Everyone has got one- wouldn’t it be nice to have a lower energy bill and use your extra money on things you actually want to pay for? Better yet, wouldn’t it be awesome to save money on your energy bill AND help save the planet?! You would feel like a great person- a great person with a little extra dough in your pocket.
How can you feel this great?
Big what? How does that work?
By using big data devices to monitor your energy and also receive stats on your energy usage
you can see where you can use less and conserve more!
We all like to think that we are doing all we can to help conserve energy and save the planet, but there is a lot of wasted energy we do not see. Through the use of Big Data analytics, energy companies can receive information on the amount of energy each household is using and send the consumer a usage report. This report can highlight wasted energy and inform the consumer of better ways to conserve their energy. By informing the consumer of their wasted energy, they will be able to adapt their habits to reduce their energy use and also save some money on their bill.
Another way to reduce unnecessary energy use in the household is to install a thermostat that is connected to the internet such as the Nest. Nest is a “smart” thermostat that learns the habits of the household and adjusts the temperature to ensure optimal efficiency. For example, a family may like their house to be sixty-five degrees in the summer while they are home, but when everyone leaves for work and school for the day, does the air conditioning need to keep the house at sixty-five degrees? No, unless you think your couch will get too warm without it. This is where Nest would turn off the air conditioning for the day, saving energy and money, and then return the house to your preferred temperature shortly before you return home.
These big data devices like Nest are a great way to ensure you are conserving energy without having to do the work yourself. I’m sure it also does a great deal to lower your bills as well, only using energy sucking devices when they are most needed. America has a long ways to go and much to change before being recognized as an energy efficient country, but these are some simple changes the energy companies and average families can do to help the cause!
Is Big Data for Energy a Reality?
Ecova is buying Retroficiency. Ecova specializes in software and services to help large companies save energy or to help utilities launch programs that will help their customers reduce energy.
Ecova Buys Retroficiency: Is Big Data for Buildings Finally Taking Off?
Calling All Building Owners – Crunching Big Data Can Save Energy
Researchers tell us that, in the United States, 20 to 30 per cent of a building’s annual energy bill is wasted.
Building operators walk a thin line. Operating a building requires that a perfect balance be struck between heating, cooling and ventilation. It also requires repair and maintenance of all the equipment and systems that allow that delicate equilibrium to exist.
New Data Sensors Saving Millions
Duke Energy says new sensors and ‘big data’ save millions in plant repairs.
And it allows Duke to use data analytics for everything from scheduling routine maintenance — learning how to read actual wear and tear on equipment instead of relying on rough operational hour estimates for needed work — to anticipating problems rather than reacting to them.
Using Cheaper Batteries for the Power Grid and Buildings
Utilities can use batteries to make the grid more stable, and to avoid building new expensive and dirty power plants that they only operate during times of peak power demand.
Building owners are also interested in buying batteries so that they can run buildings off of battery power when electricity rates from the power grid are high. Building owners can lower their monthly energy bills by switching onto battery power periodically.
Tesla batteries to power office buildings in California
BIG DATA PODCAST – 5 LESSONS ABOUT BIG DATA
Use Big Data to make information transparent.There is still a significant amount of information that is not yet captured in digital form
As organizations create and store more transactional data in digital form,they collect more accurate and detailed performance information on everything.
How can you leverage Big Data?
Visit the Data Talk Show : Big Data Podcast