There is a glass with water in it sitting on a table- is the glass half empty or is it half full?
The way you answer the question above may determine how you think about IBM’s new solution for the high demand for data scientists. Data scientists are people who can analyze and control analytical programs that work to sort through large masses of data.
As the amount of data the world produces increases, the need for people who can sort through that data and make meaning of it goes up as well. IBM believes that they can aid this problem with their natural language analytics program which is predicted to be able to do the job of a data scientist.
This provokes the question, is this a good thing? Is this a means to an end or is this the beginning of a war between humans and robots for jobs?
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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!
Big Data is arguably the hottest topic of the year. The people who drive this revolution -Data Scientists. Data scientists mine through mass amounts of data and find the connections that can then be translated into valuable information that would otherwise be very difficult to detect. For those who are smart enough to be a data scientist, it is quite the lucrative business.
So how valuable are Data Scientists?
The average salary for a data scientists is $118,000 a year. It doesn’t matter if you are a kid straight out of college of a distinguished individual, with a salary like that you are sitting pretty. Now, mining through data isn’t for the faint of heart. Finding meaningful relationships in a mound of data can be like finding a needle in a hay stack and can sometimes take a long time to uncover anything relevant. With that being said, those who have the training and the patience to succeed in this profession have the opportunity to work for some pretty fun companies.
Google has been rated one of the best places to work and they love their data scientists. Google prides themselves on knowing their users and being able to accurately market to individuals, which takes data and a lot of it. According to Glassdoor, Google pays their data scientists anywhere from $137,626 to $149,292 a year. With this type of salary on top of being able to work at one of the most well liked companies, I would say being a Data Scientist at Google would be a pretty great gig.
Facebook is arguably the biggest social media site on the internet today. The amount of data Facebook collects from its users is colossal, which means they rely heavily on Data Scientists. Have you ever wondered why the advertisements surrounding your Facebook page are eerily accurate to your interests and desires. From volleyball gear to engagement rings, Facebook advertisements always had me pinned. This is because the Data Scientists at Facebook take the information they gather from uses and sell it to companies, allowing them to more accurately market to unique demographics. Facebook pays their Data Scientists between $135,098 and $178,789 a year. Again, not too shabby.
IBM is the world’s largest information technology company and its products include hardware, multiple types of software, storage products, and customized microchips. Similar to Big Data itself, IBM has infiltrated almost any industry you can think of. IBM uses the best Data Scientists to partner with these different industries to make change happen and help lead those industries to better efficiency. IBM compensates its Data Scientists with a salary ranging from $108, 984 to $112,984. Sounds like a great position, being paid well, while also getting to work on some of the most innovative and new technology the world has ever seen!
These are just a few of the popular companies that utilize the brains of Data Scientist to make a difference in the world. Data Scientists are slowly improving many of the largest industries from oil and gas to healthcare and these changes will surely effect us all.
Let us know what you think about Data Scientists, are they paid too much, too little, or just right?
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