Have you been noticing how the internet seems to know you? It is almost like you two are friends, knowing each others likes and dislikes. I guess it is kind of a one sided relationship, as the internet probably knows much more about you than you know about it. But that is a much more creepy analogy so let’s stick with the friends one.
Friends help each other out and always suggest products or places to each other, sharing information that would benefit one another. This is sort of what happens with the internet. The internet keeps track of what you buy or look at so it knows what products or interests to advertise to you.
Personally I find this saves me a lot of time. I have recently been planning a wedding and Amazon became my best friend. We would get together everyday. Amazon would listen to what I wanted to buy and then recommend other products I was completely forgetting about that went perfectly with the theme of my wedding. Amazon made it very quick and easy recommending the best products and even remembering my information so I didn’t have to find my credit card number for every purchase!
The reason Amazon is such a good friend is because ofBig Data, they collect my data like a dear friend listening to my needs and save it to better know me. I hate to say this but I’m not Amazon’s only friend, they have a lot of friends they do the exact same thing with! Thanks to Big Data, my relationship with Amazon has been an effortless joy.
Don’t waste money on services that don’t work or people who try to change who you are. If you believe in your company’s mission, don’t let someone try to change, learn how to take your beliefs and turn them into a profitable reality. We would love to listen to your goals and help you find the best way to achieve them!
Have you ever tried to put together a puzzle, but you cannot figure out how the 500 tiny pieces fit together?
Have you ever had an issue with your car, but cannot seem to figure out what the problem is?
These two problems both stem from the inability to see an underlying issue. It almost always takes someone else pointing out the problem for you to fix the issue. You cannot fix what you can’t see.
In the business world this happens all the time, a company is struggling and doesn’t understand why their revenue is decreasing. They grasp at ideas, maybe our product isn’t good enough, are our employees working their hardest, are we not making enough sales? Ultimately the company either reaches out for help or is drowned by their unknown problem.
Businesses like Cliintel are the detective that find a company’s hidden issues. It would be extremely difficult for the most self aware person to see everything others notice about them, which means it would be impossible for an entire organization to make the same feat. Cliintel’s slogan is ” Insights that add up to results”, can’t be much more clear than that, right?
Well Just in case, let’s dive into that. When a companies issues are brought to the surface they can begin to work on solving them. It is a lot like therapy for organizations. Step 1. Admit you have a problem. Once step one has been accomplished and the cause of the problem is diagnosed, it helps to have someone guide you though the healing process.
Cliintel is the friend who steps in and shows you that the reason your puzzle is not fitting together is because your 2 year old mixed the pieces with another puzzle. Cliintel is the mechanic that tell you that what you though was a dead battery in your car is really a faulty alternator.
What better way is there to learn about big data than listening to a podcast about it? I found a really great podcast recently that dives into all of the different aspects and current issues that we are dealing with when it comes to big data. There are also podcasts that help us understand the best ways to save and make money with your data.
Their most recent podcast, 5 Lessons About Big Data brought some interesting facts to light. These 5 lessons can help you to leverage the data that you already have, and ultimately, save you money:
Use big data to make information transparent.
Create and store more transactional data in digital form.
Big data allows for the segmentation of customers so that companies can better tailor products and services.
Sophisticated analytics improve decision making, minimize risks, and ascertain valuable insights that would otherwise remain hidden.
Big data can be used to develop the next generation of products and services.
The next step is for you to use all of these lessons to add value to your data and your company.
Any time a new model of technology comes out there is a huge hype about its potential and the infinite possibilities it possesses. New is exciting, it is unknown and holds hope for our wild dreams. The heartbreaking part is when these new technologies don’t live up to our impossible expectations. Many are skeptical of the hype surrounding Big Data and it’s potential, calling the excitement a “Data Fetish”.
Big Data seemed to come out of no where and hit the ground running with promises to solve every problem and make everything easier. This is difficult because to an extent Big Data has already proven to provide insights and results that allow companies to operate more efficiently. We must be realistic though, to think that Big Data is going to swoop in and cure cancer is a bit of a stretch. So how do we remain level headed yet allow ourselves to take risks with Big Data to hopefully achieve our goals?
We must think of Big Data for what it is- a tool. It is not some super hero, it is simply a device we can use with along side human critical thinking to produce better results. Big Data is access to information, it is merely a library that continues to organize the material in ways that allow us to see patterns. Once these connections are made, it is still up to the intelligent men and women around the world to take that information and apply it is a way that will produce results.
Those who have already fallen prey to the Data Fetish can protect their investment by remembering that Big Data is merely a tool. Companies must not constantly rely on the next Big Data program to deliver them to success. Companies must invest in their employees to work with Big Data to produce a desired effect.