Big Data is bringing new business opportunities to companies around the world. We have officially entered this new age of Big Data, and it’s helping business, education, healthcare and more. This Big Data is offering vast amounts of information at rapid speeds, even in real time. And this information is fueling insights, leading to better decision-making. These better decisions enable huge savings, huge increases in sales, and happier customers. But big business opportunities do come at a cost.
Big Data is not really a new thing. It has been used for years and years; but it seems new because it’s something that is just now becoming affordable enough for it to be within reach for most businesses. Despite the decrease in costs, it still remains pricey.
Many companies are turning to software, such as Hadoop, in attempts to reap the benefits of Big Data, without the Big Cost. Although Hadoop is technically a free software, there are many costs associated with it.
The costs begin right away. The cost to set up the software is estimated at $9,000 a month, and takes around 4 months to do so. But the software isn’t the solution itself; you’ll need to hire a developer to develop the solution. But before you hire this developer, you’ll have to hire a business analyst to determine what question needs to be answered, or what hypothesis needs to be investigated. Then, he will tell the programmer what to code.
Another cost gets added if you have data from other systems that you need to import to your Hadoop cluster. Which is likely, as most companies have over 6 systems. In this case you will have to hire a database specialist to do this for you.
Finally, if you’re trying to get all you can out of the data, you will have to hire more data scientists and analysts. A business analyst alone is not effective when it comes to Big Data analysis.
So, it’s really not free. It’s actually estimated at just under $55,000 a month, according to this source.
But, this isn’t exactly fair, or attainable for small or medium-sized enterprises. Even though using data analysis always improves ROI, it is sometimes too large of an up-front cost for some companies – even if they wanted to, they couldn’t.
Luckily, there are options for companies that cannot afford this cost of set-up, maintenance and ongoing analysis. There are some companies that offer end-to-end solutions, however they do not offer their clients the best deal, as they are not customized to the company itself, they are a one-size-fits-all solution. But, there are a select few companies that truly do offer customized, end-to-end solutions at far less of a cost than these others. We did our research and found one for you, that offers customized solutions- in fact, they don’t even list their services on their website in advance. They wait to meet with you, learn about your business, and then tell you how they can help you.
But what’s even better is that they know that some are weary of putting that much cash upfront without seeing on a first-hand basis how it effects/benefits their company. This is why they have created a “special.” They will analyze one of your data sets, for a greatly reduced cost, reflecting a problem area in your company, to see how that analysis alone can help you. You can find more details from this blog about it.
89% of companies believe that if they do not develop and adopt a big data analytics strategy, that they could lose both market share and momentum.
Why? Because big data tells you things about the world, and about your business that you didn’t know before. And as more and more of your competitors adopt data strategies, they will learn more and more about your industry, putting you at a disadvantage. It is quickly becoming the “new thing” in business.
Luckily, it is quickly becoming easier and easier to adopt a big data strategy.
Step 1: What is Big Data?
The first step is to learn what Big Datareally is. Understand it first, in order to appreciate its value to your company.
Step 2: Get Comfortable With the Idea of Using Big Data
The definition may scare you, because it is a little mind-boggling and difficult to comprehend. However, it is not as big and scary as it seems. It is also not as costly as it seems. The Internet of Things (IoT) movement is making collection much easier, and the cloud is making storage much easier. Even analytics are becoming easier for companies of all sizes. If you don’t have enough money to spend on hiring a whole team of data analysts and data scientists, don’t sweat! There are firms out there that specialize in this that can analyze your data for a much lower cost than hiring a team.
Step 3: Ask Yourself These Questions to Develop a “Big Data Plan”
A good first question to ask yourself is, “what do we have?” Then identify what kind of data you think you are missing that you may need. This will help you identify what kind of data to collect. Many companies think that simply collecting a lot of data is a “data strategy.” However, data is only useful if it is relevant to your company. Furthermore, collecting a lot of data can make it more difficult for a data analyst to extract information and insight from that data. Having a lot of data makes the analyzing process more difficult, as they have to sift through all of the irrelevant information (and initially decide what information is irrelevant in the first place).
Next ask, “What assumptions do I have about my company?” This is a great question to ask, as it is a great starting point for companies that don’t have a big data analytics plan already in place. At this point, much of what you know (or rather, think you know) about your company are based on assumptions. You may have reports that tell you things, but this data can be manipulated and often comes from many, disparate sources. Because of this, you may not be getting accurate information.
Therefore, a good starting point is to test your hypothesis about your assumptions of your company. This also makes it easier for a data scientist to determine where to start…and you never know, along the way, he or she may find something else that will be useful.
As a data analytics and business process engineering firm, we find that these 5 things are the most common challenges that businesses face. They also greatly impede on the prosperity of the company. Watch this video to find out what they are. And check out more on http://cliintel.com
There are many small businesses out there who may feel that they are being left in the dust by all of these huge corporations using Big Data to get the upper hand. This does not need to be the case. Small companies can use Big Data even if they themselves are not generating it. There is so much data produced by consumers every day that is just sitting there waiting for the taking. Where would you find these reservoirs of data sets?
There is a huge pool of them out there, but here are just a few of the resources that could be tapped into to receive valuable data to benefit your business.
Google Finance offers a wide range of financial data on the stock market
I recently took a trip to the infamous Las Vegas and as I walked through the rows of flashing lights and sounds of slot machines I couldn’t help but think about the amount of data each casino must produce. In Vegas especially, casinos are packed full of slot machines seducing people to come test their luck and their money. With so many different machines to choose from, how do casinos know which slots to fill their floors with?
All of the slot machines are equipped with the bells and whistles of flashing lights and catchy tunes, so there must be some sort of sensory appeal that draws a person to one specific slot machine and not another. This is where Big Data comes in. Casinos can track which machines are more popular than others. The data can also determine if the slot machine remains popular even when people are losing money on it.
If people are losing money while playing on a slot machine and they continue to sit there, it must be a really great game. Well, what constitutes a great game? For some people it is the machines that have a fun theme, like a favorite movie or television show and for other people it is the quiet, straight forward keno games. Big Data can show casinos which machines are more appealing and even give them an idea of where to strategically place certain games to attract the most players. The more attractive a casino’s games are, the more money they will make, which is a part of why Big Data is heavily used in Las Vegas.
As for me I like the machines with interactive bonuses and games, but because of Big Data I’m sure the casinos already know this about me!
Big Data is slowly moving away from simply being a buzz word to a respected tool used in the majority of industries these days. Now that Big Data is becoming more easily manageable and a well known tool, new systems are being developed from it. Cognitive Computing is on the rise and is said by some to be the new buzz word of 2016.
Cognitive computing is a new system that mimics the way the human brain processes information. By teaching computers to “think” in a more independent manner as opposed to being told what to do can lead tounlimited possibilities. The more human like computers become, the less busy work humans must do.
Some people think that computers are better than humans because they are objective, but every technology out there originated in someone’s brain. It is important to remember how capable the human brain can be and to emulate that is the goal of cognitive computing.
Cognitive computing uses Big Data Mining, pattern recognition and natural language processing to process information and create an appropriate response. If we can teach computers to think like humans we can use them to do the dirty work that tends to be highly time consuming and free up the experts to do more important work.
Through the combination of Machine learning, big data and cognitive computing there is a very real future of companies becoming significantly more efficient and saving a lot of money. This lucrative field is on the rise and is something everyone should expect to see a lot more of in this new exciting year!
To learn more about how cognitive computing mirrors the processes of the human brain check out this interesting article!
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