Summary: As data continues to grow, businesses now have access to (or generate) more data than ever before–much of which goes unused. How can you turn this data into a competitive advantage? In this article, we explore different ways businesses are capitalizing on data.
We keep hearing statistics about the growth of data. For instance:
- Data volume in the enterprise is going to grow 50x year-over-year between now and 2020.
- The volume of business data worldwide, across all companies, doubles every 1.2 years.
- Back in 2010, Eric Schmidt famously stated that every 2 days, we create as much information as we did from the dawn of civilization up until 2003.
The big questions: Where is this data? How can you use it to your advantage?
In a previous article, we answered the first question. Data exists all around us, often in places we wouldn’t expect. Businesses generate (or have access to) far more data than they realize. Much of this data goes unused.
Today, let’s focus on the next question. How can you use this data to your advantage?
If you want to capitalize on this data, you must first begin storing it somewhere. But, how can you store and process massive data sets without spending a fortune on storage?
That’s where Hadoop comes into play.
Hadoop is an open-source software framework for storing and processing large data sets. It stores data in a distributed fashion on clusters of commodity hardware, and is designed to scale up easily as needed. Hadoop helps businesses store and process massive amounts of data without purchasing expensive hardware.
The great advantage of Hadoop: It lets you collect data now and ask questions later. You don’t need to know every question you want answered before you start using Hadoop.
Once you begin storing data in Hadoop, the possibilities are endless. Companies across the globe are using this data to solve big problems, answer pressing questions, improve revenue, and more. How? Here are some real-life examples of ways other companies are using Hadoop to their advantage.
1. Analyze life-threatening risks
Suppose you’re a doctor in a busy hospital. How can you quickly identify patients with the biggest risks? How can you ensure that you’re treating those with life-threatening issues, before spending your time on minor problems? Here’s a great example of one hospital using big data to determine risk–and make sure they’re treating the right patients.
“Patients in a New York hospital with suspicion of heart attack were submitted to series of tests, and the results were analyzed with use of big data – history of previous patients,” says Agnieszka Idzik, Senior Product Manager at SALESmanago. “Whether a patient was admitted or sent home depended on the algorithm, which was more efficient than human doctors.”
2. Identify warning signs of security breaches
What if you could stop security breaches before they happened? What if you could identify suspicious employee activity before they took action? The solution lies in data.
As explained below, security breaches usually come with early warning signs. Storing and analyzing data in Hadoop is a great way to identify these problems before they happen.
“Data breaches like we saw with Target, Sony, and Anthem never just happen; there are typically early warning signs – unusual server pings, even suspicious emails, IMs or other forms of communication that could suggest internal collusion,” according to Kon Leong, CEO, ZL Technologies. “Fortunately, with the ability to now mine and correlate people, business, and machine-generated data all in one seamless analytics environment, we can get a far more complete picture of who is doing what and when, including the detection of collusion, bribery, or an Ed Snowden in progress even before he has left the building.”
3. Prevent hardware failure
Machines generate a wealth of information–much of which goes unused. Once you start collecting that data with Hadoop, you’ll learn just how useful this data can be.
For instance, this recent webinar on “Practical Uses of Hadoop,” explores one great example. Capturing data from HVAC systems helps a business identify potential problems with products and locations.
Here’s another great example: One power company combined sensor data from the smart grid with a map of the network to predict which generators in the grid were likely to fail, and how that failure would affect the network as a whole. Using this information, they could react to problems before they happened.
4. Understand what people think about your company
Do you ever wonder what customers and prospects say about your company? Is it good or bad? Just imagine how useful that data could be if you captured it.
With Hadoop, you can mine social media conversations and figure out what people think of you and your competition. You can then analyze this data and make real-time decisions to improve user perception.
For instance, this article explains how one company used Hadoop to track user sentiment online. It gave their marketing teams the ability to assess external perception of the company (positive, neutral, or negative), and make adjustments based on that data.
5. Understand when to sell certain products
“Done well, data can help companies uncover, quantitatively, both pain points and areas of opportunity,” says Mark Schwarz, VP of Data Science, at Square Root. “For example, tracking auto sales across dealerships may highlight that red cars are selling and blue cars or not. Knowing this, the company could adjust inventory to avoid the cost of blue cars sitting on the lot and increase revenue from having more red cars. It’s a data-driven way to understand what’s working and what’s not in a business and helps eliminate “gut reaction” decision making.”
Of course, this can go far beyond determining which product is selling best. Using Hadoop, you can analyze sales data against any number of factors.
For instance, if you analyzed sales data against weather data, you could determine which products sell best on hot days, cold days, or rainy days.
Or, what if you analyzed sales data by time and day. Do certain products sell better on specific weeks/days/hours?
Those are just a couple of examples, but I’m sure you get the point. If you know when products are likely to sell, you can better promote those products.
6. Find your ideal prospects
Chances are, you know what makes a good customer. But, do you know exactly where they are? What if you could use freely available data to identify and target your best prospects?
There’s a great example in this article. It explains how one company compared their customer data with freely available census data. They identified the location of their best prospects, and ran targeted ads at them. The results: Increased conversions and sales.
7. Gain insight from your log files
Just like your hardware, your software generates lots of useful data. One of the most common examples: Server log files. Server logs are computer-generated log files that capture network and server operations data.
How can this data help? Here are a couple examples:
Security: What happens if you suspect a security breach? The server log data can help you identify and repair the vulnerability.
Usage statistics: As demonstrated in this webinar, server log data provides valuable insight into usage statistics. You can instantly see which applications are most popular, and which users are most active.
These are just a few examples of ways other companies are using Hadoop right now. Do all of these examples apply to every company? Of course not. I share them to spur your imagination. What could you accomplish if you started capturing unused data with Hadoop? What questions could you ask/answer?
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Here are five examples of Hadoop use cases:
- Financial services companies use analytics to assess risk, build investment models, and create trading algorithms; Hadoop has been used to help build and run those applications.
- Retailers use it to help analyze structured and unstructured data to better understand and serve their customers.
- In the asset-intensive energy industry Hadoop-powered analytics are used for predictive maintenance, with input from Internet of Things (IoT) devices feeding data into big data programs.
Telecommunications companies can adapt all the aforementioned use cases. For example, they can use Hadoop-powered analytics to execute predictive maintenance on their infrastructure. Big data analytics can also plan efficient network paths and recommend optimal locations for new cell towers or other network expansion. To support customer-facing operations telcos can analyze customer behavior and billing statements to inform new service offerings.
- There are numerous public sector programs, ranging from anticipating and preventing disease outbreaks to crunching numbers to catch tax cheats.
Hadoop is used in these and other big data programs because it is effective, scalable, and is well supported by large vendor and user communities. Hadoop is a de facto standard in big data.