Firmex is pleased to present the following 3-part series on Big Data. In this article (Part 1) we will define what Big Data is and the advantages it can offer your business. Part 2 & 3 will provide some practical advice on how to adopt it into your business.
What is Big Data?
‘Big Data’ is the application of specialized techniques and technologies to process very large sets of data. These data sets are often so large and complex that it becomes difficult to process using on-hand database management tools. Examples include web logs, call detail records, medical records, military surveillance, photography archives, video archives and large-scale e-commerce.
By ‘very large’ we’re talking about datasets that require at least one terabyte – if not hundreds of petabytes – of storage. (Note that 1 petabyte = 1024 terabytes!). Facebook is estimated to store at least 100 petabytes of pictures and videos alone.
Big data is first and foremost, data; an elusive, yet valuable, corporate asset quite unlike any other, that needs to be properly managed.
Unique characteristics of data:
– It can be copied perfectly at very low cost
– It can easily be combined with other data to uncover valuable insights
– It can be used by more than one person at the same time
By managing big data effectively, businesses are better able to capitalize on its value.
Big Data is Big Money
Big data spending is expected to reach $20 billion by 2016. The reason is simple; big data can dramatically improve productivity. According to a detailed study conducted by the McKinsey Global Institute, the potential value of big data for the US health sector alone could amount to more than $300 billion annually.
In the banking industry, big data is being used to target consumers with “right time” offers. These offers are informed by the large volumes of data the bank already has on each consumer, such as their spending habits.
Citigroup, for example, monitors credit-card transactions and uses this information to send text messages to customers offering them special deals. The Economist reports: “A customer buying clothes around lunchtime, for example, might be offered a discounted meal at a nearby restaurant.”
Privacy and Big Data
The successful adoption of big data into an organization is by no means simple and can be a steep learning curve. It also presents some obvious challenges around privacy. By capturing and combining big data sets, an organization is able to create an extremely detailed profile of an individual (e.g. sites visited, links clicked, searches made, location of cell phone calls). Regulations that balance productivity gains with privacy protection are yet to be developed.
From a commercial or competitive perspective, organizations also face the challenge of sharing highly confidential big data; things like financial statements, patents, trade secrets and intellectual property. This sensitive data must be securely stored and made available to those who need it.
New innovations, like virtual data rooms, are making this task easier. Virtual data rooms allow authorized individuals to review confidential data and documents in a secure online space. They are essential for data sharing in matters of due diligence, and are widely used for mergers and acquisitions, litigation, bankruptcies, and fundraising.
Companies that implement a comprehensive data security system and have good privacy policies in place, which protect against the unauthorized disclosure of sensitive information, will be in the best position to adopt big data.
7 Reasons to Adopt Big Data
By adopting big data techniques into their business operations, organizations are able to:
1. Stop wasting data exhaust
An organization’s ability to produce data greatly exceeds its ability to store and manage it. Think of all the data streaming from sensors embedded in devices, from items that contain RFID tags, or from employees with smartphones generating location-based data, videos, and e-mail. Rather than wasting this ‘data exhaust,’ big data enables the best of this information to be combined with other data, often producing unanticipated new value for the organization.
2. Save time and money
Even when data is captured and saved, it is typically stored in disconnected silos. This increases the amount of time it takes employees to find information. By adopting big data techniques and technologies that can connect data sets together, employees can usually find what they are looking for instantly.
3. Improve performance
Big data enables information from both inside and outside the organization to be combined, so that key performance indicators can be developed and acted upon. The Startup Gnome project, for example, collects information about startups by offering them a free data-driven benchmarking tool. Investors then use this data to calculate risk and investment feasibility.
4. Improve Product Offerings
Data from a variety of sources can be combined to improve existing products. For example, BusinessWeek recently reported how manufacturer John Deere is combining GPS data with sensor data from onboard tractors. These tractors can be operated remotely, and can monitor crop yields while they work. Crop yield data is later used to determine precise amounts of fertilizer to deliver, according to the location in the field.
5. Segment Groups within Larger Populations
Big data techniques can combine and analyze data from a number of sources and segment specific sub-groups within larger populations. For example, Big Data analytics provider Medio Systems, offers a module appropriately named “Clustomers”, which “provides automated audience segmentation to help increase customer engagement and monetization capabilities.”
6. Improve decision making
Big data is a powerful means for making informed decisions. However, as big data technologies continually improve, there remains a shortage of skilled professionals who can take full advantage of these technologies. In an article titled “Improving Decision Making in the World of Big Data”, Forbes magazine reports that for every one manager with big data skills, there will be ten positions left vacant in 2013.
7. Innovate
Big Data diminishes the need to rely on preconceived ideas or assumptions, by enabling innovators to analyze and experiment using real data, in real time. Ford Motors, for example, is emerging as a leading data-driven company, using big data techniques to better understand how their customers are using their vehicles.
“Our manufacturing sites are all very well instrumented. Our vehicles are very well instrumented. They’re closed loop control systems. There are many, many sensors in each vehicle… Until now, most of that information was [just] in the vehicle, but we think there’s an opportunity to grab that data and understand better how the car operates and how consumers use the vehicles. [We can then] feed that information back into our design process and help optimize the user’s experience in the future as well”, said John Grinder from Ford Research.
Read Part 2 of our Big Data Series, which outlines 7 big data techniques that create business value.
