Big Data is the next ‘big’ thing in computing. It generates value from different data sets that cannot be analyzed by using traditional computing methodologies. The amount of data being generated daily is growing exponentially-- as new data is being recorded, newer data is being created, previous data is being monitored, existing data is being modified and so on and so on. This obsession with data might seem absurd at first, but the practice of recording, evaluating and creating is ancient, and for good reasons. Retailers are building troves of data on the observed activity of customers and their next interactions, while organizations from logistics firms, financial services, health care, and other service sectors are striving to fill their own databases full of unique information.
Big data, what’s it really about?
Besides being a holistic management strategy that deals with the integration and management of new data, Big Data can be categorized using the three V’s. Volume, Velocity, and Variety;
Volume deals with the total amount of data, Gigabytes, Terabytes, and even Petabytes of data. Volume poses the greatest challenge and the greatest opportunity for businesses as it helps organizations to better understand their customers’ needs. The posts on social media, the interaction between organizations and customers, the remarks posted 6 years ago, on Reddit, the harsh comment you left on their Facebook page when they didn’t put enough pepperoni on your pizza, are all valuable assets for the company. This huge chunk of data allows businesses to correlate shopping patterns, understand consumers’ wants, keep a record and come up with business strategies, advertisements, campaigns that will satisfy their consumers the most. When it comes to consumer research, having this ocean of data by your side can be your ticket to success.
Velocity refers to the rate at which data is flowing. The high-speed moving data stream requires immediate attention and a timely response. But the supersonic speed of data streams can often exceed the capacity of an organization's IT systems. In addition to this conundrum, users demand data which is streamed to them in real time. Processing in real time is a challenge, as it requires continual input, fast processing, and frequent outputs. The intensity of real-time processing of big data, in terms of velocity, can be understood by looking at a banks’ ATM-- it provides you with money (output) instantly, despite having thousands of users using the service simultaneously.
Everything in this world comes in different shapes and sizes, not to mention formats. Variety deals with different formats of data. Ranging from highly structured to semi-structured and unstructured, data is available in many types; audios, texts, photographs, 3D structures, videos etc. Gone are the days where computers only had to deal with a few mainstream forms of data such as documents, financial transactions, personal files and stock records. Now an incredibly diverse variety of potentially valuable data is available, and enterprising organizations want to grab and pile as much as possible into their data storehouses. These often unstructured sources of data are difficult to categorize, let alone process by means of traditional computing.
How Big is Big Data?
On looking at a daily scale, seven billion people in this world with nearly half the population having access to the internet, upload 55 million pictures, post 340 million tweets and upload about a billion documents. In a rough estimate, producing a whopping total of 2.5 quintillion bytes of data... In a day! Organizations today have little to no choice but to ignore most of this enormous amount of data, leaving a large portion of data which could have worked for the betterment of the business, unanalyzed. Even the most advanced and vast IT systems combined are not capable of handling the astronomical amount of data, consequently valuable data is lost.
The significance of Big Data
The significance of big data in any organization cannot be questioned. When leveraged properly, big data can act as the backbone of the organization, helping it to sky-rocket it into a field of success. Winning organizations shift their focus onto the processing of big data, rather than big data itself. Data which has been left unanalyzed is data that cannot be interpreted or used scientifically. Analyzed data serves as a platform that enables the company to accomplish its primary goals:
Better brand positioning
Improved product positioning
Superior decision making
Increase consumer loyalty
Effective product placement
Faster response time
Customization of Product
Users seeing a product which was “made for them” isn’t purely coincidental, but instead has pools of big data backing it up. This is how companies tend to position themselves in the minds of the consumer, by using big data to better understand their consumers’ requirements and creating products that are a fit for them. Successfully harnessing big data and hitting the mark on these new offerings ultimately lowers business costs on failures, and increases revenues along with loyalty from their customers.
Big Data Technologies; Hadoop
One of the leading big data technologies available in today’s world is Hadoop. Hadoop is an open source software library, that provides reliable, scalable and distributed computing and serves as a platform for big data analytics. Hadoop is an extremely famous platform that is used by many organizations to advance their businesses. LinkedIn, a big data pioneer uses Hadoop to generate billions of recommendations for its users.
Hadoop distributes storage along with the processing of voluminous data sets across servers. It detects and compensates for any hardware malfunctions or system defaults at the primary application level. This post provides a primer on Hadoop -its origins, why its data storage and accessibility design is so secure, and how it's become such a valuable platform for companies in their big data efforts.
Users of Big Data
Organizations across the spectrum are implementing and putting big data programs to work. While the information they collect, parse and analyze may be very different from each other, the goal is always to derive fact-based, actionable insights from the data they're collecting. Here's a brief look at how some industries are putting big data to work for them:
Health care organizations, look into previous records of their patients, making use of general information to form the optimal treatment plan. Big data analysis also provides the basis for their research and development departments to discover new medicines which can alleviate pain caused by dire diseases.
Many inventory management systems rely on big data for providing useful insights that will lessen their waste production and improve their product quality.
Retailers are building vast databases of observed customer activity and interactions, this promotes two-way communication and improves consumer-producer relationships, a key asset to interact effectively with the customers.
With big data analysis, significant profitable changes can be made to the schooling systems, promoting well-being, interactive programs, extra curriculum activities, student counseling and to ensure sufficient progress in their academic performances. However, the Cincinnati school district was a great example of why it takes more than just access to data to generate beneficial actionable insights.
A recent Harvard Business Review survey reported that 48.4% of firms engaged in big data efforts are achieving measurable results, and 80.7% deem their big data investments as "successful". Successfully leveraging big data has the power to help organizations engage customers in new and beneficial ways, researchers to identify previously unknown solutions to critical issues, and give businesses the edge over their competition. What will your organization do with big data?