Big Data, Small World
While data is growing at a tremendous pace of 2.5 quintillion bytes a day, the concept of 6 degrees of separation among human beings, called small world theory, is actually getting even smaller. Created by social psychologist Stanley Milgram the small world theory imagined that everyone on earth could be connected in less that 6 intermediaries. The visualization of big data and how it promotes this connectedness is the underlying key of how insights and analytics drives business intelligence.
The small world theory makes the “big world” more approachable and less alone. Facebook claims that their network had three and a half degrees of separation!
Companies spend a great deal to understand data and connectedness with all its limitations. To really understand big data, it’s helpful to have some historical background. Here is Gartner’s definition, circa 2001 (which is still the go-to definition): Big data is data that contains greater variety arriving in increasing volumes and with ever-higher velocity. Also referring to a combination of structured and unstructured data that needs to be extracted for insights meaning, what pattern can be designed that will be useful to take a decision for grabbing the new business opportunity, the betterment of product/service and ultimately business growth.
Understanding Big Data comes down to three V’s
Volume: The amount of data matters. With big data, you’ll have to process high volumes of low-density, unstructured data. This can be data of unknown value, such as Twitter data feeds, clickstreams on a webpage or a mobile app, or sensor-enabled equipment. For some organizations, this might be tens of terabytes of data. For others, it may be hundreds of petabytes.
Velocity: Velocity is the fast rate at which data is received and (perhaps) acted on. Normally, the highest velocity of data streams directly into memory versus being written to disk. Some internet-enabled smart products operate in real time or near real time and will require real-time evaluation and action.
Variety: Variety refers to the many types of data that are available. Traditional data types were structured and fit neatly in a relational database. With the rise of big data, data comes in new unstructured data types. Unstructured and semistructured data types, such as text, audio, and video, require additional preprocessing to derive meaning and support metadata.
Day by day the amount of data is increasing exponentially because of today’s various data production sources due to digital transformation, IoT and over innovation across all industries. As per IDC (International Data Corporation) report, each person in the world creates 1.7 MB per second. Considering other data sources with IoT, this figure is set to expand exponentially.
We can have data without information but we cannot have information without data.
With such voluminous data comes the complexity of managing it well with techniques that are not only effective and human-friendly but also deliver the desired results in a timely manner.
The significance of Big Data does not only revolve around how much information an organization has but also how an organization uses the gathered information. Each organization utilizes information as per their needs; the more proficiently an organization utilizes the information, the more promising are the chances of its prosperity. Big Data has played a pivotal role in the business environment today.
Why most of the Big Data Projects fail?
The way Big Data is perceived by the masses: Big Data gets treated as if it has a fixed starting point with a fixed ending point whereas it is an excursion leading through consistent analysis and examination of data. It can be used to infer patterns for tomorrow’s business achievements. However to find the solution you can take the process as a primary concern and not expect a characterized deliverable out of it. Big Data is a steady research to increase useful insights as opposed to the view of getting to conclusions sooner than ever. The essence of this data is found when it is placed in business setting else it’s only a tremendous measure of data.
Lack of skilled data scientists: Absence of appropriate research in Big Data ventures is mainly because of the inaccessibility of professional and skilled data analysts. Great amount of experience, expertise, greater adaptability and extended timeframes are required to increase the productivity out of Big Data.
Cost cutting and lack of budget: Emerging technologies can be harnessed only with the help of proper tools and when the systems are well equipped. Sometimes businesses aren’t willing to invest a lot in ventures that ensure promising ROIs but in a long term. The greed of making zillions in a short span of time limits the use of proper tools and technologies. This leads to a failure of these Big Data projects.
No clarity of thought and poor strategy: The first and foremost step of problem solving should include the end user to question himself of the kind of outcome he is focusing on and the reason behind it. The outcome of a problem can be vague offering a wide range of possibilities and might confuse the user and distract him from his ultimate objective. Therefore, it is important to compile a detailed problem statement in order to gain maximum benefit out of Big Data.
There are 800 million websites on Internet giving data about Big Data. Big Data is the next huge thing after Cloud. Big Data accompanies a ton of chances to bargain in health, education, earth, and enterprises yet to manage the information having huge volume utilizing traditional models turns out to be extremely troublesome.
Data Revolution, Data Driven Marketing and Impact on Business Intelligence
"Data is king" and it is irreplaceable to every organization and business for their digital marketing strategies. With the help of big data, marketers can analyze every action of the consumer. It provides better marketing insights and it helps marketers to make more accurate and advanced marketing strategies. While systems, applications and concepts like Hadoop, reservoir sampling help with extracting insights, ‘Data will be a precious thing and will last longer than the systems themselves’. This quote perfectly captures the true essence of Big Data and how it is the new raw material for various businesses and firms.
Sources and Excerpts
https://rampages.us/giny/2017/09/17/small-world-theory/
https://www.oracle.com/big-data/what-is-big-data/
https://www.geeksforgeeks.org/what-is-big-data/
https://bigdatasmallworldblog.wordpress.com/2017/03/11/how-to-forecast-revenue-growth-using-excel/
https://infocus.delltechnologies.com/steve_woods/small-world-big-data/
https://www.geeksforgeeks.org/