There will always be a love and hate relationship in all aspects of human life. This goes the same with modern technology. There are people who embraced something new or something already established and there are some people who literally hate anything about a certain technology. This love hate relationship includes big data. Arun Jacob of Disney said “ I hate the term Big Data. Someday, we’ll just call it data- but for now it’s big”. They’re people who want to banish “cloud”,”big data” and all the other buzzwords that they have grown to hate. They pointed out that it’s like every start-up enterprise at present is in “big data”. They also stated that there are even “venture funds” that are completely devoted to big data startups.
Why do some people grow to dislike the phrase “big data”? It is because they think that the term itself is outdated and mostly consists of a general set of words that does not reflect what is truly happening to date nowadays? They believe that it is about the apps that layer on top of the stored data and the insights the apps can provide. According to the article of Vincent McBurney, the term big data originated from Francis Diebold as a term paper that was submitted on July 2000 at the University of Pennsylvania. McBurney’s term paper was titled “Big Data: Dynamic Factor Models for Macroeconomic Measurement and Forecasting”. According to the McBurneys term paper, Big Data is defined as the explosion in the quantity and quality of potentially relevant and available data which are the results of recent and unprecedented data advancements in storage and recording technology. By using the new term, sample sizes are no longer fruitfully measured in just number of observations but in megabytes.
A Little Bit of History: Big Data
Bixo Labs’ Ken Kruger made a presentation in 2011 titled “The very Short History of Big Data”. His presentation cited the Hollerith Tabulating System that was used for the 1890 US Census as the first big data computing system. Herman Hollerith invented the first machine that tabulates millions of pieces of data in producing a set of statistics. Hollerith also founded the company called the “Tabulating machine Company” which merged with three other enterprises to form the Computing Tabulating recording Corporation and then evolved to IBM. IBM’s founding company started big data, but it would take 120 years to make it a marketing phrase.
The Big Data Rejection And Eventual Acceptance
As a matter of fact, a big data entry was made on Wikipedia. It was almost deleted because one of the editors pointed out that it was just a combination of the words big and data. The word “big” is an adjective that can be combined or merged with other words. The editor also stated that there is nothing unique about its use with the word data. But in April 2010, the big data page was up again with a larger number of citations even with many discussions and requests for it to be deleted. And by 2010, the phrase Big Data showed up for the first in Google search trends.
At present, big data appear in 0.1% of almost all job listings and continues to grow at a very quick pace. Experts stated that the listings will double by the end of the year and will eventually pass hold-up as a popular term in this emerging field of technology. And today as mentioned, big data is used by many enterprises and companies, specifically those that are selling storage hardware, Cloud storage, Hadoop based products, data warehouse appliances and analytics software. It can also be considered as a transformation of the industry or the change from old technologies that do not scale as compared to scalable software and hardware.
Reasons Why Many Hate Big Data
Hate is a very strong word, but for many people, it fits how they feel about big data. However, the catch phrase may not go away soon and will make any less important to the business. Below are the reason why people cringe at big data.
1. Big Data Is Consfusing Too Many People
Even industry experts will tell anyone that big, data is confusing but, it becomes less complex when it is segmented and visualised. Businesses that make their big data into smaller data segments for individual teams for use in marketing, content creation, advertising and other tasks a company requires.
2. It Is Impossible To Keep Big Data Accurate
In reality, big data in never 100% accurate. People can lie on surveys, people mistakingly get things wrong and nobody wants to admit some information about themselves or habits. Bear in mind that big data should showcase habits and trends.
3. Big Data Is Very Hard To Organise
Assuming that you don’t have the right software and the right staff to make it happen, it will surely be hell in organising big data. There are many CRM software available in the market today that can fit any budget. Choose a software that will fit your needs and don’t let the finances greatly affect your decision to do so.
4. Big Data Is Always Changing
This is a fact, that‘s why it is important to organise and analyse everything immediately. Some data will be outdated if it just sits stored and not used at all. Big data collection is an ongoing process and is not one task that you just leave.
5. Big Data Does Not Mesh With Action
When collecting large amounts of data, make sure you have a concrete action in mind. Using the right tools will help you in collecting digital customer data. Own the digital data as a first-party to your chosen business and act on it in real time in delivering personalised and customised user experience across all devices and channels.
6. Big Data Requires Large Manpower
This can be true if a chosen approach does not fit the capabilities of the business. Processing all the data is too large and a hard task for anyone. Figure out which results the business requires from big data and pull the information most relevant to the business. Big data will only be useful if it is dissected, studied and made it smaller and more understandable.
7. Big Data Is Not Cheap
Almost every technology comes at a price. The platforms that are used to collect, analyse and convert data into useful information are not cheap. If it’s out of the business’ budget, then choose different options.
8. Big Data Is Not Useful To Anyone
If a collection of data is not useful to you, it’s possible that you have the wrong set of data or you don’t know how to analyse it. Not all big, data is going to be an advantage. You need to know how to get the useful ones from the crappy ones. Not all information is going to be helpful to every enterprise. This is one factor that every enterprise needs to consider in which data are needed to be analysed.
9. Big Data Is Not What The Financiers Wants To See
If the business is required to include data and statistics as part of the grant proposal or for a possible investor, you have make sure that the information you provide is exactly the information they want. If one set of data does not provide it, search for another.
10. Big Data Forces People To Face Their Responsibilities
This does not mean that people are too lazy to work on their given tasks. Who does not dream of measuring the impact of real time decision making? Unfortunately, not everyone. The reason is the culture within the enterprise. When people are given the right information to make decisions, more people can be empowered in making decisions where the issues happens and then can lead to management weakness. Big data does not provide answers, but information allowing to find the answer. Interpreting data belongs to the people.
At the end of the day, people will think of different ways of describing startups that are dealing with big quantities of data. It can also be said that it may be the actual function of apps vs the data. Hate is a very strong word, but points must be taken to analyse if big data will stay or not. The people on the other side of the fence say that anyone promoting big, data is somewhat “hipsters” of the tech world. Only time will tell if big data are as relevant as other technological breakthroughs.