Last Monday, the team of Apiumtech from Vietnam had the chance to attend the Big Data Meet Up that was organized by Felipe Hoffa – a US-based Big Data Developer Advocate of Google – in Ho Chi Minh during his trip down to SE Asia.
From my side, it was a great meet up even though there was a small problem with the projector. Obviously, no one is perfect and nothing can be perfect, it’s all about the final experience. What really counts is how we handle problems, and at the end, we all enjoyed this very warm meet up where Felipe shared his widen knowledge and strong experience about Data.
WHAT IS BIG DATA?
First of all, it’s important to know that there are many ideas related to its definition. Big Data can be seen as a broad term for data sets, a buzzword or a catch-phrase.
Some definitions refer to big data using what is know as the three Vs model: Volume, Velocity, and Variety. In fact, Gartner describes big data as a “high-volume with high-velocity and/or high-variety of information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision making, and process automation”.
Beside that, we’ve also found many interesting definitions or opinions about big data from more than 40 leaders in different industries such as medicine, marketing, food, fashion, etc. If that interests you, you can have a look here and you might be surprised by the variation!
No matter what the definition is, the term “big data” is not only about the data itself; it also refers to the challenges, capabilities and competencies. What seems to appear everywhere is that big data is a non-stop massive growth of information.
DIFFERENCE BETWEEN BIG DATA & LARGE DATA
You might ask yourself if there is a difference between “big data” and regular “large data” ? After doing some research, I found a good example of Dwight deVera that explains the difference between those two; the thousands of statements and invoices that a financial director has about his clients on files is considered as large data. But log files from social media sites such as LinkedIn and Facebook are considered as big data. What is the difference? It’s the speed at which the data must be captured and available for analysis.
BIG DATA & MARKETING
For Marketers, big data is the result of the new marketing era, the result of this digital world we live in. In fact, they have to face customer data, social media integration, mobile device usage, browsing behaviour, geo-location, click through rates, etc. Obviously all that represents a huge amount of data, but the thing is that if we know how to combine big data with an integrated marketing analysis, we are able to have a huge impact and reveal very interesting insights. According to Darryl McDonald – president of Teradata Applications – “marketers are most effective in generating revenue when they are able to put all their data to work to deliver the most relevant offers to consumers”.
One of the first things you need to do as a marketer is to get the most information as you can about your target to be able to build their profile; who they are, what they do and how they feel. With big data, you can easily get significant insights about your customers; where they are, how they want to be contacted and when. The formula can be called the 04 R’s: the right people, the right way to contact, the right time and the right location. Basically, big data helps marketers to have a deep understanding about customer’s behavior and what it is that will make them come back again and again to you, your product or service. Nowadays, big data analytics skills and digital marketing savvy are increasingly valuable to companies, they help drive more revenue, better margins, increased efficiency, and resulting into more profits. All of that used in the right way obviously.
HOW TO IMPLEMENT BIG DATA
A few months ago, we wrote an article about how to implement big data, I invite you to read it if that interests you! Mainly, the requirements were that in the context of a web application with a high load of requests to server with multi-field search, it is necessary to implement a system of low latency and high availability in order to perform queries against a relational database with maximum efficiency.
Finally, Felipe Hoffa’s idea on the technical side is that: “What if big data is sizeless, weightless, fast and easy? Here’s a presentation and video. He is also willing to answer your questions related to big data.
