Big Data vs Machine Learning

Impressed by this quote

"When it comes to big data, analytics and AI, the value does not come from collecting the data, or even from deriving some insight from it — value comes from just one thing: action."

- from https://www.cio.com/article/3307110/the-future-of-big-data-and-ai-boils-down-to-one-thing.html

Big Data & Machine Learning is trend topic in 21st century. Everyday we are producing the data, and we are also absorbing data through internet, TV, social media. And this both interrelated topic is cooperate with each other to create a Big Data-based technology & lifestyle we will be heading to.

But why do they look same yet different?

Big Data

1. Play with LARGE data set. 
2. The target of using Big Data is to figure out the hidden pattern appears in a group of large volume of data. When it come into a small group of peoples, it's only appears as a survey to a practice that applies to s dedicated group of humans - example 10% of student in a town will visit basketball court even though they are not from basketball team. The reason is, this is the daily entertainment for youngster in this town. However when comes into big group, it may appears as 90% of youngster in this country visit basketball court due to the promote of the sports society of the government.
3. Big Data analyse for business decision in market trends and customers orientation decision. As all data is coming from real-life user, no assumption, it would help better business decision and strategist move. Example there are XX% of people in the Malaysia having oily skin type, so to have more products stock and market promotion for oily skin care product can be introduced to Malaysia.
4. Concern of Big Data is always related to storage and performance. When it comes into high volume of data, we always encounter the issue with the slow loading & required a high specs hardware for performance purpose, and a storage to have all this virtual information stored. And what? they are virtual, yet they required to be stored on a physical devices. Why are we making a virtual object to a physical object?

Machine Learning

1. Machine Learning is a fields of Artificial Intelligence, AI
2. ML use computer to learn from a set of data, the purpose is to increase the accuracy for a planned action. In another word, is to educate the computer to be able to perform a complicated task without required human operation. Example ads recommendation.
3. When slice into small operation, big data set would be a problem to a machine learning. because small & area-oriented data set will help in narrowing the available options for end results purpose.
4. Concern of ML is always been expect to be able to react/advise like a human. 

We are already in a century having all this data flowing around the air, data is growing very fast and huge, the challenge will still be how should we collect data, how can we learn from the reading to build a tools to collect, analyze, present and utilize these virtual information. Will it force us to move to real time decision making model?

The challenge to most of the people is privacy. When your information could be found simply by a Google entry, when your information could be found simply by a photo of you.

There are official site predicted few things should be happened in future:

1. Chief Data Officer role introduce - That playing an important role in huge data era that we are heading to. This is interesting assumption. We will be having a group of professional people focus in Big Data & Machine Learning growth in future.
2. Data as service & business model, by selling data. This is what happening now, example selling country-based holiday data.
3. Algorithm market - algorithm involves professional knowledge & analyse skills, so...are we going to earn money with our knowledge instead of our physical man-hour? How do we sell a knowledge? How do we buy a knowledge?