More and more people today are using smartphones and computers in their daily life, resulting in the rapid expansion of data volume.
According to International Data Corp. it is predicted that by 2020, on average, people will generate 1.7MB individually per second.
And because applications and programs are becoming more complex, the same research shows that 40% of the internet data in 2020 will be coming from machine generated data.
With these astonishing statistics, it is important for us to understand what Machine Learning entails, the connection between Machine Learning and Big Data, and what it means to implement Machine Learning and Big Data for businesses.
Machine Learning is a branch of computer science that allows machines to execute self-learning algorithms that can make them learn from past experiences, while at the same time continuously evolve and improve the tasks that were assigned to them.
When built correctly, Machine Learning can produce patterns and insights that are very useful for predictive decision making. Based on a report from IBM, the adoption of Machine Learning Library (MLIB) will grow by 60% in the next 12 months.
As Machine Learning algorithms will become more effective with the datasets growing, the combination between Big Data and Machine Learning will make the quality of data-driven decision making and predictive analysis become better and more accurate.
Organizations can implement Machine Learning algorithms in Big Data operations, including data labeling and segmentation, data analytics, and scenario simulation.
Although the relationship between Machine Learning and Big Data is very close and considered as a never-ending loop, it is important to understand that this system still needs human expertise to provide the right data and interpret the output.
Without the human experts who have experience, critical thinking, and knowledge, the recommendation that is made by an algorithm can compromise corporate decisions.
Big Data and Machine Learning algorithms can be used in all organizations across industries. In the healthcare industry, Big Data and Machine Learning can be used to improve the diagnostics capabilities and provide recommendations for personalized treatment plans.
Not only that, predictive analysis from Big Data and Machine Learning can also be used to create a proactive framework to address patients before they are sick, preventing illness and safe lives.
In retail, Big Data and Machine Learning can be used to create a personalized shopping experience in real time, allowing businesses to simplify segmentation and improve their customer targeting.
This will help businesses to increase customer loyalty and secure more business opportunities in the future.
With more and more companies implementing Big Data Indonesia, it is important for businesses to understand the relationship between Big Data and Machine Learning.
Improving the capability to develop insightful data analytics and predictive models, Big Data and Machine Learning can help organizations improve their decision making process and therefore increase productivity, profitability, and achieve better business results.
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Considering implementing Big Data in your organization, some case studies on how companies employ Big Data to optimize their business performance mentioned above can be a good reference for your business.
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