Heaptalk – Jakarta, In the era of Big Data nowadays, everyone is always talking about data science. Like why data science matters and how it powers business value. Indeed, data also becomes a universal ideal that modern business is awash with data. Even our ears are too used to hearing the designation of this cool science, as we know more and more organizations have applied this scientific method. Here we are going to see more clearly what ‘Data Science’ is.
Some questions also arise; how can Google create a car without a driver? How can an advertisement appear on a website about the items we are looking for? How can social media accounts recommend articles, web pages, or other users for us to follow? And various other how-to questions. All of these are Big Data phenomena. The emergence of many platforms where we share stories, photos, personal data, etc., shows that our personal data’s security level is no longer “privacy” anymore. The amount of data stored is enormous, and even these data can be used for crimes if not appropriately managed.
Therefore, data science is crucial in the current Big Data era, where many experts can analyze various types of data, both structured and unstructured, properly. “Data science” is a combination of data inference, algorithmic development, and technology to solve complex analytical problems. “Data science” itself is more about extracting or predictive analysis of data to be filtered and found the correct data to produce accurate data according to the actual data. In “Data Science” relies on science alone, but some more knowledge must be possessed to understand this field.
Some of the Power of Data Science in Business:
Internet of things
The first reason is regarding the era of the internet of things that many tools are connecting via the internet and able to send data seamlessly. This analysis of machine-generated data can reveal many new things. Most importantly, data can help provide better decision-making with quantifiable evidence generated from connected equipment/devices in the business environment.
For the customer experience, IoT helps to reduce friction in the buying experience. It facilitates customers to interact with products and often provides in a virtual or augmented reality environment, pre-purchase. For some solutions, the experience is still a little clunky, but the message is that the IoT can give high street and leading street stores a much-needed boost at a time when conventional online retailing is undermining it.
Computers get smarter
Over time, computers become smarter at producing better translations. That is why Machine Learning belongs to the subject matter of data science courses. Later Google can produce accurate translations, including translating conversations and make the translation profession fade away, as will happen to many other professions due to technology.
With Data Science, we can also better understand consumer behavior. Such as finding on the leading marketplace like Amazon, Tokopedia, and Alibaba.com, which has successfully developed a purchase recommendation system for several other items for its website visitors.
Escalation of Business Value
Data science can add value to any business who can use their data well. Data science is valuable to any company in any industry from statistics and insights across workflows and hiring new candidates to help senior staff make better-informed decisions. A data scientist is typically conducting research dealing with big data and using accurate methods in fundamental responsibility.
However, data scientists in this field are binding to be proficient in using big data platforms such as Hadoop and Hive, and Pig and understand using SAS, Scala, Python, and R to reduce the burden on computers performing data analysis.
Potential career pathway
Data scientists typically build machine learning models to make accurate predictions based on past data. A data scientist often has more freedom to pursue their ideas. They also do experiments to find interesting patterns and trends in the data that management may not have thought about. As a data scientist, you may be dealing with the job to assess how a marketing strategy change could affect your company’s bottom line. This role would entail a lot of data analysis work (acquiring, cleaning, and visualizing data).
Still, it would also require building and training a machine learning model. Thus, you can make reliable future predictions based on past data. Meanwhile, the salary received ranges from IDR 40 Million to IDR 400 Million plus stock option.
