If you have been keeping your eyes and ears open in the modern world, you will definitely have come across the term data science somewhere. Data science is currently changing the way humanity functions, that too in a huge manner. Almost every field, ranging from healthcare to warfare has been improving in leaps and bounds owing it to the data science techniques which have been developed in the past decade or so.
What is Data Science?
Every second, terabytes of data are being produced in the world today. Most of this data is raw, which means that there is no order to it whatsoever. Before the onset of the internet age, most of the data produced in the world was structured, which meant that it was easy to analyze it, store it and manipulate it qualitatively. However, the rise in the amount of unstructured data in the past two decades resulted in the development of data science, which was created from the need to structure and analyze this treasure trove of data.
Data science is an extremely multidisciplinary field, which makes use of algorithm development, technology and data inference to sole the extremely complex problems in the world today. The aforementioned large amounts of data are stored in data warehouses around the world, and the focus is on how this data can be analyzed to create business value in tangible terms.
There are two ways in which data science is used, especially in the case of big organizations. The first is to use the available data in order to obtain business insights from it so that the insights can be used to improve the product the customer receives. This is all about digging deep within the data and uncovering complex behavioral patterns and trends, which can, therefore, be of business value. An example of this is the way Netflix uses data analytics. Netflix mines data for movie patterns of users and they try to understand what the users prefer to watch so that the next project they create is according to the interests of the user. This ensures a higher viewership for each project.
The second way in data science basics is to use the data to build a ‘data product’, which is usually a deliverable in itself. This is a technical asset since it gets data as input and the output is algorithmically generated from this data in the form of recommendation or the likes. Taking the example of Netflix again, the data product that Netflix uses is the algorithm which takes the users’ viewing patterns as the input to provide better recommendations to the user, in order to ensure higher viewership.
The Requisite Skill Set
By now, you would already have your interest piqued in data science and will be looking to understand the data science basics. However, what is the skill set that every data scientist must have? Let us take a look at that.
A data scientist must have three major skills to solve most major data science problems. These are expertise in mathematics, technical knowledge and a sense of business acumen. Proficiency in mathematics is important, along with an understanding of technology, if you want to build a great algorithm. This field is extremely statistics-oriented, so you must be comfortable and willing to work with numbers and equations in order to develop algorithms.
Data science, like any other field, is a business in itself too – therefore, a strong business acumen will be the thing that propels you quickly through your career. If you find yourself yearning to work in data science now, you should definitely check out the online data science courses on Acadgild today!