Have you ever wondered how humans have managed to get ahead of other species? By utilizing resources around them. Over the course of history, humans have made the most of resources like agriculture, gold, coal and more to prosper. In today’s age, these driving resources have gone digital too. According to research, out of 7.8 billion people on earth, 4.93 billion, that is 64% of the world’s population, has access to internet. Today, the internet is an ocean of a resource.
As per experts, the mere use of internet increased by 1622% in the one year between 2020 and 2021. A major characteristic of this trend has been the generation of vast amounts of data. While most of us don’t pay heed to the data we generate by posting photos, commenting or being on the internet, there’s a lot that can be accomplished by delving deep into it. The study of such data is known as data science. To understand the real benefits and advantages of Data Science, we need to understand what the world of Data Science is, so let us guide you through this overwhelming field.
More about Data Science
It’s commonly known that massive amounts of data is being generated with the use of internet and devices such as desktops, mobiles, tablets and more. Currently, all this data sits in data lakes or data repositories. There’s a lot that this data can teach us about human habits, behaviours, the performance of businesses online, internet usage, social media’s impact, etc. This is where Data Science comes in. What if this data was put to use?
Simply put, Data Science is the culmination of several fields like statistics, Artificial Intelligence (AI), Data Analysis and more. This field aims to study internet-generated data and reap value from it. Field experts, also known as Data Scientists, like those at Ikokas, feed harvested data to enable Machine Learning. In turn, Machine learning leads to smarter AI. That is why Data Science is an emerging field in the domain of Artificial Intelligence (AI) and has numerous applications.
How can Data Science be used?
Data Science is making a huge headway in business growth. Some ways in which Data Science is being used commercially include:
1. Predicting business outcomes
Data Science has the power of statistics and can be used to predict outcomes. Predictive causal analytics in Data Science, as the name suggests, can help a business foretell if a venture or a decision will yield success. For example, this style of Data Science can be used by a bank or a financial institution to predict if money lent through a home loan to a homebuyer will be successfully repaid or not. Predictive causal analytics will delve into the homebuyer’s payment history and financial patterns to generate predictions about future payments.
2. Making business decisions
Data Science, as well as AI, uses multiple techniques to obtain insights from raw data. These insights can be used by businesses and brands to gauge the performance of new products even before their launch in the market. Similarly, Data Science can also help us understand which business models would perform well and which would not succeed.
3. Enhance efficiency
Data science feeds raw data to AI which identifies patterns and learns or observes behaviour. As a result, data on the productivity and efficiency of machines in a factory or employees in an office can be analysed to identify problem areas. These problem areas can then be fixed to maximize output and grow businesses.
While those were the top 3 uses of data science in which businesses can reap more from data science-driven insights. Some of which include bettering supply chains, improving sales, pushing for positive brand awareness and more.
How can I get Data Science to work for my brand?
The minutia of Data Science is expertly managed byData Scientists who develop strategies for analyzing data, plan how data is to be used for Machine Learning and determine what type of data needs to be analysed to benefit a business. The right set of data scientists can help a business grow exponentially even during a dynamic and turbulent external environment.
