“Data science is an interdisciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from many structural and unstructured data”. – Wikipedia
To elaborate, Data Science is the ability to take a deeper look at the data and its indicators to develop a strong understanding of what it is that the data is telling us. The true expertise lies in recognizing what the valuable and actionable insights are and then applying those to help everyone from small business owners to large corporations in making those strategic decisions.
A real-world example most can relate to deals with Facebook. After a few scrolls, you notice the “Sponsored Ads” column reflecting products that you would be interested in potentially purchasing or content you would be interested in viewing. This could include various products that either you might have been looking at online or even a match made based on your taste or preference which could have been gathered from your previous social media engagement. How is it that Facebook can identify these patterns and so accurately and curate the things we like or want to see?
The answer lies in Big Data and Data Science technologies. These technologies are analyzing and predicting our taste and preferences in such great depth that it is no longer much of a mystery. Facebook’s advertisement platform is so accurate that it can gather and display highly accurate content based on Behavior, Demographics, Location, Interests, and Connections. According to CNBC, Facebook made $40 billion in advertising revenue last year, second only to Google.
Today, Data Science has many benefits for businesses, especially when considering the increasingly educated consumer market. With the whole concept of, “the customer is king” and having to appeal to customers to get their business, companies must be able to go the extra mile just to meet the minimum requirement. This is where implementing Data Science and utilizing data techniques becomes integral to a company’s success, allowing that organization to stand out from the rest.
How does Data Science help?
Several key methods in which Data Science is currently paving the road for success:
- Understanding the Consumer: Using Data Science in predictive analysis techniques allow companies to help tailor a customized service and allow for the ability to continuously track the customer’s preferences. This helps with drawing in new potential customers in addition to helping them retain the existing ones at a lower cost.
- Competitive Edge: With the majority of companies rushing to achieve larger market share and lead in their respective areas, Data Science has proven to be the key. Data Science helps an individual company to surpass others by providing strategic insights to channel company resources, thus giving a competitive edge over rivals.
- Targeted Advertisement: With such a vast amount of data flowing in from such a wide variety of sources and at an incredibly fast rate, it is becoming increasingly difficult to keep up. Companies are beginning to struggle to track and analyze said data with conventional technologies. By using modern data tools such as SQL and Python, data scientists can deal with heterogeneous and asymmetrical data to maintain and keep up with the data flow. This allows them to provide the necessary insights for targeted advertisements to various niche segments.
- Supply Chain: Data Science has proven to be an invaluable technological asset within supply chain management. What was once done by manual calculations and modeling is now completed faster and more accurately than ever before in history. The ability to predict demand and manage inventory levels, assess picking and delivery, and determining the shortest delivery routes, are just some of the many areas where Data Science has made waves and has become a dependency for many new companies.
As new Data Science techniques and algorithms continue to emerge, they will pave the way for new business avenues in formulating strategies and subsequently allow such companies to capitalize on them. The future of Data Science looks to be an exciting and promising one.
Author: Alvin Galesic