A few words of introduction
What data science stands for?
Data science is, as the name suggests, a study of data. It requires knowledge of different algorithms and high-tech tools. The primary goal of data science processes is to extract valuable insights from structured and unstructured data.
How can companies benefit from data science?
Every company collects a certain amount of data every day. The larger the company, the more data it collects. The amount of collected data is too large to be processed manually. It would take too long to obtain useful information – by the time we are finished, the information obtained will no longer be relevant. That’s why we need data science applications.
A team of data scientists who have advanced mathematical and statistical skills and a deep understanding of the industry in which your business operates, builds complex algorithms that process the collected data and provide your organization with valuable information about internal processes and customer behavior.
“Data Scientist (n.): Person who is better at statistics than any software engineer and better at software engineering than any statistician.” – Josh Wills, Director of Data Engineering at Slack
Furthermore, based on acquired information, data science-driven performs predictive analysis that allows you to make the right decisions. There is no limit to the business domain that can benefit from this solution. To prove it, below are some of the best data science applications in a variety of industries.
Data science applications in the financial sector
Financial professionals often struggle with huge amounts of data coming from various sources and forms: structured and unstructured data.
By applying data science techniques such as language processing, data mining, text analysis, and more, financial professionals can extract relevant information from raw data and use it to their advantage to make more effective decisions that generate more profit.
Fraud detection is one of the main areas of interest of any organization operating in the financial sector. Data science with AI technology offers an effective solution to reduce fraud.
Real-time predictive analytics – this data analytics application enables companies to identify potential fraud transactions and block them when unusual financial activity is detected. Thanks to this solution, companies can prevent numerous financial losses.
Risk management is one of the key factors in finance. The potential risk is closely related to changes in policy, customer behavior, market trends and competition strategies.
Thanks to data science applications, financial professionals can more accurately assess the creditworthiness of potential customers by analyzing their data taking into consideration many aspects.
Data science applications in the healthcare sector
Image analysis and diagnosis
The analysis of medical images is one of the main challenges faced by doctors every day when looking for the cause of a patient’s health problems. Medical reports usually include a CT scan, MRI, or x-rays.
Data science applications can now assist clinicians to automatically detect image abnormalities and diagnose the most likely disease that caused them. To do so, data scientists apply advanced computing technologies such as image recognition and machine learning.
Data science integration enables detailed data analysis, which is critical in developing advanced treatments. Now doctors can conduct an in-depth DNA analysis and determine how it affects the health of a particular patient.
This method enables geneticists to find biological connections between genes, various diseases, and the way a drug responds to them. Deploying a data science application is critical to analyzing gene responses to various drugs.
Drug discovery and development
Drug discovery and subsequent development is a time-consuming process that often costs pharmaceutical companies a fortune. Data science offers a revolutionary solution that significantly reduces the time spent on these processes.
Specially designed data science algorithms can predict the effectiveness of a new drug with high accuracy. Additionally, the drug manufacturing process can be shortened through real-time data analysis.
Data science applications in the search engine
Most of us use search engines such as Google, Yahoo, etc. on a daily basis. If you also belong to this group, it’s high time to find out – you already use data science applications every day!
Data science algorithms are responsible for delivering the search results that best suit your needs and without waiting. Typically, query results are ready in a fraction of a second. This is impressive considering the amount of data available on the internet.
Data science applications in image recognition
Another data science application that you are most likely already using without even knowing it is image recognition. The easiest example to represent this is Facebook.
Whenever we upload an image, for example with friends, Facebook automatically shows suggestions to tag the people depicted in the photo. How is this possible? This feature is supported by face recognition algorithms. Its accuracy grows every year, and more and more companies are using its business potential.
Data science applications in speech recognition
The last data science application that I will introduce in this article is speech recognition. In the last few years, it is gaining popularity, and it is being used by big companies for functions like Siri, Google Voice, etc.
This data science solution enables the use of electronic devices without clicking any buttons. It is a convenient solution as a substitute for writing, helpful, for example, for the elderly. Speech recognition accuracy has improved significantly recently.
A brief summary
Data science applications affect more and more aspects of our daily lives. This advanced technology makes it easier for us to perform various tasks successfully and saves time and money.
If you are an entrepreneur, you should definitely take a closer look at the solutions outlined above and take advantage of data science consulting to find out how your business can benefit from data science applications.