2 min read
Raw data is of no use until it is categorized into data sets to communicate results. Data helps in determining the cause of the problem and allows organizations to visualize relationships between events in different locations, departments, and systems. Here, we take a look at Data Science, its analysis, and some of its applications in various industries.
What is data science?
Data science involves developing methods to record, store, and analyze information. It is used to extract knowledge and useful insights from structured/unstructured data. It's goal is to understand the flow of information and identify prospective business opportunities.
The study is an interdisciplinary field and includes statistics, computer science, analysis, and machine learning. Computer science involves creating programs and algorithms that record and process data, while statistics is the collection, analysis, interpretation, presentation, and organization of data.
Applications of Data Science
Data science has become the fuel that is helping industries and businesses accelerate its value to the market at scale.
1. Healthcare: Data science in healthcare is medical imaging. It enables the computers to interpret MRIs, X-rays, mammography, and similar images. It also helps identify patterns in the data to detect tumors, artery stenosis, organ anomalies, etc. Additionally, it can also predict diseases, helping medical professionals offer personalized healthcare recommendations.
2. E-commerce and Retail Industry: The field is profitable for the retail and e-commerce industry as it helps predict purchases, profits, loss, and can encourage customers into making a purchase through personalized suggestions. Retail brands analyze data to create customer profiles and strategic marketing and targeting plans.
3. Transportation: Big data analysts focus on reducing freight costs through efficient routing and provide dynamic price matching of supply to demand.
4. Finance: Companies use business intelligence tools to analyze data trends. The use of data science has improved detection of anomalies and fraud. In finance, it analyzes and mitigates the risk involved per transaction.
5. Manufacturing: Data science has many practical applications in manufacturing. These include the use of fuel, maintenance and fleet operations. It also helps companies analyze precisely all factors affecting business growth.
6. Banking: Data science has led banks to manage the information from multiple channels in real-time. Banks use this in the areas of customer service, fraud detection, forecasting, understanding consumer sentiment, customer profiling, and target marketing.
Conclusion
Data science also involves machine learning - a field of technology where scientists use the information to teach computers. The company may use the scientific method to run tests and extract results that can provide meaningful insights about their users.
Specialized and innovative techniques are required to use data science in the business. It acts as an umbrella that encompasses all of the tools and technologies used during the life cycle stages of data. The field has come a long way from scratching numbers into papyrus, up to the modern-day punching of numbers into a keyboard.
