Data Science

What is data science?  

Data science is an extension of other data-analysis methods, such as data mining tools, statistics, and predictive analysis. Essentially, it aims to create order from the chaos of big data by sifting through it and organizing it in a meaningful, usable way. Among the methods that data science tool employs are: 

• Machine learning 
• Probability models 
• Data mining techniques 
• Statistical learning 
• Signal processing 
• Data engineering 
• Visualization 
• Uncertainty modelling 
• Computer programming 
• Pattern recognition and learning 

For example, it applies machine-learning algorithms to content – text, images, audio, video, numbers and more – to produce artificial-intelligence systems that do the work of humans – only faster and more efficiently. 

By understanding the value of data science and putting its power to work for you, businesses across most industries can effectively evaluate and address their challenges. 

Why is data science important? 

The five key reasons businesses should capitalize on data science consulting are to: 

• Keep pace and stay competitive 
• Make the most of the valuable data available to them to drive growth 
• Solve business problems 

• Better understand their customers 
• More effectively communicate their brand’s story 

Stay competitive 

We live and work in an increasingly data-driven society. In the age of big data, if you’re not putting in place data science capabilities, you risk being left behind. 

Drive growth 

Most businesses have a great deal of data at their disposal, from customer information and financial data to social media commentary and material on competitors. Data science consulting empowers companies to judiciously take advantage of this information for their benefit and drive the growth of the business going forward. 

Solve problems 

Having a data science team that can help you clearly define and analyze a problem and establish a rule-based system and plan for tackling it is essential. Once you uncover the exact needs of your business, you’re in a much better position for your data science processes and technologies to do the hard work effectively and efficiently. 

Understand customers 

Your customers are your bread and butter; they are incredibly valuable to your business. Using data science techniques, such as data mining tools and data analysis, you can gather a great deal of enhanced business intelligence about your customers. You can then use this information to your advantage--to personalize your interaction with your customers, to impact the further growth, development, and engagement of your customer base, and to solidify the success of your brand. 

Communicate your message 

Similarly, data science allows companies to communicate their brand story in a more engaging, powerful way. When brands and companies have a robust overarching strategy for using data science, they can better share their messaging with their target audience and cultivate a stronger brand connection. 

Common methods of data science 

There are a few common methods for data research and analysis by most scientists. 

• Exploratory Data Analysis (EDA): Through statistical and visual methods, EDA helps data scientists understand the main characteristics of a data set, identifying patterns, trends, and outliers. 
• Statistical analysis: Statistical techniques are applied to draw meaningful inferences from data, providing a solid foundation for decision-making and hypothesis testing. 
• Machine learning: Algorithms are developed and applied to enable systems to learn and improve performance without explicit programming, covering supervised and unsupervised learning techniques. 
• Data mining: This involves extracting patterns and knowledge from large volumes of data, uncovering hidden relationships and trends that can inform decision-making. 
• Predictive modeling: Data scientists build models to predict future outcomes based on historical data, facilitating forecasting, and scenario analysis.  

Benefits of data science 

Data science provides numerous benefits, including: 

• Informed decision making: Supporting decision-makers with data-driven insights, fostering more effective and strategic decision-making. 
• Business innovation: Identifying new opportunities and areas for improvement, driving innovation and competitiveness. 
• Competitive advantage: Gaining insights that drive innovation, enhance market understanding, and contribute to market leadership. 
• Efficiency improvement: Optimizing processes and resource allocation based on data-driven insights for increased efficiency and productivity.  

How LexisNexis Supports data science research 

LexisNexis provides essential resources for data science practitioners. With Nexis^® Data+, users can access a vast repository of over 36,000 licensed sources and 45,000 total resources in more than 37 languages. This extensive database empowers data scientists to access accurate and up-to-date information for their analyses and models, contributing to the success of their data science initiatives. 

Learn about Nexis^® Data+