Systematic study of data to allow companies to answer business-critical questions, solve problems and make well-informed data-driven decisions
What is data science?
Data science is the systematic study of data. It draws on a combination of scientific methods, processes, statistics, algorithms and technology to extract, evaluate, visualise, manage and store both structured and unstructured data. Armed with the business intelligence and valuable insights that come from this data, companies can answer business-critical questions, solve problems and make well-informed data-driven decisions.
Data science is an extension of other data-analysis methods, such as data mining, statistics and predictive analysis. Essentially, it aims to create order from the chaos of big data by sifting through it and organising it in a meaningful, usable way. Among the methods that data science employs are:
- machine learning
- probability models
- data mining
- statistical learning
- signal processing
- data engineering
- 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?
- 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
This one can be a bit trickier for companies. Data science is a must-have for problem-solving, but key to that is that businesses first need a truly in-depth understanding of the actual challenges they face. Having a data science team that can help you clearly define and analyse 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 effectively and efficiently do the hard work for you.
Communicating your message
Nexis® DaaS enables your organisation to connect to LexisNexis’ world-class database through an application programming interface (API) to get the relevant, high-quality data you need.
- uses predictive analytics
- builds quantitative financial models
- powers machine-learning applications
Our database provides access to such information as:
- domestic and global news
- social commentary
- company, industry and legal intelligence
- magazines and trade publications
- radio and TV broadcast transcripts
- intellectual property (IP) and patents data
- press releases
What’s more, it’s our vast experience with cutting-edge technology and the sheer volume of the information we provide that distinguish us from other DaaS offerings. Nexis DaaS draws from 80,000 sources, and we add 4.5 million documents to our collection daily. It comprises data on 80 million companies, includes information in 75 languages, covers more than 13,000 topics and encompasses more than 100 countries.
But Nexis DaaS doesn’t just provide access to the necessary technology and content. The service also enables your data science team, so it can:
- evaluate the competitive landscape to support your strategic planning
- inform PR and marketing campaigns to strengthen your brand and drive revenue
- use trend analysis to identify domestic and international movements so your company can quickly and proactively respond proactively to market opportunities and disruption
- integrate big data into machine learning to increase the efficiency and effectiveness of your critical business processes, such as risk management
With the valuable intelligence and insights you uncover with Nexis DaaS, you can harness the robust power of data to make well-informed, more accurate decisions and ultimately drive business gains.
Frequently Asked Questions
Answers to some popular questions
Data science is the systematic study of data. It draws on a combination of scientific methods, processes, statistics, algorithms and technology to extract, evaluate, visualise, manage and store both structured and unstructured data. Armed with the business intelligence and valuable insights that come from this data, companies can answer business-critical questions, solve problems and make well-informed data-driven decisions. Read more
The five key reasons businesses should capitalise on data science 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
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