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As interest in data science degrees continues to grow, universities need to arm faculty members and students with best-in-class tools for deep dive exploration of data. is a smart approach.
It starts with a trusted source of news data that librarians, professors and students turn to already for academic research—Nexis Uni. This powerful library database features thousands of authoritative news content aggregated from publishers around the world, as well as an archive going back decades.
Nexis Data Lab connects users to this same data, supporting key activities of students pursuing undergraduate or graduate degrees in data science and advanced analytics.
Before any analysis can take place, data scientists typically face some serious hurdles, starting with the sheer amount of data available and the need to wrangle the data into a format that can be more easily used. A 2020 survey of data science professionals found that data scientists spend nearly half of their time on data preparation, leaving far less time for more valuable analysis and interpretation of data.
Nexis Data Lab eliminates the need to wrangle the data by connecting users to data that has already been normalized and enriched with metadata. Our proprietary LexisNexis® SmartIndexing Technology™ analyses and tags documents based on subjects, industries, companies, organizations, people, and places. This makes it easier for users to jump into academic research and other data analysis in just a few steps.
Nexis Data Lab uses the Nexis Uni user interface as a starting point. Users can enter a search across the entire repository of news content or within their own saved, curated datasets. Need to narrow results sets further? Simply take the next step.
Users can examine the results from the original search string and then quickly refine results using post search filters. Want to narrow results to a particular time period? Adjust the timeline. Want to focus in on location by publication? See how many results appear for each location and select one or more locations to include. Users can then import these refined search results into the Jupyter Notebook environment.
The Jupyter Notebook environment empowers users regardless of their level of expertise. Novice users appreciate the available of open-source or LexisNexis developed Python libraries of code to support text mining and analytics. More experienced data scientists can write custom code to support analysis and create visualizations that tell a compelling story with the data.
Users can then export their analysis, visualizations, and document manifest to their laptops. The full-text data remains within Nexis Data Lab, removing any hosting requirements while allowing users to reproduce findings as needed.
Preparing students for a future career in data science demands hands-on experience. With Nexis Data Lab for Academic, universities empower students to achieve greater proficiency in real-world applications, such as data mining, algorithm testing and advanced analytics. Take a closer look today!