We establish the stability of independence for any pair of random variables by their corresponding Brockwell transforms (Brockwell, 2007) beyond the non-atomic condition that is naturally imposed on their distributions, thereby generalizing the proposition originated by Cai et al. Open Skills Library - Frequently Asked Questions.View a PDF of the paper titled Statistical Independence and the Brockwell Transform - From an Integral Equation Perspective, by Xingzhi Wang View PDF HTML (experimental) Abstract:Statistical independence is a notion ubiquitous in various fields such as in statistics, probability, number theory and physics. Statistics of US Businesses (SUSB) (2019). Standard occupational classification manual. United States (2022)Įxecutive Office of the President, Office of Management and Budget. North American Industry Classification System. Įxecutive Office of the President, Office of Management and Budget. In: 2017 International Conference on Current Trends in Computer, Electrical, Electronics and Communication (CTCEEC), Mysore, India, pp. Mishra, S., Misra, A.: Structured and unstructured big data analytics.

Vassiliadis, P.: A survey of extract-transform-load technology.

In 2017 IEEE 7th International Advance Computing Conference (IACC), pp. Mukherjee, R., Kar, P.: A comparative review of data warehousing ETL tools with new trends and industry insight. Wiley, Hoboken (2004)Įdjlali, R., Beyer, M.A.: Magic quadrant for data warehouse and data management solutions for analytics, Gartner (2016) Kimball, R., Caserta, J.: The Data Warehouse ETL Toolkit: Practical Techniques for Extracting, Cleaning, Conforming, and Delivering Data. Paul College of Business & Economics (2021) Wilkins, D.: An in-depth analysis of the data analytics job market. Stanton, W.W., Stanton, A.D.: Helping business students acquire the skills needed for a career in analytics: a comprehensive industry assessment of entry-level requirements. Hudson, D.: Tips for navigating the academic job market. Manyika, J., et al.: Big data: the next frontier for innovation, competition, and productivity. The resulting two dashboards provide “one-stop” search places for career research and shorten the cycle time of tedious searches.ĭavenport, T.H., Patil, D.J.: Data scientist: the sexiest job of the 21st century. Interactive and user-friendly visualizations were created in Microsoft Power BI, resulting in two dashboards providing students with current information on the job market landscape: (i) Analytics Career Prospect, which offers data on top occupations, salary and wage information, job posting trends, required skills information, hiring industries and companies’ information, education information, and job location and (ii) Job Market Consultation, which provides a more in-depth analysis of required skills, industry performance and description, and specific job information reports such as Industry Insight, Industry Snapshot, Industry Supply Chain, Industry staffing pattern, and job posting analytics. A relational database schema was then created to connect the ETL data output for visualization and analysis. The resulting data underwent manipulation using Microsoft Power Query and Microsoft Excel and were stored in Microsoft SharePoint, with structured data in a flat table and unstructured data in a standalone file with a URL generated for linking the data. Multiple analytics-related industry and occupation data were extracted and aggregated from third-party sources, primarily from Lightcast and US Government Official Data. This paper proposes an Extract Transform and Load (ETL) framework and Data Visualization method to provide students with easy-to-use and intuitive occupation information. Tailored industry and occupation information for analytics graduates is vital to make a well-informed career decision, especially for Boston University Metropolitan College (BU MET) Applied Business Analytics students and graduates.

Extract transform and loading