Exploring the modern data landscape

This was a presentation that I gave at the inaugural data meetup by Siligong Valley in May 2021 in Wollongong, Australia.

Transcript

1. SILIGONG.DATA Photo by Isaac Smith on Unsplash EXPLORING THE MODERN DATA LANDSCAPE 1
2. - Data Reporting Coordinator at University of Wollongong 
 - Hospital Scientist —> Software Engineer —> Business/Data Analyst 
 - rachelnacilla.com HI, I’M RACHEL 2
3. Source: The 2020 Data Landscape Chart by Matt Turck https://mattturck.com/data2020/ 3
4. - Data is information that has been translated to a form that a computer can process. - Data can: - Be personal - Be transactional - Come from the web - Come from sensors i.e. IoT WHAT’S THE DEAL ABOUT DATA? 4
5. DATA IS THE OIL OF THE 21ST CENTURY 5
6. - Technology is evolving and improving at the speed of light. With that comes an increase in data processing speeds and the addition of data creators and consumers. - Data is the key to smooth operation of companies. Without data, progress would halt and we can’t make decisions. - The modern data ecosystem is expanding! Traditional tools and methods of analysis may no longer cut it. - Need new tools and techniques, which paves the way to new knowledge and insight. - But data can’t do much without people. WHAT’S THE DEAL ABOUT DATA? 6
7. - Data Engineer - Data Scientist - Data Analyst - Profession/industry speci fi c analyst - Business Analyst MODERN DATA LANDSCAPE KEY PLAYERS 7
8. - Develop and maintain data architectures - Make data available for business operations and analysis - Extract, integrate and organise data - Clean, transform and prepare data - Store data and manage data repositories to be used. - Tools - SQL - Python or R - Databases - Data integration platforms like Mulesoft DATA ENGINEER 8
9. - Analyse data for actionable insights - Build machine learning or deep learning models - Train past data to build predictive models. - Pick up on problems that will have most value once addressed. - Analyse data to answer questions. “How many Twitter followers am I likely to get next month?” - Tools and Knowledge - SQL - Python or R - Excel - BI Tools, e.g. Tableau and Power BI - Mathematics and statistics - Databases - Building data models DATA SCIENTIST 9
10. - Analyse data to answer questions and make business decisions. - Inspect data for deriving insights, fi nding correlations and patterns. - Present and visualise data to tell a story. - Profession speci fi c data analysts include marketing analysts, fi nancial analyst, business analyst. - Tools and Knowledge - SQL - Excel - Python or R - Business Intelligence tools e.g. Tableau and Power BI DATA ANALYST 10
11. - Make business decisions with the help of data analysts and data scientists. - Provide business intelligent solutions by monitoring data on di ff erent business functions. - Use data to extract insights to improve business processes and performance. - Tools and Knowledge - SQL - Excel - Business Intelligence tools e.g. Tableau and Power BI BUSINESS ANALYST 11
12. - Mathematician, computer scientist and trend-spotter. - Big data —> the rise of the data scientist. - Machine learning (automating model building) and deep learning (training a computer to perform human-like tasks) is in their toolbox. DATA SCIENCE SPOTLIGHT ON: 12 Source: the Complete Data Science Landscape by Zohaib Ahmed https://www.kaggle.com/general/210722
13. - High performance computing (or supercomputing) - processing data and performing complex calculations at high speed. - Australia has 4 supercomputers for research purposes. - Magnus (Pawsey - Perth) - FlashLite (UQ) - MASSIVE (Monash) - GPU - Gadi (NCI - ANU) - Mechanisms of protein binding and receptor inhibition in COVID-19. - Bush fi re predictive modelling. HIGH PERFORMANCE COMPUTING FOR RESEARCH SPOTLIGHT ON: 13
14. Number of cores in use on Gadi vs Areas of Study Captured 20 May 2021 12:38 AM AREAS OF RESEARCH 14
15. - Let’s connect on social media! - Twitter: @rachelintweets - Instagram: @rachelinjpg THANK YOU! 15