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Solve Biz Problems with Data Visualization

9 July @ 11:30 am - 1:00 pm SMT

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We’ve all used Data Visualization reports and dashboards to view and observe data. But, Data Visualization was never meant for just reports! Join this session to learn how designing What-If Scenarios, using Open Source languages, and combining algorithms with Data Visualization brings you closer to your answers faster. The session is designed for beginners and intermediate users. Some experience in R and Data Visualization may be helpful, but not required.

FAQ

Q. Is it free to join?
A. Yes! Participation is free, but slots are limited, so please register early!

Q. I’m based outside of Singapore. Can I still join?
A. Absolutely! This is an APAC-wide online event. You can join from any part of the world.

Q. Is it only for women?
A. Just like our regular She Loves Data #MeetUp events, this online webinar is open to all professional men and women. #HeLovesData too!

Q. Is this an interactive discussion or just a ‘listen-in’ webinar?
A. Definitely interactive! Your thoughts, feedback and questions are most welcome and will be entertained during the polling and live Q&A portions at the end of the discussion.

Q. What if something comes up and I need to retract my registration?
A. Please be considerate and let us know if you won’t be able to attend the online meetup a day in advance, so we can offer your place to somebody else.
Contact us and we’ll help you. The email you need is [email protected]


Speakers

 

Neil Kanungo
Data Scientist @TIBCO Software

Neil is a Data Scientist for TIBCO Software, and based in Seatte, Washington. Neil takes passion in helping others learn advanced analytics and creating transformational change. When he’s not working he likes to enjoy the great outdoors with his fiance and dog in the beautiful Pacific Northwest. He also enjoys a wide variety of visual art, experiencing new cultures, and playing pinball!

Partners

 

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Details

Date:
9 July
Time:
11:30 am - 1:00 pm SMT
Event Tags:

Venue

Online

Organizer

She Loves Data
Email:
info@shelovesdata.com
Website:
www.shelovesdata.com