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Why R? - Data Optimisation Network

Wydarzenie:
Why R? - Data Optimisation Network
Typ wydarzenia:
Spotkanie
Kategoria:
IT
Tematyka:
Data:
15.03.2021 (poniedziałek)
Godzina:
19:00
Język:
angielski
Wstęp:
Bezpłatne
Miasto:
Miejsce:
Online Webinar
Adres:
On your computer
Prelegenci:
Opis:

stream: https://youtu.be/5TQfLU-58Y4

speaker: Gaurav Pahuja None

title: Data Optimisation Network


- webinars http://whyr.pl/webinars/

- subscribe http://whyr.pl/subscribe/

- slack http://whyr.pl/slack/

- meetup http://tiny.cc/WarsawRUG


#### Speaker: Gaurav Pahuja

Process-oriented Data Scientist with 9 years of experience. I am a conscientious person who works hard and pays

attention to detail. Experienced in interpreting and analysing data to drive the growth of the company. I am an

effective communicator with excellent interpersonal relationship and management skills. My greatest strength is strong

analytical thinking, which enables me to furnish insights, analyse data, build machine learning and deep learning

models to leverage business to guide their decisions. I am also experienced in coordinating with stakeholders. I

create content on YouTube to help others in the data science field; I am a qualified gym instructor and personal trainer.


### Talk: Data Optimisation Network

The Data Optimisation Network (DON) seeks to improve business decision-making using machine intelligence and data science

techniques. It predicts customer behaviour through data-driven insights to enable the business to acquire new customers

intelligently. The key problem with most of the companies is not just to acquire more customers, but it is to acquire the right customers and retain them. Companies consider the cost of customer acquisition as an important measure in evaluating how much value a customer will bring to their businesses. DON will empower teams such as Customer Value

Management, Marketing, Sales, Continuous Improvement and more via interactive dashboards available in real-time.

These dashboards will enable research, and the understanding of market trends and behaviours. The demonstration of the app is based on the utility sector. However, the data is anonymised for the solution but depicts the real-life problem.


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