Name: Data Science utilization to become the most valuable 🍕PIZZA🍕 brand - SLICE
Start: 2019-12-17T18:00:00+01:00
End: 2019-12-17T20:00:00+01:00
Location: Faculty of Technology and Metallurgy, Amphitheatre

We are very excited to announce the 9th, 🍕PIZZA Data Science Meetup - Tuesday, 17.12.2019, from 18:00 to 19:30.
Dr. Igor Dimoski and MSc. Klimentina Ratkova from Slice, will give an interesting talk about how Slice is using data analytics and data science to become the most valuable pizza brand worldwide.

Snacks, 🍕and drinks provided by Slice.
https://slicelife.com
https://slice.mk

Agenda:
- 17:45 - 18:15 - Gathering and networking (🍕 and drinks)
- 18:15 - 19:00 - Presentation by Igor Dimoski and Klimentina Ratkova
- 19:00 - 19:30 - Networking (snacks and drinks)

The event is also supported by IEEE chapter for Theory of Information, and IEEE chapter for Education, Robotics and Automatics, and Systems, Human and Cybernetics.

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More information about the talk.

The first part of the talk is aimed to make clear what is global pizza industry today and how it has changed in last decade due to digitalization of the orders. Igor will explain how Slice is technology driven global company that connects local pizza makers and pizza eaters to enrich their lives through the power of specialization and expertise. Today, local pizzerias are thriving against corporate competitors with the tech, marketing, data, and services that Slice provides. The company’s core products enable online ordering, generate marketplace demand, and facilitate customer loyalty. To do that, large data sets should be used to enhance the experience of the customers and the restaurants as well. Data Analytics and Data Science team is equipped and in growth, since more and more predictive analytics, machine learning, deep learning … projects became so important for reaching the goals. First showcase – Temporal User Behavior Predictive Analysis.
In the second part of the talk, Klimentina will explain the importance of the Data Development for preparing base ground for advanced data analysis processes. Slice has many teams that work together as a whole, like sales team, customer support, marketing and many others. Each of them needs additional tools to perform their everyday activities like CRM system, tools for Marketing, integration with other 3th party systems and all of them are generating valuable information in different repositories, data that needs to be gathered in one centralized repository that will be easily accessible for the data analysts and data scientists.
Second Showcase: Airflow ETL pipeline from centralized Data Lake to Redshift Datawarehouse and converting data into valuable business information

Bio:
Igor Dimovski is a newbie in the filed of Data Science, but he is a beast in the area of mathematics applied in the industry. He is now part of the Data Science team at Slice. Igor holds a PhD in Mathematics education and has several publications in the field of robotics, due to the 7 years of experience as researcher in Institute for Advanced Composites and Robotics. Previously, he was math teacher dedicated to work with gifted students and math competitions preparation. He is author of several math textbooks.

Klimentina Ratkova is Data Developer at Slice. She holds MsC degree in Intelligent Information Systems from FINKI.
Her main responsibilities at Slice are design, implement and optimize data pipelines to produce clean and unified data from multiple data sources, extend the existing AWS Redshift DWH according reporting and analysis needs.
She is around 10 years in the IT industry. Previously worked at Seavus as Senior BI Developer, where was implementing DWH, designed multidimensional OLAP cubes in MS SQL Server, worked on variety reporting projects with tools like SQL Server Reporting Services, Power BI and MicroStrategy.

Hristijan Gjoreski

Goran Stojanovski

Valentin Gjorgjioski

Gjorgji Madjarov

Data Science Macedonia

Technology

Business Intelligence

Big Data

Machine Learning

Data Analytics

Data Visualization

Predictive Analytics

Data Mining

Data Science

Data Science using Python

Data Science for Business

Data Science utilization to become the most valuable 🍕PIZZA🍕 brand - SLICE

Faculty of Technology and Metallurgy, Amphitheatre

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Data Science utilization to become the most valuable 🍕PIZZA🍕 brand - SLICE

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