Women in Big Data

NEW PLACE - NEW GOOGLE for startups CAMPUS

All talks will be held in English.
18:00- 18:30- Gathering, mingling

18:30 - 19:00 - First talk with Galit Koka Elad: "Data preparation - common challenges, best practices and the cost"

About: How to powerfully manage data warehouses in the era of exponentially growing data. We will discuss the challenges faced and the common architectures used to overcome them. We will discuss distributed, shared nothing MPP solutions as well as MPP solutions that decouple storage and compute.

Common practices and their prices:
** Data preparation (indexing, materialized views, distribution keys).
** CAP theory
** Streaming
** Micro batches

Bio: Product manager at SQream technologies. Developing GPU Data Warehouse that achieves maximum performance, with maximum flexibility and minimum disk footprint for BI of large scale data stores.

Data architect and an expert in RDBMS and other Big Data solutions. Leading Business Development, Presentation & Marketing.

19:10 - 19:40 - Second talk with Einat Borohovich "Time Series-Statistics from Theory to Practice. What’s between the sea waves and the stock market?"

About the talk:
Time series describe many processes in real life. In this talk I will first give a short theoretical introduction to time series followed by examples of where in real-life time series can be found.
I will then demonstrate time series forecasting using statistical and machine learning methods.
We will end with tips and tricks for how to correctly analyze time series. A cheat sheet for everyday use will be provided for attendants.

Bio: Einat has been working at Elbit Systems ISTAR division for the past 10 years. She is experienced with various positions in the Unmanned Air Systems world. Her current challenge focuses on researching ways to predict operational online data.
She gained a BSc. in Industrial Engineering and Management from the Technion, and International MBA with specialization in East Asia from University of Haifa.
In addition, she is currently pursuing a master’s degree in statistics, and is interested in the application of statistics on real life problems.

19:50 - 20:20 - Third talk with Noa Stanger "It's not only about how big the data is, it's also about how good the data is"

About the talk:
We talk a-lot about big data, I would like to talk about quality when dealing with big data quantities.
The AI field opens a whole lot of different ways for handlng data, a whole new set of data processes which are new and significant to this field.
I will dive into a few of these significant processes with examples of some of our projects focusing on the labeling process, human in the loop, best practices, challenges and potential when handling this data.

About myself:
Leading the data processes for AI in WIX's data science group for the past year and a part of WIX for the past 4.5 years.
Tailoring data solutions for WIX's various AI projects and managing these data projects from the research stages until they are put into production.