Roksolana Diachuk

Links: - Slides link: https://speakerdeck.com/roksolanad/modern-data-pipelines-in-adtech-life-in-the-trenches - Donations to support Ukraine: https://savelife.in.ua/en/ Free data engineering course: https://github.com/DataTalksClub/data-engineering-zoomcamp Join DataTalks.Club: https://datatalks.club/slack.html Our events: https://datatalks.club/events.html

Come to hear a story, leave making plans for a trip to Ukraine. We will tell you about how Scala came to Ukraine, who was the first to use it and how, but also who are the people of the Ukrainian Scala community, what are their thoughts and plans, and how you can get involved.

"Alice And The Return To The World Of Pods And Higher-Order Functions" by Roksolana Diachuk at Functional Scala 2022. Alice discovered in the records of the past that all the pods disappeared. Desperate to save her friends Alice needs to travel back to the world of pods and higher-order functions. To build a bridge with that world Alice is going to rely on the power of ZIO K8s. Join Alice in her exploration of this library and her rescue mission. Grab Your Early Bird Tickets for the Functional Scala 2023! ➡️ https://www.eventbrite.com/e/functional-scala-2023-tickets-481896564597 #FunScala2022 #scala #zio #functionalprogramming #functionalscala #scalaconference #scaladeveloper

AdTech is a very innovative sphere and brings more and more attention now with the removal of cookies. Captify is one of the industry players and is the largest independent holder of user search data outside of Google. But how do companies like Captify leverage big data to find solutions for advertising problems? Which problems can be solved using big data? And where’s Scala in all of that? You will find out in this talk by Roksolana Diachuk! #functionalscala #FunScala2021 #Scala #zio #Ziverge #zymposium #functionalprogramming #scaladeveloper #zioscala

Alice found out that her friends from the world of pods and higher-order functions are in danger. The key to their happy future is their turbulent past. Alice is going to use the power of Delta Lake to explore the records of the past and find a way to save her friends. https://2022.scala.love https://twitter.com/scala_love

Title: Alice and Mad Hatter: Predict or not to predict Alice and Mad Hatter should solve a mystical riddle that will help them to find the way back home. Alice is a big data engineer and Mad Hatter is a skilled data scientists. In order to solve the riddle they need to build a prediction using a machine learning model. Will knowledge of Scala help Alice to find a solution? And will she be able to collaborate with the Mad Hatter? You will find out in this talk.

This talk was given at ScalaCon on May 19th, 2021 by Roksolana Diachuk. Alice and the lost pod: practical guide to Kubernetes in Scala Following Alice’s adventure to the world of pods and higher-order functions. Now Alice is a professional Scala developer and over the years she has forgotten her trip to the world of pods and higher-order functions. But this time a new adventure found her. Alice needs to bring back the pod home using her knowledge of Scala. Will she be able to discover the link between Scala and Kubernetes and save her friend? You will find it out in this talk. Speaker: Roksolana Diachuk - Captify https://www.twitter.com/dead_flowers22 --- ScalaCon is organized in partnership by 47 Degrees, Skills Matter, Scala Center, and Lightbend.

Roksolana works as a Big Data Engineer at Captify. She is a speaker at technical conferences and meetups, one of the Women Who Code Kyiv leads. She is passionate about Big Data, Scala, and Kubernetes and she always loves to learn something new. In this episode Roksolana talked about her journey , her learning experience and about some challenges that she has encountered during her studies and work. We talked about the lack of women in Tech and how this can be changed. She shared some tips to create an inclusive culture in Tech industry. Roksolana talked about the activities of Women Who Code organisation and about how she got inspired by the community. Listen to the full episode and learn more about the journey of Roksolana! Check out her Website: https://roksolanadiachuk.wixsite.com/roksolana-d ---------------------------------------------------------------------------------------- 00:00 - Introduction 00:53 - The education path 01:38 - Big Data engineering path 02:23 - Challenges during her studies 03:12 - Working during studies 05:28 - Guidance at work 06:31 - The progress in Roksolana's career after university 09:10 - The obstacles and challenges that Roksolana has faced 16:38 - Why there are few women in Tech? 19:37 - Empowered women empower women 21:35 - Women Who Code community 24:45 - Advice for anyone who wants to start their journey in Tech 26:07 - Ways to build inclusive culture in the workplace 29:07 - Her journey of becoming a speaker 31:27 - Advice ---------------------------------------------------------------------------------------- Podbean link: https://wiemzin.podbean.com/ Google podcast: https://podcasts.google.com/feed/aHR0cHM6Ly9mZWVkLnBvZGJlYW4uY29tL3dpZW16aW4vZmVlZC54bWw Spotify: https://open.spotify.com/show/0zRbfj8S0AKa4EhwyAAvHD Pocket Casts: https://pca.st/o944lr7p Instagram account: https://www.instagram.com/techtakpod/ ------------------------------------------------------------------------------------------------------------ Music from Uppbeat (free for Creators!): https://uppbeat.io/t/cruen/in-the-now License code: YBQKKTXT2DQXSTA1

We talked about: 00:00 DataTalks.Club intro 02:19 Roksolana’s background 04:26 A Big Data Engineer’s typical day at work 07:18 Big Data Engineer’s tools 08:04 Alice discovers Kubernetes 09:12 The difference between big data engineers and usual data engineers 11:07 Data Engineers’ skills 13:56 Data scientist role from the perspective of a data engineer 15:32 Big data engineers’ tools vs data scientists’ tools 16:26 Communication between big data engineers and data scientists 18:54 Example project walkthrough 23:40 Deployment 24:49 How much should data scientists know about data engineering? 26:32 How can data scientists acquire knowledge about data pipelines? 27:30 Should data engineers become more like data scientists? 30:53 Advice for analysts and scientists for transitioning into engineering 34:53 Database recommendations 36:07 Data engineering and infrastructure 39:09 Monitoring and alerts 41:00 Do data scientists need to set up monitoring? 42:04 Do data engineers depend on data scientists for something? 43:37 Data documentation 44:41 Documentation tools 46:14 How much data engineering should a data scientist know? 48:26 Trying out Kubernetes 49:29 Choosing a path for graduates – engineering or science? 51:16 Project recommendations to see if you like data engineering 53:28 Dataset sources 56:08 Pre-built tools vs hiring a data engineer 58:05 Challenges in the work of a data engineer 1:00:40 Recommended courses and books for data scientists Links: - Twitter: https://twitter.com/dead_flowers22 - LinkedIn: https://www.linkedin.com/in/roksolanadiachuk/ Join DataTalks.Club: https://datatalks.club/slack.html Our events: https://datatalks.club/events.html Conference: https://datatalks.club/conferences/2021-summer-marathon.html