DataTalks.Club

By DataTalks.ClubTechnology

DataTalks.Club episodes

June 18, 2021Analytics Engineer: New Role in a Data Team - Victoria Perez Mola
Links:
https://www.notion.so/Analytics-Engineer-New-Role-in-a-Data-Team-9decbf33825c4580967cf3173eb77177

https://www.linkedin.com/in/victoriaperezmola/

Join DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.html
Conference: https://datatalks.club/conferences/2021-summer-marathon.html
1 hr
June 11, 2021Data Governance - Jessi Ashdown, Uri Gilad
We talked about:
Jessi’s background

Uri’s background

Data governance

Implementing data governance: policies and processes

Reasons not to have data governance

Start with “why”

Cataloging and classifying our data

Let data work for you

The human component

Data quality

Defining policies

Implementing policies

Shopping-card experience for requesting data

Proving the value of data catalog

Using data catalog

Data governance = data catalog?

Links:
Book: https://www.oreilly.com/library/view/data-governance-the/9781492063483/

Jessi’s LinkedIn: https://www.linkedin.com/in/jashdown/

Uri’s LinkedIn: https://linkedin.com/in/ugilad

Uri’s Twitter: https://twitter.com/ugilad

Join DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.html
Conference: https://datatalks.club/conferences/2021-summer-marathon.html
58 min
June 04, 2021What Data Scientists Don’t Mention in Their LinkedIn Profiles - Yury Kashnitsky
We talked about:
Yury’s background

Failing fast: Grammarly for science

Not failing fast: Keyword recommender

Four steps to epiphany

Lesson learned when bringing XGBoost into production

When data scientists try to be engineers

Joining a fintech startup: Doing NLP with thousands of GPUs

Working at a Telco company

Having too much freedom

The importance of digital presence

Work-life balance

Quantifying impact of failing projects on our CVs

Business trips to Perm: don’t work on the weekend

What doesn’t kill you makes you stronger

Links:
Yury's course: https://mlcourse.ai/

Yury's Twitter: https://twitter.com/ykashnitsky

Join DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.html
1 hr
May 28, 2021Becoming a Data-led Professional - Arpit Choudhury
We talked about:
Data-led academy

Arpit’s background

Growth marketing

Being data-led

Data-led vs data-driven

Documenting your data: creating a tracking plan

Understanding your data

Tools for creating a tracking plan

Data flow stages

Tracking events — examples

Collecting the data

Storing and analyzing the data

Data activation

Tools for data collection

Data warehouses

Reverse ETL tools

Customer data platforms

Modern data stack for growth

Buy vs build

People we need to in the data flow

Data democratization

Motivating people to document data

Product-led vs data-led

Links:
https://dataled.academy/

Join our Slack: https://datatalks.club/slack.html
1 hr 1 min
May 21, 2021How to Market Yourself (without Being a Celebrity) - Shawn Swyx Wang
We talked about:
Shawn’s background and his book

Marketing ourselves

Components of personal marketing

Personal brand for an average developer

Picking a domain: what to write about?

Being too niche

Finding a good niche

Learning in public

Borrowed platforms vs own platform

Starting on social media: Picking what they put down

Career transitioning: mutual exchange of value

Personal marketing for getting a new job

Getting hired through the back door

Finding content ideas

Marketing yourself in public — summary

Open-source knowledge

Internal marketing: promoting ourselves at work

Signature initiative

Public speaking

Wrapping up

Discount for the coding career book

75% of the engineering ladder criteria are not technical
Links:
Shawn's personal page: https://www.swyx.io/

Twitter: https://twitter.com/swyx

Book of the week page: https://datatalks.club/books/20210510-the-coding-career-handbook.html (with a discount for DTC members!)

Join DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.html
1 hr 3 min
May 14, 2021From Physics to Machine Learning - Tatiana Gabruseva
We talked about:
Tatiana’s background

12 career hacks and changing career

Hack #1: Change your social circle

Hack #2: Forget your fears and stereotypes

Hack #3: Forget distractions

Hack #4: Don’t overestimate others and don’t underestimate yourself

Hack #5: Attention genius

Hack #6: Make a team

Hack #7: Less is more. Forget about perfectionism

Hack #8: Initial creation

Hack #9: Find mentors

Hack #10: Say “no”

Hack #11: Look for failures

Hack #12: Take care of yourself

Kaggle vs internships and pet projects

Resources for learning machine learning

Starting with Kaggle

Improving focus

Astroinformatics

How background in Physics is helpful for transitioning

Leaving academia

Preparing for interviews

Links:
Mock interviews: https://www.pramp.com/

Learning ML: https://www.coursera.org/learn/machine-learning and https://www.coursera.org/specializations/deep-learning

Python: https://www.coursera.org/learn/machine-learning-with-python

SQL: https://www.sqlhabit.com/

Practice: https://www.kaggle.com/

MIT 6.006: https://courses.csail.mit.edu/6.006/fall11/notes.shtml

Coding: https://leetcode.com/

System design: https://www.educative.io/courses/grokking-the-system-design-interview

Ukrainian telegram groups for interview preparation: https://t.me/FaangInterviewChannel, https://t.me/FaangTechInterview, https://t.me/FloodInterview

Join DataTalks.Club: https://datatalks.club/slack.html
1 hr 7 min
May 07, 2021What I Learned After Interviewing 300 Data Scientists - Oleg Novikov
We talked about:
Oleg’s background

Standing out in recruitment process

NextRound — a service for free mock interviews

Why rejections are generic

Starting NextRount — preparing a list of situations

Steps in the interview process

Read the job description!

CV is your landing page

Take-home assignments

Questions about your past experience

Hypothetical case questions

Technical rounds

Handling rejections

What to do after receiving an offer?

Do recruiters pay attention to age?

Getting a job with a PhD — it’s a cold start problem

Should I answer rejection emails?

Negotiating when my salary is low

Should I apply for jobs that require 5 years of experience?

Tricking applicant tracking systems

What else Oleg learned after interviewing 300 data scientists

How a horse's ass determined the design of a space shuttle

Links:
Oleg's service for interviews: https://nextround.cc/

LinkedIn: https://www.linkedin.com/in/olegnovikov/

Join DataTalks.Club: https://datatalks.club/slack.html
1 hr 9 min
April 30, 2021Effective Communication with Business for Data Professionals - Lior Barak
We talked about:
DataTalks.Club intro

Lior’s background

Who is a data strategist?

Improving communication between business and tech

Building trust

Putting data and business people together

Dealing with pushbacks

Building things in the lean way (and growing tomatoes)

Starting with ugly code

Convincing others to take our code

MVP vs development and Hummus

Talking to people who can’t code

Break down the silos

Hummus

Hummus places in Berlin

Lior’s book: Data is Like a Plate of Hummus

Data chaos

Links:
Book: https://www.amazon.com/-/en/Sarah-Mayor/dp/B086L277LZ (can be found on any amazon store)

Company: https://www.taleaboutdata.com/

Podcast: https://podcast.whatthedatapodcast.com/

Linkedin: https://www.linkedin.com/in/liorbarak/

Twitter: https://twitter.com/liorb

Hummus places in Berlin:
Azzam: https://goo.gl/maps/uCkb3ATc5CVKapDa6

Akkawy: https://g.page/akkawy

The Eatery Berlin: https://g.page/theeateryberlin

Join DataTalks.Club: https://datatalks.club/slack.html
58 min
April 23, 2021Data Observability - Barr Moses
We covered:
Barr’s background

Market gaps in data reliability

Observability in engineering

Data downtime

Data quality problems and the five pillars of data observability

Example: job failing because of a schema change

Three pillars of observability (good pipelines and bad data)

Observability vs monitoring

Finding the root cause

Who is accountable for data quality? (the RACI framework)

Service level agreements

Inferring the SLAs from the historical data

Implementing data observability

Data downtime maturity curve

Monte carlo: data observability solution

Open source tools

Test-driven development for data

Is data observability cloud agnostic?

Centralizing data observability

Detecting downstream and upstream data usage

Getting bad data vs getting unusual data

Links:
Learn more about Monte Carlo: https://www.montecarlodata.com/

The Data Engineer's Guide to Root Cause Analysis: https://www.montecarlodata.com/the-data-engineers-guide-to-root-cause-analysis/

Why You Need to Set SLAs for Your Data Pipelines: https://www.montecarlodata.com/how-to-make-your-data-pipelines-more-reliable-with-slas/

Data Observability: The Next Frontier of Data Engineering: https://www.montecarlodata.com/data-observability-the-next-frontier-of-data-engineering/

To get in touch with Barr, ping her in the DataTalks.Club group or use [email protected]

Join DataTalks.Club: https://datatalks.club/slack.html
1 hr 2 min
April 16, 2021Shifting Career from Analytics to Data Science - Andrada Olteanu
We talked about:
Andrada’s background
Recommended courses

Kaggle and StackOverflow

Doing notebooks on Kaggle

Projects for learning data science

Finding a job and a mentor with Kaggle’s help

The process for looking for a job

Main difficulties of getting a job

Project portfolio and Kaggle

Helpful analytical skills for transitioning into data science

Becoming better at coding

Learning by imitating

Is doing masters helpful?

Getting into data science without a masters

Kaggle is not just about competitions

The last tip: use social media

Links:
https://www.kaggle.com/andradaolteanu

https://twitter.com/andradaolteanuu

https://www.linkedin.com/in/andrada-olteanu-3806a2132/

Join DataTalks.Club: https://datatalks.club/slack.html
1 hr 3 min