The Coalesce 2020 conference, which I’ve mentioned before, took place from 7 till 11 of December 2020. This year, the organizers decided to carry out the conference in 5 days with a bunch of talks.

On the one hand, it’s an advantage as due to the abundance of information you have a sense of choosing what’s more interesting to watch. On the other side, such an amount of information is tiring as often it’s impossible to tell if the presentation will be interesting and useful just based on its name. In my opinion, it’s too much to have more than 3 days for a conference as the audience loses interest. Moreover, the need to deal with personal and professional issues cannot disappear because of the event that although online takes your time.

However, I managed to watch most of the talk, sometimes skimming through. First of all, my overall impression, it is great to study the presentations from conferences like Coalesce as they mostly cover modern BI tools and cloud solutions. Almost every talk mentions Redshift / BigQuery / Snowflake or BI tools like Mode / Tableau / Looker / Metabase. Obviously, dbt is in the middle of everything.

The shortlist of talks that I recommend for studying:

1. dbt 101 — an introductory talk on what dbt is and how to use it.
2. Kimball in the context of the modern data warehouse: what’s worth keeping, and what’s not 
   — an interesting but extremely controversial video that raised a lot of questions in dbt. In short, the author suggests using wide analytical tables and giving up normal forms everywhere.
3. Building a robust data pipeline with dbt, Airflow, and Great Expectations — a talk about a rather interesting tool called greatexpectations which is used for data validation.
4. Orchestrating dbt with Dagster — a video seemed a bit boring for me, but if you want to learn about Dagster, you’ll like it.
5. Supercharging your data team — the guys created a wrapper for dbt called dbt executor 9000 and presented it.
6. Presenting: SQLFluff — a video about a really cool feature called SQLFluff that automatically edits SQL code according to the SQL rules.
7. QQuickstart your analytics with Fivetran dbt packages — from this video, you’ll learn about Fivetran and find out how to use it with dbt.
8. Perfect complements: Using dbt with Looker for effective data governance —
   about the interaction of dbt with Looker, differences and similarities of the tools.

The Future Data Conference, which I happened to participate in, took place on September 8-9. And in today’s post, I’d like to share my observations about thoughts about presented ideas. Before we get started, I apologize for the poor quality of some images, I tried to make the most meaningful screens straight from the video.

Featured Keynote: Automating Analysis
Speaker: Pat Hanrahan
The report was presented by the Stanford Professor and Tableau Co-Founder and mostly touched the use of AI and analytics. Pat discussed where we are now, today’s AI use cases, although the report alone was kind of repetitive, the Q&A part turned out to be interesting.

The Modern Data Stack: Past, Present, and Future
Speaker: Tristan Handy
The main builder of dbt and author of the well-known post serving as a guide to data analytics for startup founders, spoke about changes in modern data-stack from 2012 to 2020. Personally, I think it was one of the best conference reports since Tristan made predictions about growing tendencies and the future of data-stack.

Making Enterprise Data Timelier and More Reliable with Lakehouse Technology
Speaker: Matei Zaharia
This report belongs to the CTO of DataBricks. Unfortunately, the audio part had sound issues, but Matei considered the problems of modern Data Lake, promoting a new technology of DataBricks – DeltaLake. The report was more promotional but still interesting to listen to.

How to Close the Analytic Divide
Speaker: Alan Jacobson
The Chief Data Officer of Alteryx went on about the Data Scientist job and wages statistics, citing that the average salary of a data scientist is significantly higher than others in this field. By the way, our recent research with Roman Bunin also confirms this. Alan discussed the revenue of companies at different stages of analytical growth. Companies with more advanced analytical approaches grow faster (surprising fact). A separate part was focused on changes in modern approaches to working with data. Overall, it’s a great report that was easy to listen to.

Hot Analytics — Handle with Care
Speaker: Gian Merlino
The Co-Founder and CTO of Impy compared hot & cold data (a clue to
Snowflake?). Then he demonstrated some BI tool with drag-n-drop in a simple interface. Gian went on talking about possible analytic architectures and overviewed some features of Apache Druid.

Yesterday I had a chance to address the largest marketing conference in Kazakhstan: Kazakhstan Marketing Conference 2020.

Almaty, as a city, has made a positive impression on me, whereas the conference itself turned out to be highly professional event, filled with plenty of smart, versatile and kind people.

A pleasant bonus for conference participants: presentation of my speech available on slideshare (careful, VPN!), so one can recall what it was about.

Apart from the speech, in the main forum’s section I was holding a masterclass on “How to construct a comprehensible technical specification on analytics?”.
And, within the framework of work with the audience, we managed to formulate points for a template of a technical specification.

Sharing the template, it will be helpful for those, who faced with difficulties in translating of a task from business language to the technical one.