I’m available for short-term assignments (half-day or one or two full-days), such as workshops, training, advising sessions,
or architecture reviews within the Data Engineering, Data Analytics and Business Intelligence domain. You can find below
examples of topics for presentations and workshops.
We can start with an informal chat for me get to know more about your current challenges and future plans regarding the data analytics domain, and we can discuss if and how I might be able to help.
⭐ Data journey 101
👨💼 Audience
When it is not clear what a data warehouse is, what Business Intelligence/reporting tools are and when you might want to start considering adopting them.
📖 Content
We go through the data analytics journey of a fictious e-commerce startup, starting from its inception, when the only developer exports data for reporting from the production database as CSVs, to more people joining and starting to have their own spreadsheets showing different numbers, to the introduction of a Business Intelligence tool and finally a data warehouse, combining a variety of internal and external data sources.
⭐ The data stack starter kit
👩💼 Audience
When the benefits of having a Business Intelligence function are already recognized, but it is not clear how to get started. Also useful for startups with an existing initial setup in place but open to compare and evaluate it with other existing options.
📖 Content
An overview of the modern startup data stack starter kit, with all the necessary tools to get started. We will talk about different solutions, their characteristics, trade-offs and costs and cover both commercial and open-source tools.
⭐ Technology deep dive
👨💼 Audience
When there's a clear understanding of the big picture and most likely a setup already in place.
📖 Content
Snowflake? dbt? Tableau? Choose one of the technologies that I have experience (you can look at my LinkedIn profile) and let’s do a deep dive on it.
⭐ Process deep dive
👩💼 Audience
When there's a clear understanding of the big picture and most likely a setup already in place.
📖 Content
Incremental or full extractions? Perhaps CDC or event sourcing? ETL or ELT? Visual data pipelines authoring tools, or pipelines as code? Transformations with analytics engineering? Choose one step in the ETL/ELT process and let’s discuss different approaches to it.
⭐ Open for suggestions
👨💼 Audience
Any (technical or non-technical).
📖 Content
How to use data analytics to understand your marketing costs and improve your campaigns? How to use simple models to classify your existing user base and find the most valuable users or the ones that are likely to churn? Reach out to discuss with me what kind of professional experience I might have that is of your interest.
Recent presentations
- 2021-02: Geospatial analytics | Snowflake Virtual User Group (Sweden)
- 2021-01: Data pipelines | Internal (Engineering) Lunch & Learn @ Voi
- 2020-10: Data roles | Internal (Engineering) Lunch & Learn @ Voi
- 2020-05: Database exports | Internal (Backend chapter) Lunch & Learn @ Voi
- 2020-04: Pivot tables, Part 2 | Internal (Company) Lunch & Learn @ Voi
- 2020-03: Pivot tables, Part 1 | Internal (Company) Lunch & Learn @ Voi
- 2020-03: Data warehouses | Internal (Backend chapter)) Lunch & Learn @ Voi
- 2020-02: Automated SQL DDL backups and meta dashboards | Breakfast with Data meetup
- 2019-10: Data & BI tools | Breakfast with Data meetup
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