We are [almost] DB-agnostic (as long as there is SQL interface and JOINs are supported) and have been adding support for particular DBs based on the interest from our users. SQL Server & Azure SQL areon the roadmap, please let us know if you have a use case in mind to pilot Datafold on them.
Optimizing marketing spend - you can show how a ML model will beat a conventional past performance regression algorithm by increasing sales, reducing cost, etc.
Learning Prolog was one of the better decisions I have made. Not because Prolog jobs are plentiful. Rather, understanding logic programming by broadened my problem-solving skill set.
I worked in ecommerce for 10 years and got to know the quantitative marketing folks well. All marketing campaigns were tracked and analyzed weekly based on the concept of "marketing income". Marketing income at the order level was defined as: Marketing Income$ = Order Total$ - Cost of Goods$ - Shipping$ - Marketing Expense$.
Good data-driven marketing teams work hard to establish control groups and known baselines before starting high-spend campaigns, and the ROI of those can be quantified by referrer info if they're highly specific and keyword-related.
As for more general campaigns, in my experience, it's a crapshoot, if the numbers go up everyone is happy whether or not marketing was responsible for the majority of it. I'm sure other companies have better approaches than that though.
Good question! Combination of holdout groups (split testing) based on historical keyword traffic/conversion and tagging paid and natural search entries to compare cannibalization across campaigns.
I would imagine many folks who are visiting cancer/ALS content are impacted by the diseases either directly or indirectly. Affiliate marketing (directed to non-profits) seems like a place to start.
Much like mathematics, programming is learned through action. As a fairly cautious individual, I wanted to understand everything I was about to type as input for the compiler. I would recommend the opposite approach: Copy code examples line by line, and start modifying them with simple changes such as variable names, output strings, etc.
