Designing data intensive systems, M. Kleppmann
Ask HN: Good tech talks on how analytics systems are implemented?
11–20 of 87 posts
Re: Ask HN: Good tech talks on how analytics systems are implemented?
#12IMO, your requirements are too basic to need a serious system. Either log interaction to a file or a database, parse the output and query it with SQL to produce your basic metrics, or just write to Google Analytics. When this starts creaking at the seams it'll mean that you either have bigger analysis and/or scalability requirements and it'll much clearer what you need to look for.
Re: Ask HN: Good tech talks on how analytics systems are implemented?
#13IMO, your requirements are too basic to need a serious system. Either log interaction to a file or a database, parse the output and query it with SQL to produce your basic metrics, or just write to Google Analytics. When this starts creaking at the seams it'll mean that you either have bigger analysis and/or scalability requirements and it'll much clearer what you need to look for.
Re: Ask HN: Good tech talks on how analytics systems are implemented?
#14Go with off the shelf. You'll get something far better that you can build yourself, and if you need something custom, you'll have a much clearer idea what your analysis is missing. Writing to Google Analytics, Amplitude, Mixpanel (all of which have free tiers) or equivalent all should handle your case well.
Re: Ask HN: Good tech talks on how analytics systems are implemented?
#15IMO, your requirements are too basic to need a serious system. Either log interaction to a file or a database, parse the output and query it with SQL to produce your basic metrics, or just write to Google Analytics. When this starts creaking at the seams it'll mean that you either have bigger analysis and/or scalability requirements and it'll much clearer what you need to look for.
Piwik then perhaps
Re: Ask HN: Good tech talks on how analytics systems are implemented?
#16Note: I build and maintain such systems for a living. There's a lot of context that's missing from your post, some questions that can help us guide you in the right direction: 1) Can your website call out to external services, or are you limited to operating behind a company network? 2) Is this more of an ad-hoc analysis or do you want to invest in a framework to be able to track such metrics systematically over time…
1) The website cannot call to external services, which is the primary reason why we thought about implementing it from scratch. 2) We want to invest in building a good framework to track such metrics systematically over time 3) We have some non-web API clients too. Adblock is not a problem. 4) Accuracy is better. Speed is not that critical and could even be a few minutes delayed. 5) The data will be kept for a few mo…
You can use different technologies based on your use case, but you probably need all the pieces outlined above. As someone else has mentioned, if you're looking for trade-offs between different technologies, I'd recommend "Designing Data-Intensive Applications" by Kleppmann.
Re: Ask HN: Good tech talks on how analytics systems are implemented?
#17I was working for a startup implementing analytics tools. In my opinion, our setup was over-engineered, but I wasn't there at the beginning, so I might be wrong. Also, requirements changed a couple of times, so this could also explain why something that looked necessary for scaling and speed, ended up being this over-engineered mess. This is how it worked: After javascript tracker fired, we got log files, passed them…
I worked in a 15m/year revenue product for 3 years. Our Analytic system was screw by cookie messages and now GDPR. Marketeers wanted to serve Analytics through Google Tag Manager, which helped customers to block our analytics launcher, meaning 0 data for most of the visits.
Re: Ask HN: Good tech talks on how analytics systems are implemented?
#18Re: Ask HN: Good tech talks on how analytics systems are implemented?
#19Re: Ask HN: Good tech talks on how analytics systems are implemented?
#20I was working for a startup implementing analytics tools. In my opinion, our setup was over-engineered, but I wasn't there at the beginning, so I might be wrong. Also, requirements changed a couple of times, so this could also explain why something that looked necessary for scaling and speed, ended up being this over-engineered mess. This is how it worked: After javascript tracker fired, we got log files, passed them…
The analytics are not just limited to web clients. There would be API clients too. The deployment will be in a private enteprise vpn and so talking to external services may not be an option. I am aware of these tools like cassandra/flink/spark/kafka etc. But I am more curios about the best tools and architectural patterns that work well with each other.
Well you can go with:
Fancy: Hdfs(distributed file system) as storage - oozie as workflow scheduler for your load(python/hive/scala/spark) - Tableau for visualization (your business ussers will love it.
Mid range: SQL Server as storage - Informatica for your workload - power BI /SSRS for visuals
Open/low budget: PostgreSQL / Cassandra for storage - make your own scheduler/ there is a post for ETL open score yesterday that might help - for visuals you can make it from scratch but hire a good designer!
This is based on my experience on industries like Gambling, Banking and Telecom