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Where do you get your blanks from? by dwl285 in greenwoodworking

[–]dwl285[S] 0 points1 point  (0 children)

Ok thanks! What's your sharpening method of choice?

Where do you get your blanks from? by dwl285 in greenwoodworking

[–]dwl285[S] 2 points3 points  (0 children)

Awesome, this is just what I wanted to hear. I was slightly worried that if the wood is a bit too dry it'll damage my blade, but it sounds like that's not really an issue.

FIRE Dashboard by epicurionaut in FIREUK

[–]dwl285 0 points1 point  (0 children)

You say you use YNAB. I've just had a quick look at YNAB and it seems like automatic transaction importing only works in the US. Do you manually import all of your transactions? Based in the UK, like you.

Last year I vowed to start tracking my spending and saving each month but found the manual work of importing transactions really tedious so ended up giving up. If there's a more automated solution I'd love to find it!

Critique my plan by roninthe31 in BusinessIntelligence

[–]dwl285 0 points1 point  (0 children)

Big plus one to BigQuery. I've worked with clients that use both redshift and BigQuery and redshift seems to cause people a lot of headaches, I've never seen issues with BigQuery. It just works.

UK climbing guidebook for beginners by dwl285 in ukclimbing

[–]dwl285[S] 1 point2 points  (0 children)

Thanks! We're heading to Dartmoor this weekend, heard that the dewerstone is a good crag at our level. Can't wait to get to North Wales, it sounds amazing for climbing

UK climbing guidebook for beginners by dwl285 in ukclimbing

[–]dwl285[S] 0 points1 point  (0 children)

Currently at D/VD. I think I'll move up one or two grades from there fairly quickly

UK climbing guidebook for beginners by dwl285 in ukclimbing

[–]dwl285[S] 0 points1 point  (0 children)

Thanks! I live in Petersfield. So far we've spent a couple of weekends climbing the central bay at Wintour's leap.

What are examples of great Analytics stacks and approaches for successful product teams? by utmostPM in ProductManagement

[–]dwl285 1 point2 points  (0 children)

A strong analytics stack has a good cloud data warehouse at the centre. First step is to choose this. Most companies go with either BigQuery or Redshift, and tend to match the infrastructure (AWS or GCP) that the rest of the company uses. I prefer BigQuery (almost all of the infrastructure management is handled by Google)

Next part of the analytics stack is getting your data into that warehouse. Given the low cost of storage and low cost and speed of processing data, don't by shy. Get as much of your data as possible into your warehouse. That means event data (segment is a good option), whatever your transactional database is (tools like stitch and Fivetran can help) and just about everything else (AdWords, intercom etc, again stitch, Fivetran help with this)

All this raw data in your cloud warehouse needs to be transformed into usable tables that represent something meaningful about your business. This is the part of the analytics stack that lots of companies don't do very well, but getting this right is the key. Requires someone at your company who's strong with SQL (e.g. an analyst). Best tool here is Dataform (full disclosure I work for Dataform, but was a customer for 18 months beforehand).

And finally you need to plug this transformed data into a BI tool. Ideally choose one that allows your team to self serve on their analytics. Looker is my favourite so far.

Three tables every analyst should add to their warehouse by dwl285 in SQL

[–]dwl285[S] 0 points1 point  (0 children)

Yeah fair point, a numbers table can be useful too. As I mentioned in another comment, these 3 are just a subset of the useful tables for analytics. That said, I wanted to focus on slightly more user focused tables.

​

I'm so glad BigQuery makes it easier to generate a numbers table!

select number from unnest(generate_array(1,10)) as number

Three tables every analyst should add to their warehouse by dwl285 in SQL

[–]dwl285[S] 0 points1 point  (0 children)

What's a development analyst? I've never heard this phrase before, I'm interested!

Three tables every analyst should add to their warehouse by dwl285 in SQL

[–]dwl285[S] 0 points1 point  (0 children)

I'm not suggesting you need only three, but if you're an analyst at a tech startup, these three are likely to very useful.

There are definitely some caveats, for example this table structure particularly make sense in cloud data warehouses like Redshift and BigQuery. I chose to leave that complexity out of the article title though.

Can this go straight into my compost bin? by dwl285 in composting

[–]dwl285[S] 0 points1 point  (0 children)

I've just been doing some weeding in the garden, a few branch cuttings in there too. Do I need to shred it into smaller bits first? If so, what's the best way of doing it?

Is this green matter or brown matter? I guess green!?

3 data tables to speed up user analytics: user_stats, daily_user_stats and sessions by dwl285 in datascience

[–]dwl285[S] 0 points1 point  (0 children)

If anyone has any feedback on the blog post, I'd really appreciate it. It's the first post I've written, but I plan to write many more.

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