31 Matching Annotations
  1. Jul 2021
  2. May 2021
    1. Dr Nisreen Alwan 🌻. (2020, March 14). Our letter in the Times. ‘We request that the government urgently and openly share the scientific evidence, data and modelling it is using to inform its decision on the #Covid_19 public health interventions’ @richardhorton1 @miriamorcutt @devisridhar @drannewilson @PWGTennant https://t.co/YZamKCheXH [Tweet]. @Dr2NisreenAlwan. https://twitter.com/Dr2NisreenAlwan/status/1238726765469749248

  3. Mar 2021
  4. Nov 2020
    1. We love dbt because of the values it embodies. Individual transformations are SQL SELECT statements, without side effects. Transformations are explicitly connected into a graph. And support for testing is first-class. dbt is hugely enabling for an important class of users, adapting software engineering principles to a slightly different domain with great ergonomics. For users who already speak SQL, dbt’s tooling is unparalleled.

      when using [[dbt]] the [[transformations]] are [[SQL statements]] - already something that our team knows

    1. The attribution data modelIn reality, it’s impossible to know exactly why someone converted to being a customer. The best thing that we can do as analysts, is provide a pretty good guess. In order to do that, we’re going to use an approach called positional attribution. This means, essentially, that we’re going to weight the importance of various touches (customer interactions with a brand) based on their position (the order they occur in within the customer’s lifetime).To do this, we’re going to build a table that represents every “touch” that someone had before becoming a customer, and the channel that led to that touch.

      One of the goals of an [[attribution data model]] is to understand why someone [[converted]] to being a customer. This is impossible to do accurately, but this is where analysis comes in.

      There are some [[approaches to attribution]], one of those is [[positional attribution]]

      [[positional attribution]] is that we are weighting the importance of touch points - or customer interactions, based on their position within the customer lifetime.

  5. Oct 2020
  6. Aug 2020
  7. Jul 2020
  8. May 2020
  9. Apr 2020
  10. Feb 2020
  11. Jan 2020
    1. The Web Annotation Data Model specification describes a structured model and format to enable annotations to be shared and reused across different hardware and software platforms.

      The publication of this web standard changed everything. I look forward to true testing of interoperable open annotation. The publication of the standard nearly three years ago was a game changer, but the game is still in progress. The future potential is unlimited!

  12. Nov 2019
  13. Sep 2019
    1. On the other hand, a resource may be generic in that as a concept it is well specified but not so specifically specified that it can only be represented by a single bit stream. In this case, other URIs may exist which identify a resource more specifically. These other URIs identify resources too, and there is a relationship of genericity between the generic and the relatively specific resource.

      I was not aware of this page when the Web Annotations WG was working through its specifications. The word "Specific Resource" used in the Web Annotations Data Model Specification always seemed adequate, but now I see that it was actually quite a good fit.

  14. Apr 2019
  15. Sep 2016
    1. The importance of models may need to be underscored in this age of “big data” and “data mining”. Data, no matter how big, can only tell you what happened in the past. Unless you’re a historian, you actually care about the future — what will happen, what could happen, what would happen if you did this or that. Exploring these questions will always require models. Let’s get over “big data” — it’s time for “big modeling”.
  16. Feb 2015