SQL : PostgreSQL

  Aggregate Functions Like most other relational database products,  PostgreSQL  supports  aggregate functions . An aggregate function computes a single result from multiple input rows. For example, there are aggregates to compute the  count ,  sum ,  avg  (average),  max  (maximum) and  min  (minimum) over a set of rows. As an example, we can find the highest low-temperature reading anywhere with: SELECT max(temp_lo) FROM weather; max ----- 46 (1 row) If we wanted to know what city (or cities) that reading occurred in, we might try: SELECT city FROM weather WHERE temp_lo = max(temp_lo); WRONG but this will not work since the aggregate  max  cannot be used in the  WHERE  clause. (This restriction exists because the  WHERE  clause determines which rows will be included in the aggregate calculation; so obviously it has to be evaluated before aggregate functions are computed.) However, as is o...
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Step-by-step critique of a presentation

 https://coursera.org/share/e50a08979ec712d04a38003bb685398b

Step-by-step critique of a presentation

This reading provides an orientation of two upcoming videos:

  • Connor: Messy example of a data presentation

  • Connor: Good example of a data presentation

To get the most out of these videos, you should watch them together (back to back). In the first video, Connor introduces a presentation that is confusing and hard to follow. In the second video, he returns to talk about what can be done to improve it and help the audience better understand the data and conclusions being shared.

Messy data presentation

In the first video, watch and listen carefully for the specific reasons the “messy” presentation falls short. Here is a preview:

  • No story or logical flow

  • No titles

  • Too much text

  • Inconsistent format (no theme)

  • No recommendation or conclusion at the end

Messy presentation: people don’t know where to focus their attention 

The main problem with the messy presentation is the lack of a logical flow. Notice also how the data visualizations are hard to understand and appear without any introduction or explanation. The audience has no sense of what they are looking at and why.  When people in the audience have to figure out what the data means without any help, they can end up being lost, confused, and unclear about any actions they need to take. 

Good data presentation

In the second video, numerous best practices are applied to create a better presentation on the same topic. This “good” presentation is so much easier to understand than the messy one! Here is a preview:

  • Title and date the presentation was last updated

  • Flow or table of contents

  • Transition slides 

  • Visual introduction to the data (also used as a repeated theme)

  • Animated bullet points

  • Annotations on top of visuals

  • Logic and progression 

  • Limitations to the data (caveats) - what the data can’t tell you

Tip: As you watch this video, take notes about what Connor suggests to create a good presentation. You can keep these notes in your journal. When you create your own presentations, refer back to your notes. This will help you to develop your own thinking about the quality of presentations.

Good presentation: people are logically guided through the data

The good presentation logically guides the audience through the data – from the objectives at the beginning all the way to the conclusions at the end. Notice how the data visualizations are introduced using a common theme and are thoughtfully placed before each conclusion. A good presentation gives people in the audience the facts and data, helps them understand what the data means, and provides takeaways about how they can use their understanding to make a change or do some good.

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