It’s all here each week in the OpenLampTech developer newsletter. I am sharing some fantastic curated content this week. Thank you for reading!(more…)
We don’t always need all rows from the table as part of the final results set. You can use one (or more) of the comparison operators to filter the rows with a WHERE clause conditional. In this post, we are looking at the equality comparison operator (=)…(more…)
Today’s post is a special one and a first-timer here on Digital Owl’s Prose. I am featuring a guest post by Edoardo Frasca.
Let’s meet Edoardo in his own words…
“Hey, I’m Edoardo!
I’m an Italian digital marketing enthusiast living in London.
My professional focus is on marketing, web analytics and data analysis.
After graduating at the School of Management and Economics in Turin (IT), I had to face what a lot of other graduates face: INEXPERIENCE when transitioning from university to work 🙂
That’s why I decided to share a few tips and tricks around highly requested tools like, in this case, Google Analytics.
- What is working well or not working at all on your website?
- Which category of products is gaining traction?
- Are the blog posts just published gaining interest?
I hope you’ll be able to answer some of those questions after reading this blog post, unlock the power of content grouping in Google Analytics!”
Now without any further delay, let’s enjoy Edoardo’s post, Advanced Content Grouping with Regular Expressions .
Thank you, Edoardo for guest-posting on my blog!
Saying time is important is to state the obvious. Our lives are built on time. We only have so much of it and once it is gone, there is no getting it back. While not as important as that time, date and time data values are integral pieces in most –if not all– database infrastructure and design. At some point or another, date and time values must be considered. PostgreSQL has many functions and options for date and time value manipulation. In this post, I look at the
INTERVAL type for date and time calculations….
At times, you may only need a certain portion of a date interval or
TIMESTAMP. Luckily in PostgreSQL, we have the
EXTRACT() function that allows you to grab just those particular bits of data. See how with a few simple examples in this post…