Sat 18 Jul 2020
Enduring favorite - Getting Data out of Notes (for whatever reason)
Thu 9 Jul 2020
Maximizing power while minimizing code and effort
Fri 29 May 2020
Round tripping, even while staying put
Delving deeper into your data - Intro
Fri 7 Jun 2019, 12:33 PMTweet
by Ben Langhinrichs
We live in a data driven world, and finding the useful data means searching.. Google (aka Alphabet) is a hugely valuable company because they figured out how to offer better searching on data. When HCL/IBM wanted to reignite interest in Notes/Domino, one of their highly publicized new features was DQL, because it offers faster and better searches on data.
Yet, there are some searches on Domino data that are painfully hard to do or painfully slow to execute, For that reason, I wanted to do a series on how the Midas engine allows better, deeper searches into your data, and how it can harness DQL or other techniques to get at that data quickly and efficiently. Also, how the results can be delivered as JSON or XML or other formats, depending on what you need.
But rather than starting with a demo, I'm going to pose a few questions which will be addressed in the following posts.
1) How would I find all the product images in our offerings database that do not have corporate's dictated 1.91:1 aspect ratio or that are under 450 pixels wide?
2) How would I find all doclinks in our three sales dbs that point to our product db? Or the ones that don't?
3) How would I see what bullet point items we've used in the ten highest earning proposals? In the ten lowest earning?
4) Given our accessibility rules, which graphics in our four public-facing dbs have heights greater than 1 pixel but no alt text?
5) Are there any unredacted credit card numbers appear in our discussion and job posting databases? How about only in certain views?
6) Are there any zero size attachments in our discussion databases? Any greater than 10MG in size? How about greater than 4MG in size from before 2017?
Each of these should be answerable without writing a lot of code, ideally using a data-driven approach, and the results should be available in JSON or XML.
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