My most recent discovery – and to judge from the naming conventions of the users you’re assigned when using it, I’m relatively early to the trend — is PlatformDemos.com
They have lots of different fancy, often expensive licenses to choose from, and you can spin up a scratch org of even apply it to an existing org. Searching for Data Mask options brings me here.
And I chose to spin up a new demo org, which does this:
And using the link at top, voila! A new org with all kinds of fancy licenses.
Navigating to the Data Mask App, Masks Tab
And clicking through to the Sample that PlatformDemos.com configured for me,
The sample only masks Contacts. Clicking through to configuring Contact, takes us here
This Salesforce Help Link explains what options are available for the mask. After we review and understand what’s going to happen, we run the mask, which takes some time. Over about 30 minutes, a number of Apex Jobs are run.
And if that seems overwhelming, the Run Logs tab and Object make it a bit easier to understand.
Some anodyne case comments I had made on this case have been scrambled beyond intelligibility, not least because of the truncation involved.
And what seemed a little abstract on Trailhead
Which the fine print here makes clear requires permission sets that are paid for is now much more concrete.
And look at all these other nifty apps with licenses to play with over the next 4 days!
I’m trialing some telephony options for a client on G-Suite. CloudCaller.io and DialPad, in addition to the possibility of a Twilio custom job. I’ll be reporting back more on these soon.
But I have to say, DialPad has impressive capabilities. The transcription is pretty accurate – and more impressively, it identifies interesting questions between the caller/agent and the call recipient.
Dialpad Analytics
This was with a girlfriend of mine from college, so it was unusually long, and not commercially focused. But it’s a little creepy to think about how much of our conversation The Machines are listening to. They’re certainly getting familiar with how we speak in practice if not our inner souls.
More on #DialPad, CloudCaller and integrating both of these with Salesforce coming soon.
Today was one of those “whoa”: this stuff is impressive, powerful and the tiniest bit scary. (Not that I haven’t, to paraphrase Kubrick, learned to stop worrying and simply love the cloud).
Signed up for Xendo via Yammer, and then proceeded to add all the usual suspects of my cloud services: Salesforce, Twitter, Gmail, LinkedIn, Office 365, Evernote, Trello — hey, to learn things sometimes you have to have redundancies (even if you have to pay for the privilege).
Let it whir and churn for a while as it builds primary indexes for the first time. But before long, you’ve got an “internal” search engine of quite some (staggering) power. I searched upon my former colleague/treasurer of Columbia Business School Alumni of MetroDC, Dana Scherer, a Virginia resident who works for the Federal Government.
The result set was impressive — her contact information in my multiple synchronized systems; her attendance at events as recorded in Salesforce, along with her ticketed purchases from the club. Google drive stored versions of contact clean up exports that I, mental pack-rat that I am, simply save. A reference to her in a backup of a WordPress database (evidently unencrypted). It goes on and on — just as this image does here.In fact, what you’re seeing and about to scroll through is truncated, because no browser based screenshot tool that I know of will capture a sample as tall as this is.
(To give a slight preview, here is the search results dashboard detailing source, record type and chronological allocation of the search results. Nifty, eh?) But that’s where that slight tinge of fear comes from. If, courtesy of Xendo I can aggregate information like that — just imagine what people who truly know their way around systems can do. The Snowden halo is hard to ignore. Still, for lil’ole me: it’s simply fun — oh and useful.
A Preview of the Results with Descriptive Stats & Chronological Allocation
So: get ready to tire your thumbs as you scroll through the (extremely) truncated search results.
I discovered today in the chrome webstore a nifty little business intelligence offering from Zoho.
Zoho Reports
So I uploaded some exports from Salesforce. First we’ll take a look at the login activity data, which begins to point towards how one audits things in the multidimensional space that is a database in the cloud, towards which lots of web services are making calls.
Salesforce Login Log Export – in Zoho Report (Table)
The summary function reporting of Zoho’s BI Tool is just like a SQL/MS Access GroupOn[Value] query. It enables us to take this table of 1,691 rows and look at the clustering of values. To tmake this interesting, I choose to Group On (and thereby collapse around) the LoginType field. And count the records to produce the following distribution histogram:
Distribution Histogram of Login Type: Humans aren’t even close!
Absolute Automation is the name of an app by IHance, and it’s an email matching app that takes all email to my address and tries to find a Salesforce record to attach them to — it makes for a very thorough approach to CRM, which is rather exactly what we’d expect from Salesforce.com
Cirrus Insight is an app that syncs Google Apps contact data with Salesforce — and enables creating new accounts & contacts & leads from within the Gmail interface.. Those 175 entries via the browser — that’s me as the admin: a living, breathing mortal who is a mere piker in comparison to the hard working apps Such is the beauty and power of Cloud computing
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Record Type Agreement between Salesforce.ACCOUNT object and Salesforce.CONTACT.
SF.CONTACT fields are shaed in Gray; SF.ACCOUNT fields are in Blue; Dark blue is redaction of Alumni personal data
Record type agreement — after all my bellyaching about the importance of a record type schema that can handle the complexity of the milieu in which an Ivy League Alum Club operates. Record type agreement is one way to track if one’s practice lives up to one’s theory. Furthermore, this little exercise is providng an awfully convenient excuse to dig deeper in Zoho Reports. Pretty nifty the way it’s just a few short clicks until you can make some interesting discoveries.
The image below shows a portion of the 1700 plus rows in the table. The grey shaded portion are SF.CONTACT object fields; the light blue are SF.ACCOUNT object fields. And the dark blue are redaction on my part to safeguard my alumni data.
When I was enthusing earlier about dataloader.io, this is why: if you don’t pull over related records’ actual fields, to look at a Salesforce export — well for a human, it’s often not an easy read: long strings of digits in which upper v. lowercase actually counts!
One nice diagnostic test to run is to compare counts of Salesforce CONTACT records, by record type, against the number of organizational ACCOUNT records, by record type. The logic of the nature of the relatioships that are to be expected helps one to ascertain how well the coding schema is working. So, again, using GroupOn ACCOUNT.Organization Record type: what inferences can we make about the SF.CONTACT records by type?
Take a look at the entires in the report and, as Linda Richmond would say: “discuss amongst yourselves.”
I’ll use non-Linda-Richmond diction by noting that I’ll return to this anon.
red needs further investigation green is exactly or almost exactly as one would expect yellow is pretty good oh, provided you’re using a non-free account, it’s basically one-click publishing of your data. Take that, SharePoint 2013!
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