GPEDM | Gaussian Process regression for Empirical Dynamic Modeling | Analytics library

Note that it's extremely unlikely that you will be satisfied with just the device information in any analysis, but in this answer, I will presume that you know your situation better than I.

Your options:

1. Sounds fine. Primitive, but sure.

2. Firebase/GA is large. You probably don't wanna complicate things with them. They demand very certain data structure in order to be able to give fullest insights. But later, when you want to get the data back, it's not that straightforward since those APIs are meant for pretty serious ETL process with exact understanding of all their internal definitions. It will be annoying if your aim is just to get a few metrics and a few dimensions and never anything more.

3. I never used Sheets APIs when the sheet is not opened. I always use its internal pseudo JS to move the data around. Well, it's up to you.

4. That's just a variation of 3.

Okay, now how I would do it.

You have (or supposed to have) access logs on the backend. If what you've described is all you need, I would suggest feeding the access logs as they are to G sheets and be done with it. That would be the sturdiest and most reliable implementation and if done correctly, it won't even depend on your backend language, but just on the web-server logging.

Well, if your setup typically bypasses the web-server (which is annoying really), then the framework you use for managing endpoints would likely have semblance of logging in it. I would use that then.

If not, I would try doing my tracking on the front-end, too, but you mentioned that that's not an option, so I'm not gonna entertain the thought any further.

Finally if those options aren't really options then you should think if you want to bother aggregating the data on the fly, in your script or not. And you're unlikely to want that because that would be extremely annoying.

To that point, unaggregated data will take a lot of space. G Sheets won't be able to handle that amount of raw data. For the same reason, using your local DB may be a bad idea too.

So it may be better for you to use GA API to stream the data through their measurement protocol (there are multiple libraries available for it). GA has an ability to feed its data to BQ, and from BQ it's much easier to get it to wherever. Well, I believe there already are multiple scripts and plugins for G sheets to get aggregated data from GA and make a semblance of semi-live dashboards in it.

This feature helps attribute app installs to certain adds through the apple identifier they call IDFA (identifier for advertisers). It's immensely useful to measure effectiveness of ads not only for downloads and installs, but also for latter internal conversions in the app.

But it won't be used if a user doesn't opt in to be tracked starting from iOS 14. So the value of it is somewhat diminished, making the analysts working with an effectively bias-sampled data that won't extrapolate normally.

Anyhow, if you need to do attribution, you'll need IDFA. Otherwise, you're perfectly fine using AnalyticsWithoutAdIdSupport.

The easiest way I found to check the cell limit was to try and add a huge amount of lines at the end of the document, which gave me this error message:

This reads: "An error has occurred: This action would increase the number of cells in the worksheet above the limit of 10000000 cells".

However, when I used one more digit, I got a different message:

That one reads: "Oops, enter a number between 1 and 5000000", suggesting the maximum number of rows you can have is 5 million, while the max of cells can be up to 10 million. I'm not sure about the columns, but I'd say it is the as the row's limit.

1. It's not about Plausible. It's about almost any front-end based analytics tracking system. Matomo, Adobe Analytics, Google Analytics: they're all critically vulnerable in this respect. Not mentioning the army of third party services that track conversions to optimize traffic segmentation.

2. However: 2.1 Nobody cares enough to bother spoiling others' data. Well, nobody enough for people to not concern themselves with it. It happens rarely. 2.2 It is pretty difficult to spoil the data in a reliable way. You'd have to study tracking pattern, get proxies, set up distributed event flooding, plausibly randomize every dimension that is organically set. It is difficult. 2.3 Even if you're good enough to spoil the data, good analysts and data scientists will be able to at least detect an attack if not clean the data from garbage. 2.4 An attack like this would cost more than setting up pretty good tracking. So from a business perspective, it's too expensive to spoil all your competitors' data.

3. Finally, yes, you can make it secure. But it's currently expensive. The idea here is to use a sort of server-side tag manager. Adobe Launch (now called Tags), Matomo, Tealium and GTM all offer server-side options. Not only does it offer an opportunity to hide your analytics endpoint, but also allows you to bypass adblockers that normally prevent anywhere from 5 to 75% of all tracking, depending on the audience.

Server-side, however, now requires the tracking implementation specialist to not only know bits of JS and DOM, but server side too, as well have as some API skills. And server-side TMSes don't allow you to execute generic code on the server, so now you have to be ready to write your own back-end code.

Obviously, you may ignore server-side TMS and use measurement protocol instead, directly sending events from your server endpoint to the tracking endpoint, bypassing a TMS. There's value TMSes provide, but server-side TMS just becomes a pretty and well-documented router.

Your tracking scheme now looks like so:

As Oleh Tarasenko suggested , if you need security events then they need to be enabled from Security Center.

Kindly note security events are collected from windows machines by Azure Security Center or Azure Sentinel. However, Azure Monitor agent does not support solutions and insights such as VM insights and Azure Security Center as of now. The only scenario currently supported is collecting data using the data collection rules that you configure.

• You can use AMA to natively collect Security Events, same as other Windows Events. These flow to the 'Event' table in your Log Analytics workspace.

• If you have Sentinel enabled on the workspace, the Security Events flow via AMA into the 'SecurityEvent' table instead (same as using Log Analytics Agent). This will always require the solution to be enabled first.

For your reference , availability of solutions for AMA.

Set up the Windows Security Events connector in Azure Sentinel

To collect your Windows security events in Azure Sentinel:

1. From the Azure Sentinel navigation menu, select Data connectors. From the list of connectors, click on Security Events, and then on the Open connector page button on the lower right. Then follow the on-screen instructions under the Instructions tab, as described through the rest of this section.

2. Verify that you have the appropriate permissions as described under the Prerequisites section on the connector page.

3. Download and install the Log Analytics agent (also known as the Microsoft Monitoring Agent or MMA) on the machines for which you want to stream security events into Azure Sentinel.For Azure Virtual Machines:

   1. Click on Install agent on Azure Windows Virtual Machine, and then on the link that appears below.
   2. For each virtual machine that you want to connect, click on its name in the list that appears on the right, and then click Connect.

   For non-Azure Windows machines (physical, virtual on-prem, or virtual in another cloud):

   1. Click on Install agent on non-Azure Windows Machine, and then on the link that appears below.

   2. Click on the appropriate download links that appear on the right, under Windows Computers.

   3. Using the downloaded executable file, install the agent on the Windows systems of your choice, and configure it using the Workspace ID and Keys that appear below the download links mentioned above.

   4. For additional installation options and further details, see the Log Analytics agent documentation.

   5. Select which event set (All, Common, or Minimal) you want to stream.

   6. Click Update.

   7. To use the relevant schema in Log Analytics for Windows security events, type SecurityEvent in the query window.

      Validate Connectivity

      It may take around 20 minutes until your logs start to appear in Log Analytics.

Full documentation : Connect Windows security event data to Azure Sentinel | Microsoft Docs

Azure Security Center and Azure Defender are now called Microsoft Defender for Cloud you can refer this documentation to enable security events to azure security center.

Try this:

No, you can't.

In the end, gatsby-plugin-google-analytics or any similar plugin what it's doing is to customize the html.js to add a script with the ID in it. This is created as a boilerplate/template for the content coming from your data sources (in your gatsby-node.js) while your site is being built, as you can see in the docs:

Gatsby gives plugins and site builders many APIs for building your site. Code in the file gatsby-node.js is run once in the process of building your site. You can use its APIs to create pages dynamically, add data into GraphQL, or respond to events during the build lifecycle.

Every Gatsby Node API gets passed a set of helper functions. These let you access several methods like reporting, or perform actions like creating new pages.

However, what you can do, is to set the tracking ID manually via React Helmet based on the content of your CMS, this would be simpler to achieve. In your createPage function you can do:

Follow below steps:-

1. Open Xcode and find GTMSessionFetcher folder
2. Select GTMSessionFetcher Class
3. Comment the GTMSessionFetcher Log Debug line.

Please Check the attached screenshot.