Google Universal Analytics (discontinued) vs. MongoDB

As I have discussed previously their insights were very useful. The second thing is since it is a Google product you will connect the data very easily from other platforms like Bigquery, Google Drive, etc. and even you can connect Google marketing platform. through this tool, you can track your live campaign how they were performing, and how it will be engaging your customer as well.

If asked by a colleague I would highly recommend MongoDB. MongoDB provides incredible flexibility and is quick and easy to set up. It also provides extensive documentation which is very useful for someone new to the tool. Though I've used it for years and still referenced the docs often. From my experience and the use cases I've worked on, I'd suggest using it anywhere that needs a fast, efficient storage space for non-relational data. If a relational database is needed then another tool would be more apt.

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• It is an excellent cloud analytics platform that is easy to install and configure and easy to deploy and use, allowing us to measure web traffic and other tools.
• It is an entirely online tool; it does not take up hard disk space like other desktop tools.
• Since this tool is draggable, Google is constantly adding more features.
• Even beginners who do not have a custom dashboard can get information. If there is a problem somewhere on the site that needs to be investigated, Google Analytics 360 will notify you.

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• Being a JSON language optimizes the response time of a query, you can directly build a query logic from the same service
• You can install a local, database-based environment rather than the non-relational real-time bases such a firebase does not allow, the local environment is paramount since you can work without relying on the internet.
• Forming collections in Mango is relatively simple, you do not need to know of query to work with it, since it has a simple graphic environment that allows you to manage databases for those who are not experts in console management.

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• Generally I think there is a lot you can do within the tool, but as it is a Google product it means there is limited support - something which I think lets all of the platform stacks down
• There could be more visual signifiers to identify if a feature is a normal or 360 feature. This would mean you can really get to grips with what the extra more advanced elements are

• An aggregate pipeline can be a bit overwhelming as a newcomer.
• There's still no real concept of joins with references/foreign keys, although the aggregate framework has a feature that is close.
• Database management/dev ops can still be time-consuming if rolling your own deployments. (Thankfully there are plenty of providers like Compose or even MongoDB's own Atlas that helps take care of the nitty-gritty.

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Google Analytics 360 is an upgraded version of the most widely used web/app analytics tracking tools in the market. The price is stable and predictable making it a long-term product of choice. It's easy to use and pairs so well with other Google Marketing Platform products.

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I am looking forward to increasing our SaaS subscriptions such that I get to experience global replica sets, working in reads from secondaries, and what not. Can't wait to be able to exploit some of the power that the "Big Boys" use MongoDB for.

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The UI is very easy to navigate and use. The features are well designed and intuitive. As long as the user has a good understanding of basic digital analytics definitions and capabilities, this tool should be quite easy to use. I consider Google Analytics Premium to be the easiest of all of the enterprise solutions out there to use.

NoSQL database systems such as MongoDB lack graphical interfaces by default and therefore to improve usability it is necessary to install third-party applications to see more visually the schemas and stored documents. In addition, these tools also allow us to visualize the commands to be executed for each operation.

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If you purchase Premium through a reseller like LunaMetrics, you are going to be taken care of. The additional amount of support and services that a reseller provides to make sure you have the best experience with the product is the reason why the reseller program exists to begin with. Support doesn't have to be just reactive, it can be proactive as well.

Finding support from local companies can be difficult. There were times when the local company could not find a solution and we reached a solution by getting support globally. If a good local company is found, it will overcome all your problems with its global support.

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There is a ton of information online about Google Analytics, but Google Analytics Premium users will have dedicated support and training from Google or an Authorized Reseller.

If you already have the basic version of GA installed, "getting" GA Premium happens immediately through a virtual flipping of the switch - no need to re-implement. You'll want to expand your use of custom dimensions and metrics (you get 10x the amount with Premium). Ideally, you'll be using a tag management solution to talk with GA Premium, in concert with implementing a dataLayer (to note, Google's Tag Manager platform is covered under the same GA Premium SLA, and it's free). There are some welcomed "configurations" with GA Premium, such as integrating with DoubleClick products, activating data driven attribution models, and building roll-up executive reports - but all of these are easy point and click solutions. In comparison with any other enterprise analytics solution, implementing GA and GA Premium is traditionally easier and more flexible. And if you have any trouble or need an extra set of hands for implementation, GA Certified Partners like LunaMetrics can help

While the setup and configuration of MongoDB is pretty straight forward, having a vendor that performs automatic backups and scales the cluster automatically is very convenient. If you do not have a system administrator or DBA familiar with MongoDB on hand, it's a very good idea to use a 3rd party vendor that specializes in MongoDB hosting. The value is very well worth it over hosting it yourself since the cost is often reasonable among providers.

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Unless you have very complex and edge case analytics needs, Google Analytics [360 (formerly Google Analytics Premium)] is likely going to be the best choice. From both a cost and usability stand point, Google wins. Adobe has the edge case when you need to create really custom reports, dimensions, metrics, etc. In my experience, this is rarely the case and you end up biting off more than you can chew. Stick with Google unless you are or plan on hiring an Adobe Analytics expert.

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We have [measured] the speed in reading/write operations in high load and finally select the winner = MongoDBWe have [not] too much data but in case there will be 10 [times] more we need Cassandra. Cassandra's storage engine provides constant-time writes no matter how big your data set grows. For analytics, MongoDB provides a custom map/reduce implementation; Cassandra provides native Hadoop support.

• It helps me understand which social media platforms are most successful for me - which I should focus on and which I might want to focus less on.
• I can also see which blog posts people are reading - so I know which topics resonate most. I can write more of those, hopefully gaining more visitors.

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• Open Source w/ reasonable support costs have a direct, positive impact on the ROI (we moved away from large, monolithic, locked in licensing models)
• You do have to balance the necessary level of HA & DR with the number of servers required to scale up and scale out. Servers cost money - so DR & HR doesn't come for free (even though it's built into the architecture of MongoDB