I am new to databases, and have some data stored as entities in Google Cloud Datastore. I would like to be able to analyze and plot this data in a web interface, and it seems like Google Data Studio provides an easy-to-use way to do this. However, I'm a bit confused as to how I can actually use the two interfaces together; it seems like either Google Cloud Storage or Google BigQuery could be a middleman in between, but I'm not sure how this might work. Could anyone advise on whether using Google Data Studio would be the best approach to plotting/analyzing data in Google Cloud Datastore, and if so, offer tips on how I could go about this? There are a large number of tutorials but it seems like none that I've found have explained how to load data from the Datastore into a useable file for Data Studio.
Thanks!
As Graham Polley says, the question is answered here. The workaround to connect Cloud Datastore to Google Data Studio is to first export Datastore entities to BigQuery, as explained in this guide.
Then see this in order to connect Data Studio to BigQuery tables.
Finally in this blog post, there's a tutorial for building a dashboard with Google Data Studio and BigQuery.
Related
I have a Firebase application which is uploading events with parameters. I need to be able to view those events in order to debug some issues we're having in production. I can only see the tables which are generated nightly in BigQuery. I can find references online saying that BigQuery allows viewing real time data. What I can't find is any straightforward instructions on how to create those views.
Is it possible? If so, can someone give me instructions that even a complete newb could follow?
We have decided to use the BigQuery APIs for information we want to see immediately in the database.
Can anyone please help me understand what components/services does Azure Synapse Analytics include?
From what I have read from both Microsoft website and other reviews, it says it is the new SQL Data Warehouse, however, it also says it brings together all these : data ingestion (like azure data factory), data warehouse, and big data analytics (like data lake)?
So what components exactly does a Azure Synapse Analytics include when you purchase it?
Thanks.
Azure Synapse Analytics service currently (as of 6th May 2020) refers to Azure SQL Data Warehouse, more specifically to "gen2" version of it. Microsoft released in November 2019 in Ignite'19 event the new name "Azure Synapse Analytics" and upcoming features for the service. The new features are currently available only in private preview, but I would assume they will be released in public preview soon. Access to new users to private preview is already closed, even though some Microsoft material still hints that you could apply to it.
You can already find information about the new features in documentation and other materil. The confusing part is that you cannot find them in portal yet if you are not part of the private preview. This makes it really hard for new users currently understand what really is available and what is not.
Good start to information on situation and features of both versions this can be found here:
Blog post Azure SQL Data Warehouse is now Azure Synapse Analytics
SQL DW documentation
Synapse new features documentation
Microsoft has made the release of this update very confusing. I assume they wanted to communicate early in Ignite'19 that they will have a competitive offering coming. Compared to some other cloud native data warehousing solutions the old version of Azure DW clearly were behind in many areas, e.g. in flexible scalability. The new Synapse Analytics capabilities look good and can bring Microsoft back to lead in this area.
I'm quite new to NativeScript so I'm after some advice.
I've been looking at different back-end database solutions for the data. I've looked at firebase and while it does what it says on the tin I've come from am SQL relationship database background historically.
I've had a look and see that kinvey can connect to azure database (haven't tested this as yet)
I've looked at the azure database plugin but at present that doesn't support offline data.
Just wondering what other people have tried and recommend/stay away from.
Your use plugin nativescript-sqlite.
Not great at programming so not all that confident of being able to pull data from the Google API.
Basically what I'm trying to do is pull everything from Google Analytics, all data and dump it into a table on a SQL Server (2008 R2). What would be the best way of achieving this?
Would like to automate the process so that it could be scheduled say once a month.
Cheers
There an existing add-on specifically for accessing Google Analytics.
Haven't used it but from what I read seems like it will exactly what you are looking for
http://www.google.com/analytics/apps/about?app_id=1325007
There is a specific SSIS DataSource Component for that – https://analyticssource.codeplex.com
It is open source and free.
I need to merge my GA statistics with external data (stored in SQL but I can expose them by some web service). Perfectly all the data should be available in GA for reporting but I found no solution for import the data into GA.
Do you know any piece of software that can do this and present the merged results in some readable form to the user? It should meet the following requirements:
Should be a web application
Should not be a software-as-a-service solution (will be hosted in infrastructure provided by me)
Should provide some level of automation in data import
Analytics Canvas looks interesting but I wonder if there are any other applications.
Analytics Canvas is indeed a good option, it has really good data extraction and transformation capabilities, and handles nicely any data out of both SQL data sources and the most recent GA API.
Google Analytics allows you import data through the API and manually through the Web Interface. For example this is a very good article on integrating external CRM user data with Google Analytics. But Google analytics also support importing the following types of data:
Product Data
Refund Data
Cost Data
Content Data
User Data
You can also create your own custom dimensions and metrics and import that data into Google Analytics and view the results in your own custom reports.