Is it possible to create simplified version of Tableau (Just basic visualization) using Google Chart Tools? If so, what are main challenges in imitating Tableau?
What are the advantages of Tableau over Google Chart Tools?
I would recommend reading a bit what Tableau and Google Chart actually does.
Google Chart is a library to create visualisations. Basically you need to have your data ready in the correct format and then with the API you can create and customiza a graph to publish on the web.
Tableau on the other hand gives you the possibility to directly connect to different data sources, blend and join these sources and then create dashboards that give you an overview of whatever data you would like to view.
So to answer your first question
Is it possible to create simplified version of Tableau (Just basic visualization) using Google Chart Tools?
Yes it is possible to create basic visualisation with Google Charts (that's what it's made for) but that's also possible with Excel (although that won't give you the interactivity online).
If so, what are main challenges in imitating Tableau?
You will not be able to join and blend data. You also won't have a fairly easy to understand user interface, since Google Charts is handled on code level. You will also not be able to just "play around" until you see something interesting, at least not as easily as in Tableau
What are the advantages of Tableau over Google Chart Tools?
that depends on your use case. If you want to get some pretty graphs on your website, Tableau won't be able to do the job and you shoudl use Google Charts.
If you want to have complex, interactive dashboards to examine your data from different sources, you will struggle getting all of that together just with Google Charts and you should probably have a look at Tableau.
Related
I need to automatically extract raw data of a PowerBI visualisation across multiple published reports.
Why not just pull the underlying dataset? Because the visualisations are using anomaly detection features of PowerBI, which include anomaly flags not available in the underlying dataset (basically, the visualisations contain calculated columns that are not included in main PowerBI data model)
Ideally a REST API solution would be best, but dumping CSV files or other more roundabout methods are ok.
So far, the closest functionality I can see is in the Javascript API here - https://learn.microsoft.com/en-us/javascript/api/overview/powerbi/export-data, which allows a website to communicate with an embedded PowerBI report and pass in and out information. But this doesn't seem to match my implementation needs.
I have also seen this https://learn.microsoft.com/en-us/azure/cognitive-services/anomaly-detector/tutorials/batch-anomaly-detection-powerbi which is to manually implement anomaly detection via Azure Services rather than the native PowerBI functionality, however this means abandoning the simplicity of the PowerBI anomaly function that is so attractive in the first place.
I have also seen this StackOverflow question here PowerBI Report Export in csv format via Rest API and it mentions using XMLA endpoints, however it doesn't seem like the client applications have the functionality to connect to visualisations - for example I tried DAX Studio and it doesn't seem to have any ability to query the data on a visualisation level.
I'm afraid all information on PowerBI says this is not possible. The API only supports PDF, PPTX and PNG options, and as such the integration with Power Automate doesn't do any better.
The StackOverflow question you link has some information on retrieving the Dataset but that's before the anomaly detection has processed the data.
I'm afraid your best bet is to, indeed, use the Azure service. I'd suggest ditching PowerBI and going to an ETL tool like DataFactory or even into the AzureML propositions Microsoft offers. You'll be more flexible than in PowerBI as well since you'll have the full power of Python/R notebooks at your disposal.
Sorry I can't give you a better answer.
I am creating a dashboard in Apache Superset. I want to create a funnel representation of my overall data. I didn't find any funnel charts. Is it possible to add user defined visualizations on superset. If yes, what is the method to do so. If no, what are its alternative (I am aware of bar charts)
I have followed this https://shopup.me/blog/beginners-guide-set-superset-opensource-bi-platform-ec2-aws-instance/ documentation to install superset on my machine.
you can definitely create your own custom visualizations (but I will warn you that adding custom viz plugins isn't a mature feature set yet). Here are some helpful links:
https://preset.io/blog/2020-07-02-hello-world/
https://medium.com/nmc-techblog/apache-superset-manage-custom-viz-plugins-in-production-9fde1a708e55
I will say that there are many ways to visualize funnels, which I talk about in this blog post: https://preset.io/blog/2020-07-14-funnels/
Our product requires support for a high level dashboard highlighting metrics pertaining to the business modeled by the product. Its a B2B product with a web application as a front-end.
We use Amazon RDS to store business data. What is the best approach to build a customizable dashboard in AWS?
The traditional approach would be to create metrics, process business data (analysis) and store the metrics/results in output tables. And then use a fancy charts library in the web application to build a support a panel/chart/graphic view per such metric. Support drill downs etc.
However, I believe this approach is outdated and too much work. Are there any readmade solutions available? Ideally, I should just be able to push results data to a third party solution, and the third party solution should allow for creation of custom dashboards (custom implies that the user can choose to select particular metrics/panels he would like to see in the dashboard, and their relative order& position in the dashboard) and embedding them in the products web application, to enable to end user to view as well as customize dashboards.
I'm aware of AWS quicksight, but it does not support embedding output views/dashboards into a web application.
I like Azure Power BI; At least you get to embed the dashboard in the web application, but I do not believe the end user can customize the embedded view. And ofcourse, Azure PowerBI is not on AWS ;).
Is there a mature 3rd party solution that we can evaluate? The scale of the data is very very small. So we are not looking for a high performance enterprise solution (might be too expensive anyway!). However, the need for customizability of dashboards view is high.
Embedded dashboards were added to QuickSight in November 2018, so you can now use that tool if you'd prefer.
https://docs.aws.amazon.com/quicksight/latest/user/embedded-dashboards-setup.html
Tableau is the first possibility, but it is expensive.
Infogram may also be an option: https://infogram.com/examples/dashboards
If you have small data volumes and you want cusomisation you may unfortunately have to look into writing or at least customising an existing solution.
I am working with my team to prep a project for a potential client. We've researched Amazon MWS API, and we're trying to develop an algorithm using the data scraped from this API.
Just want to make sure we understand the research correctly:
Is it possible to scrape data from Amazon.com like the plugins RevSeller or HowMany do? Then can we add that data to a database for use in an algorithm to determine whether or not an Amazon reseller should invest in reselling a product?
Thanks!
I am doing a similar project. I don't know the specifics of RevSeller or HowMany, but another very popular plugin is Amzpecty. If you use a tool like Fiddler, you can see the HTTP traffic and figure out what it does. They basically scrape out the ASIN and offer listing ID's on the current page you are looking at and one-by-one call the Amazon Product Advertising API, which is not the same thing as MWS. Out of that data returned, they produce a nice overlay that tells you all kinds of important stuff.
Instead of a browser plugin, I'm just writing an app that makes HTTP calls based on a list of ASIN's to the PA API and then I can run the results through my own algorithms. Hope that gives you a starting point.
What is the difference between the Power BI desktop client and web client. Both seem to have the same features. What can the desktop client do that the web client cannot do?
I'm not going to be exhaustive since there are a ton of features in both experiences. The Power BI Desktop is intended as a tool for Analysts to work with data. It includes data load, mashup, data modeling, and reporting capabilities. You can create models with relationships, calculated columns and DAX measures. You can create crazy transforms to manipulate the data to shape it into as good shape or merge data from multiple sources into a single data model. The web version of reports really focuses on the reporting piece. If someone else is doing all the data modeling for you, then the web reporting UI is pretty comprehensive. If you need to do the data modeling yourself, then Desktop is the way to go. Desktop does have the added benefit of a file you can save or archive. It doesn't support the direct query sources or push data sets like the web report feature. So there are at least some limitations. Which you use really depends on the types of problems you're trying to overcome.