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You can easiliy create a report following this step :
To start exporting your data to Google Sheets, you need to install the Catchr add-on. You currently have two options :
Option A: Via the marketplace:
Option B: Directly within a Google Sheets:
Once you have installed the add-on, you can start making requests.
Business Intelligence (BI) and data visualization tools are key in unifying and visualizing data normally viewed by different departments and stakeholders across the company. That is why you need to be particularly attentive to which platform you choose for your business. Looker Studio and Power BI are two powerful and excellent business intelligence tools.
The reporting and business intelligence tool Power BI is developed by Microsoft and is available in multiple versions, ranging from a free desktop application to a full enterprise-level cloud service. While Looker Studio is a business intelligence tool that is part of Google’s cloud platform offering (and as such, is well integrated and works particularly well with other Google suite data sources, such as Google Analytics) and the Google Marketing Platform (GMP).
In this article, we will be highlighting the key differences between the two and helping you understand which one will fit your usage best.
Aside from its free (and less powerful) Desktop version, Power BI has four different pricing options, taken from Microsoft’s own pricing page:
“License individual users with modern, self-service analytics to visualize data with live dashboards and reports, and share insights across your organization” (around $10 per user, per month)
“License individual users to accelerate access to insights with advanced AI, unlock self-service data prep for big data, and simplify data management and access at enterprise scale” (around $20 per user, per month)
“License your organization with capacity to accelerate access to insights with advanced AI, unlock self-service data prep for big data, and simplify data management and access at enterprise scale — without per-user licenses for content consumers” (around $5,000 per capacity, per month)
Meanwhile, Looker Studio is completely free of charge, so you can start building reports and sharing your work without budgeting for it. All you need is a Google account, so you just need to head to datastudio.google.com, and you can begin creating your first dashboard.
Being a Google product, Looker Studio is natively integrated with sources such as Google Analytics, Cloud Storage, Google Sheets, Google Ads, BigQuery, and more... And if necessary, you can always install one of the over 800 partner connectors available, letting you import data from Facebook Ads from our connector, JSON, or API. You can even build your own connector! Furthermore, Looker Studio doesn’t even need an SQL data source, as it can also connect to noSQL based data sources.
What’s more, you can also merge data from different sources in the same dashboard, thanks to Google’s data blending feature. You can use data from up to 4 different sources, and each must share a set of one or more dimensions (known as a join key).
On the other hand, Power BI allows the integration of more than 100 types of data sources (both SQL and noSQL)). And much like for Google’s tool, you can integrate files (JSON, PDF, Excel, Google Analytics, etc.) and databases (sources such as BigQuery, Amazon Redshift, MySQLm Azure, etc.).
You can also blend different data sources, but Microsoft’s features are either “Append Queries” or “Merge Queries”. The former creates a new query that contains all rows from a first query followed by all rows from a second query (you “append” them after the first), much like when carrying out an “outer join” operation in an SQL database; and the latter creates a new query from two existing queries, much like in a “left join” operation in an SQL database.
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For now, Looker Studio is only available on browser (as it is fully hosted on the cloud). So, you require an internet connection and opening Looker Studio with a Google account. The dashboards you then create will be saved and accessible online.
As for Power BI, you have three options:
Data modeling is the process of analyzing and defining all the different data your business collects and produces, as well as its interactions. It is essential because it prepares your data for analysis. You can also create new fields within the existing datasets to be visualized and analyzed for more market insights you would not have found while analyzing them separately.
After you connect your source to Looker Studio, you will see a list of fields (dimensions and metrics), each of which has a name, type and default aggregation derived from the underlying data set; and all of which you can change depending on the data you want to highlight for your business objective. You can then create calculated fields, a formula that performs some action on one or more other fields in your data source; and whose output will then be displayed for every row of data in charts that include that field.
On the other hand, in Power BI, modeling is done in two steps:
You can first define relationships between your data sets, in order to calculate results and display the information you are seeking in your reports.
Thanks to Data Analysis eXpression (DAX) formulas, you can create calculated fields like in Looker Studio.
Looker Studio does not support predictive analytics that would allow you to create classification regressions or time series forecasts, so keep that in mind if you need those functions.
It also doesn’t natively support languages like Python and R. You can however use Panoply to work with those. You can also use a Google Sheet updated using Python and connect it to Looker Studio, but it will better work for smaller datasets – you should use BigQuery if you want to work with larger ones.
You can also embed a Google Analytics report in any site or app that supports the HTML iframe tag, Looker Studio automatically generates it so you do not need any knowledge of HTML.
Unlike Looker Studio, Power BI supports a wide range of predictive and advanced analytics such as clustering techniques, time series analysis, advanced analytics custom visuals, quick insights, etc.
It also supports many programming languages for transforming and gaining insights from your data (notably including DAX, M, R, Python, etc.).
And finally, it also supports embedded analytics both for your customers (not requiring authentication with Power BI) and your organization.
As we have seen throughout this article, while both Looker Studio and Power BI allow you to integrate and visualize data, the two are far from being interchangeable, as they have different features and different strengths for different uses.
To put it simply, Looker Studio is more suitable if your organization doesn’t yet have a clear BI strategy, as it is free and its many data source connectors make it polyvalent. Looker Studio is however a limited tool (in that while it supports calculated fields, it doesn’t have any of the advanced functions such as predictive or advanced analytics). Looker Studio will let you build simple and interactive dashboards easily.
However, If your BI strategy involves defining data relationships between different tables across data sources, Power BI will handle the more complicated modeling and operations with its more comprehensive, broad and advanced features. Depending on your BI budget, you can even scale your operations with each pricing plan.
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