Google Data studio, a killjoy for Microsoft Power BI
Tools for analysing digital performance are multiplying, and the data we have access to is increasingly vast and complex #bigdata. It used to be that access to this data was reserved to an elite few who had mastered the technology within which the data was held captive. But today, measuring our activities is practically a necessity for survival, and it has never been easier to collect data, especially on the Internet.
But what use is data without understanding? What’s the point of having thousands – even billions – of rows in a database if you can’t make them speak? Today, pulling insights from this data is almost more important than knowing how to collect it. A new career path has even emerged… The famous data scientist!
Not everyone needs an airplane to get to work in the morning. A car, or even a bike, depending on your distance and means, would largely suffice. When you think about it, it would actually be fairly ridiculous to take a plane to go 2 km! The same logic applies to visualization solutions. The market for these products is huge, and has become more and more accessible over the past few years. It encompasses many players, each with their own particularities in terms of functionality, limitations, and of course cost – some tools can cost upwards of several hundred thousand dollars. One of the fastest growing markets right now is unquestionably made up of organizations without the budget, the skill or the time to really benefit from a high-end dashboarding tool.
“NOT EVERYONE NEEDS A PLANE TO GET TO WORK IN THE MORNING. »
This does not mean that you have to be approximate or inexact. You just have to find a shoe that fits. The market is now beginning to make visualization solutions available to small organizations that cannot afford a team of elite analysts and developers to take care of their data visualization.
These organizations need simple and accessible solutions at low cost. This is the philosophy that Google put forward when launching Data Studio Standard and Data Studio 360 :
“ ONE OF THE FUNDAMENTAL IDEAS BEHIND DATA STUDIO IS THAT DATA SHOULD BE EASILY ACCESSIBLE TO ANYONE IN AN ORGANIZATION. WE BELIEVE THAT AS MORE PEOPLE HAVE ACCESS TO DATA, BETTER DECISIONS WILL BE MADE. »
In this regard, one of Data Studio's direct competitors is Microsoft's Power BI tool , the result of the acquisition of Datazen Software by Microsoft in April 2014 .

With the launch of Data Studio 360 announced in March 2016 , Google is now playing in the court of data visualization tool providers. But does Data Studio really compete with Microsoft Power BI? At present, a strict comparison would be biased, if not impossible, due to the fact that Power BI is an established tool while Google Data Studio is just out of Beta. Let's do the exercise anyway.
VARIETY OF CONNECTORS
In terms of accessible connectors, Power BI offers a much wider range than Google Data Studio. On the other hand, the fact that most of the connectors with Google products — including Google Sheet, the Excel equivalent of the Google office suite — are accessible with Data Studio is a real strength, especially when you see the omnipresence of Google Analytics. able and Google Adwords in advertising for a majority of sites.
EASE OF USE AND COLLABORATIVE WORK
Another point that sets Google Data Studio apart is its ease of use and its clean interface, always in the spirit of making data accessible to as many people as possible. The possibility of working simultaneously on the same dashboard is appreciable and offers the same advantages as the Drive office suite (Sheet / Slides / Docs / Forms).

TWO VERY DIFFERENT DNAS, TWO VERY DIFFERENT PHILOSOPHIES
The major difference between the two tools, apart from the DNA of the parent company that transpires for each product, is that Google Data Studio is clearly positioned as a cloud-type tool. Power BI is available in three distinct tools (Power BI desktop, Power BI mobile and the Cloud version Power BI embedded) while Data Studio only presents itself on the Cloud. Google has even taken this philosophy of rejecting classic reporting to the point of not offering data export in Data Studio , with the aim of encouraging its users to consume dynamic rather than static data. Finally, Power Bi charges its users for the weight of data they use (the free version of the tool allows the use of up to 1 GB of data) while Data Studio has chosen to limit its users in its version standard (free) to 5 dashboards per user account (the paid version up to 1000 dashboards per user).
In Conclusion
Though it still has a way to go, Data Studio 360 seems like a promising solution. Here, we are witnessing the emergence of a new Google/Microsoft duel. Each tool is strongly influenced by the guiding principles of its parent company – and supported by a horde of loyal fans! While both tools serve a purpose, I’m sure you can guess which one we would shelve. 😉
The free version of Data Studio is now available to the public. Although it’s not quite there yet, new additions will quickly bring this product to maturity. We can’t wait!
Share this
You May Also Like
These Related Stories

Should the management or marketing data be centralized or decentralized?
For a few years now, I’ve been asked the following question about the management and activation of digital and marketing data on a regular basis: Should the management of marketing data be decentralized or centralized (BI/IT team vs. marketing team)? Before starting to discuss the issue, you should understand that this debate between centralization and decentralization has always existed. The giants of digital (of which Netflix was the precursor) have noted over time that adopting a decentralized (microservices) architecture, which is by nature more flexible, enables a faster development time for their products and digital applications, in addition to fostering innovation internally. Microservices architectures are characterized by independent services that can function autonomously, often developed by small teams. On the other hand, monolithic architectures are more rigid. The following charts illustrate the structural difference between these two types of architecture. Representation …

2nd Party Data, or how to take advantage of your partnerships for your digital media campaigns
MEDIA & SEM In recent years, we have seen an increase in digital advertising investments. It goes without saying since our use of the Internet continues to increase. It therefore becomes imperative for advertisers to vary their tactics in order to stand out in this highly competitive field. The majority of them are already using 1st Party Data and 3rd Party Data, but few advertisers are aware of the benefit of using 2nd Party Data. WHAT IS 2ND PARTY DATA? 2nd Party Data is literally another advertiser's 1st Party Data. Usually, this data is made available through a partnership between these two advertisers. It can be two partners offering complementary products (eg airline and credit card company), or two partners with a very similar target (luxury car manufacturer and golf club company). Following this partnership, it is possible to implement its retargeting pixels on the partner's site or to share these audiences via your DMP (Data Management Platform) in order to use them. To le …

Adapting enterprise data lake architecture for marketing analytics
Marketing data has been growing for the past 10 years. As mentioned in one of my previous articles , according to Toolbox , most marketing departments today have, on average, up to 16 MarTech platforms in their stack (and up to 20 on the B2B side). All these platforms generate data, even big data. Consequently, it becomes more and more difficult to manage the marketing data of these different platforms in silos. A better solution is to unify your data to get the most value out of it for the business. With this in mind, many marketers are beginning to consider creating their own data lake or warehouse, with the goal of centralizing and leveraging data in a single environment. The challenge for these marketers is that very often their company already has a data lake or warehouse which, unfortunately, prioritizes sources of data other than those of marketing. These lakes or warehouses are usually managed by IT and business intelligence (BI) teams. In addition, marketing data is sometimes …
Repérer et valoriser ce qui compte vraiment.
Recevez nos analyses et conseils pour rester à l’avant-garde du numérique.