Data visualisation is a core component of business intelligence and data-driven decision-making. These visualisations present raw data through graphs, maps, charts, and other graphics, making it easier for decision-makers to read and digest.
Organisations use data visualisation in every aspect of the business, from warehouse management to understanding customer behaviour, campaign monitoring, and financial reporting—historical and real-time reporting.
These visualisations enable organisations to compile massive amounts of data into a single number, graph, or chart for fast, accurate data-driven decision-making.
Data visualisation tools provide the tools and frameworks to convert raw data into readable graphics. Companies can sync multiple data sources to a single centralised platform for team members and stakeholders to view, analyse, collaborate, and make decisions.
Microsoft Power BI and Google Data Studio are two popular data visualisation tools we will explore in this article.
Microsoft Power BI (Business Intelligence) is data visualisation software with advanced capabilities, including data preparation, data discovery, and interactive dashboards.
Companies can integrate and combine more than 100 data sources into Power BI, including spreadsheets, webpages, services, databases (SQL, MySQL, local servers, etc.), and files (XML, JSON, CSV, etc.).
Google Data Studio (GDS) is a cloud-based tool for visualising data from multiple sources (23 from Google and 660+ from Partners).
In October 2022, Google rebranded Data Studio to Looker Studio. This rebranding consolidates Google’s business intelligence products after acquiring data analytics startup Looker in 2020.
Luckily for long-time Data Studio users, the name is the only thing that’s changed. Looker Studio looks exactly like Data Studio, so there’s nothing new to learn with this 2022 rebranding.
While GDS is capable of many data visualisation types, the platform is a favourite among marketers because of its ability to integrate website/product metrics, social media accounts, email marketing software, and ad campaigns into a single dashboard.
Like Power BI, users can create interactive dashboards and reports, albeit with less functionality. While Data Studio isn’t as powerful as Power BI, it’s free to use and requires less setup and data analytics expertise.
Deciding whether to use Power BI or Google Data Studio is more a question about your application and goals rather than which is better.
The first consideration is the ease of use. Power BI takes longer to set up and requires specialised data analytics knowledge like ETL (extract, transform, and load), DAX (Data Analysis Expressions), Multidimensional Expressions (MDX), and Power Query Formula Language to get the most out of the platform’s features and capabilities.
Google Data Studio is essentially a plug-and-play platform designed for anyone to use. While the data analytics knowledge mentioned above is helpful in GDS, you will get comparable results without it.
Best for ease of use: Data Studio.
Power BI supports hundreds of data sources, including various file formats, multiple database types, Azure, websites, and other platforms like GitHub, Salesforce, and productivity apps (Asana, Monday, etc.), to name a few.
While Data Studio supports 660+ connectors, they’re mostly Google products, ad platforms, and media-related integrations. Still, multiple database integrations are excellent for importing digital product data and comparing that with campaigns to get a holistic view of user journeys.
Best for data source integration: Power BI for business intelligence, Data Studio for marketing.
Data modelling defines different data sources and the relationships between them, allowing analysts to identify patterns and behaviours across multiple sources.
Power BI’s Power Query Editor allows advanced data modelling and transformation. Aside from the vast array of user interface options, you can also program advanced, custom models using DAX.
Data Studio’s basic data modelling allows you to blend datasets rather than clean and transform inputs. The only way to get results and granularity comparable to Power Query Editor is by running source data through Google Sheets using functions and formulas before importing it to Data Studio.
Best for data modelling: Power BI.
Power BI comes with a wide range of data visualisations, including natural language processing features that answer questions and summarise data. Users can create custom visualisations to solve problems unique to their business.
Power BI users also benefit from the marketplace, which has 400+ visualisations from third-party providers.
While Data Studio doesn’t offer the same extensive range, its 40+ data visualisation templates are more than adequate for most business needs. User can create their own data visualisations, but there is no marketplace to share templates.
Best for data visualisation customisation: Power BI.
Sharing Power BI data visualisations is tricky. You can only publish and view reports inside Power BI. Your recipients and collaborators must have a Power BI paid subscription to analyse data visualisations.
Data Studio is far more flexible when it comes to collaborating and sharing. You can invite people with a Google Account, or create a public data visualisation and share the link with anyone. Either method requires no payment from the creator or collaborator, making Data Studio significantly more accessible than Power BI.
Best for data visualisation sharing: Data Studio.
Power BI offers native applications for Android, Windows, and iOS devices. Users can view data visualisations and perform limited tasks using the Power BI app.
Data Studio does not have a mobile application, but you can access reports via mobile browsers.
Best for mobile compatibility: Power BI.
Google Data Studio is an excellent solution for organisations that are new to data analytics or are more focused on marketing and user journey analysis.
The platform’s user-friendly features and zero cost enables you to create basic business intelligence data visualisations effortlessly. You can leverage the power of Google Sheets functions and formulas to increase Data Studio’s data modelling capabilities.
Google has promised a host of new features for Looker Studio. They’re currently trialling Looker Studio on Google Cloud with plans for a full release in the first half of 2023.
Until we see those Looker Studio updates and Google Cloud integration, Power BI is the better option for enterprise data visualisations and organisations that require a sophisticated end-to-end business intelligence solution.
The platform’s wide range of features, visualisations, granularity, automation, and customisation gives Power BI the flexibility to scale with your organisation’s data needs.
The Metric Labs data analytics team includes Power BI and Data Studio experts. We can assess your business needs, recommend the right platform, and design a bespoke data visualisation solution. Contact us to learn more about our data analytics services and how we can help your business.
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