- Product & Services
- Computer Vision
- Custom BI Development
- Managed Data Analytics & Development
- Programmatic Report Generation
Analytics Products & Services
Data analytics and data engineering servicesBusiness Intelligence & Analytics Dashboard We design and develop custom web dashboards that integrate your data sources, presented in your custom style / brandingComputer Vision Research & Development From flood detection in crop management, to facial recognition and object classification, using the latest in deep learning and AI researchPDF Generation as a Service Supertype Summary creates a highly tailored pipeline that output bespoke PDF in seconds, not days or hourshot
Data Science by Applications
Implementations of data science in various industries
Bespoke solution for enterprises
Advisory & Consulting
Portfolio & highlights
Curation of featured projects and enterprise workSupertype Incubator Supertype Incubator is a platform for data scientists and engineers to develop real-world projects sponsored and supported by SupertypenewEnterprise Data Science | Case Studies Learn how we help companies like yours take charge of their analytics initiatives and build winning systems
Technical articles by data engineers & automation developers solving real-world problems
Articles and first hand observations by data scientists & analytics experts in the field
Full-Cycle Data Science Consultancy
Data Science & Analytics ConsultingCase Study: Central Bank of Indonesia A scalable query-able API service and data archive of public opinion towards monetary policies across 100+ social media channels ft. data engineering, web automation and sentiment analysisCase Study: Adaro Mining Develop an end-to-end analytical infrastructure to facilitate real-time analytics, storage & water level prediction a 1,090km river in Kalimantan ft. deep learning, data engineering & analytics engineeringCase Study: AdColony (Opera) Taking advertising operations and monetisation to the next level using a range of machine learning techniques, ft. unsupervised learning, deep learningCase Study: Creadits Supertype's data scientists and Creadits combined to produce advertising creatives that are 40% more performant, powered by deep insights into ad creatives' lifespan, ft. Supertype Summary, unsupervised learning
Monitoring River Water Level w/ Google Data Studio
In part 2 of the Google Data Studio series, we take a deeper look into how Data Studio compares to other business intelligence tools
Adi Irawan, Business Intelligence
DEVELOPING RIVER WATER LEVEL MONITORING SYSTEM USING GOOGLE DATA STUDIO (Part 2)
Business Intelligence: Making dashboards development accessible
In the first part, I have already shared some interesting information about Google Data Studio. If you have not read it yet, I suggest you give it a read:
Google Data Studio falls into a category of tools typically referred to as Business Intelligence — other well-known tools that are often compared to Google Data Studio include Power BI by Microsoft and Tableau. Business Intelligence tools makes dashboard creation easy by the provision of drag-and-drop user interactions, compared to programming-oriented workflows and tools.
Comparison to other BI tools
As a service to the reader, here is a quick comparison table between the aforementioned business intelligence tools with an emphasis on key features and pricing:
On a more subtle level, with Google Data Studio being part of the Google ecosystem, it shares many benefits and easily take advantage of the ecosystem the way that a less-connected tool can’t. Data Studio clearly benefits from the mature ecosystem through its integration with the many tools or applications that are likely already used by data science and analytics teams.
It integrates with Google Big Query, Google Analytics, Google Documents, and also Google Colaboratory. Whenever an analyst is ready, he or she can publish the work directly from Google Data Studio to his / her teammates without requiring a subscription or license.
When I’m pushed to make a comparison, I find that Google Data Studio comes very close feature-to-feature wise with other Business Intelligence tools, with Tableau offering just a slight advantage in the variety of graphs and charting options — combination graphs, and the variety of heat maps that come out of the box with Tableau are some specific examples that would be more cumbersome to replicate for an analytics developer that is asked of the same using Data Studio.
For the programming-inclined, BI tools such as Power BI gives you the full flexibility of custom custom visualization scripts using the R or Python language interpreter — also another thing that is not easily possible with Google Data Studio. This may or may not seem like a big deal for a business user / pure visualization task, but for analytics team hoping to integrate their R / Python-based analysis tightly with the BI tool, Data Studio may be less desirable of a tool.
That said, the advantages that come with Google Data Studio outweigh the lesser aspects of it and I’ll quickly summarize them in the following section.
1. Sharing Reports Features
While working as a consultant for a company, availability and the ease of sharing the results/reports is a highly-considered factor. Google Data Studio checks this box. It works like the other Google products (e.g. Google Documents, Google Slides, and Google Spreadsheets), which includes a Share with Others feature.
Alternatively, you can also download your report as a PDF file. You can also use Google Data Studios’s Embedding tool to take the code of your report and share it on your website or other media.
2. Google Ecosystem
When using Google Data Studio, you may combine data from several sources inside and outside of the Google ecosystem into a single dashboard. External data sources, flat files, spreadsheets, Google Sheets, Google Analytics, and Google AdWords are just some of the data sources you can use.
Google Data Studio can also be connected to Google BigQuery. This will help you to generate a dashboard that is easy to update on a regular basis.
In addition, the data can even be updated in real-time. A similar function is currently available in Google Documents and Spreadsheets. Since nowadays more and more people use Google Documents and Spreadsheets, this feature will make our work easier in many ways! I will explain how to connect Google Data Studio into those Google ecosystems in a separate part.
3. Great Design
It goes without saying that any data analytics team working with a BI tool would want an appealing look for their end product. When it comes to data presentation, Google Data Studio does a magnificent job, and we have no problem giving it the right aesthetic and styling to meet the clients’ branding guidelines and business requirements:
When it comes to numbers, Google Data Studio will present them in various ways, depending on what we choose to display. We can easily include controls (The data control lets viewers change the underlying data set to which a data source connects while chart-specific controls give viewers the tools to filter their data to, say, a specific date range).
Ultimately, a tool is as good as the problem it solves; I am very satisfied with the final outcome, and our clients were blown away by the presentation and simplicity of the final product. If you are on the fence, or in the market for a Business Intelligence tools, I would highly recommend you give Google Data Studio a second look and reach out if you’d ever need help with your BI tasks!