Businesses get into Tableau products’ development due to the strong market position and clear competitive advantages of the data visualization category. Tableau Software is the 2nd highest solution contender which accounts for 15.04% market share.
Further, customers use Tableau Software for Data Visualization for three things: Business Intelligence, Machine Learning, and Big Data.
Furthermore, its top competitors, such as Microsoft Power BI, D3js, and HeapAnalytics, trail behind with 16.05%, 8.61%, and 3.97% market shares respectively.
Since the potential of data analytics platforms like Tableau is immense, it's essential for businesses to understand the key steps involved in creating a similar platform. And that is what we will do in this blog.
Here, we will discuss the various key points like the benefits of developing Data Analytics Platforms like Tableau, what features your tool should have, and the steps involved in developing such a product.
Let's start talking about how to build a data analytics platform like Tableau.
What is Tableau & How Does it work?
Tableau is a user-friendly data visualization tool that helps you explore and understand your data visually. It lets you create charts, graphs, and dashboards that are easy to share with others.
After being acquired by Salesforce, Tableau now offers AI-powered analytics, making it even easier to uncover hidden trends in your data. It works by connecting to various data sources, from simple Excel sheets to complex databases like Oracle or cloud platforms like AWS or Azure.
You can analyze your data in Tableau Desktop and then share your insights with others using Tableau Server.
There are 5 major components of Tableau like-
- Tableau Public
- Tableau Desktop
- Tableau Server.
- Tableau Online
- Tableau Reader
Benefits of Developing Data Analytics Platforms like Tableau
Analyzing a lot of data quickly can really help a company. It lets them use the data better to find the answers they need, which is super important. Big data analytics helps organizations make good choices by using tons of different kinds of data from lots of places to see what's going on and spot chances and dangers quickly.
They can move faster and do better with their money because it helps them figure out what works well for them.
Efficient Data Analysis: With the data analytics platform as a tool, organizations are able to analyze a large variety of data sources within a short time frame. This feature gives businesses the ability to form wisdom and trends from the data they have, which they can later apply to their decisions.
Cost Savings: Through data analytics platforms that address bottlenecks and process improvement, data analytics is used to help organizations cut costs. These mechanisms empower enterprises with the ability to achieve operational excellence, efficient material management, and the making of better business decisions.
Improved Product Development: Customer satisfaction is highly dependent on data analytics that help reveal customer needs and preferences. Through the use of data analysis, businesses reveal the information about their clients needed to develop products and services suitable for their customers, which in turn translates into more satisfied and loyal customers.
Enhanced Market Insights: Data analytics platforms give organizations the ability to identify market trends and how consumers behave. Providing businesses with market information enables staying abreast with competitors by indicating business opportunities and possible risks.
Better Decision-Making: Data analytics platforms are very valuable to businesses because they offer the insights a company needs to make faster and more informed decisions. Through such analysis of multiple data sources, the organizations can get a holistic view of the operation and hence can make more intelligent decisions.
Increased Agility: Many companies increasingly rely on data analytics platforms in order to respond to swift changes in market conditions and customer favourites. Through studying data on a present-time basis, companies will be able to tailor their strategies and processes to new emerging needs.
Key Features of Data Analytics Platforms like Tableau
Any product is being developed for a purpose. To meet that goal, it carries some key features. In the same way, when you are developing a Data Analytics Platform like Tableau, there are some features that your platform should have. What are those; you can see them below:
| Feature | Description |
| Data Connectivity | Connects to a wide range of data sources including databases, spreadsheets, cloud storage, and APIs. |
| Data Preparation | Cleans, transforms, and prepares data for analysis. This may include filtering, sorting, and creating calculated fields. |
| Data Visualization | Presents data in charts, graphs, diagrams, and other visual formats for easier comprehension. |
| Interactive Dashboards | Builds dashboards that allow users to explore data in an interactive way. Users can filter, drill down, and see different perspectives of the data. |
| Self-Service Analytics | Enables users to analyze data without relying on IT support. This is often achieved through a drag-and-drop interface. |
| Collaboration | Allows users to share dashboards and reports with others. Some platforms also allow for collaboration on data analysis projects. |
| Data Export | Exports data for further use in other applications or systems.
APIs, Webhooks, File Servers |
| Data Storage | Stores large amounts of data optimized for analytics. |
| Mobile Access | Allows users to access dashboards and reports on mobile devices. |
| AI and Machine Learning | Some platforms offer features powered by AI and machine learning, such as data pattern recognition, anomaly detection, and predictive analytics. |
Process To Develop Data Analytics Platforms like Tableau
Creating a data analytics platform like Tableau involves several stages. When you ask a custom software development company to develop one from scratch, they have a set of processes to follow. We will talk about those processes in the below section.
1. Planning and Research
First off conduct in-depth market research surrounding the different types of data analytics solutions. See market trends, competitor products, and emerging technologies that you can include in your platform.
Based on your research, define the goals, scope, and target audience for your data analytics platform. There should be strong planning that talks about business objectives and market expectations.
2. Gathering Requirements
In this phase, you have to gather the requirements to prioritize features that your platform should have. In general, a data analytics platform has features like data visualization, dashboard creation, data connectivity, and collaboration tools. You can customize the product as per your needs
3. UI/UX Design
Create wireframes to visualize the platform's design and functionality. Ask the UI designer to implement a visually appealing design and intuitive user experience.
4. Development
Now the turn is to have an appropriate use of technologies and programming languages to develop a robust data analytics platform. What features do you think of or decide in gathering time, just implement them using best coding practices.
5. Integration
For the enhanced performance of your data analytics platform, integrate it with external systems such as databases, data warehouses, third-party applications, etc if required.
6. Testing
Conduct thorough testing to evaluate the platform's performance, security, and functionality. Test usability, compatibility, and scalability across different environments and devices. Identify and address any bugs or glitches to ensure a seamless user experience.
7. Deployment and Launch
Deploy the data analytics platform on cloud or production servers. Configure access restrictions, permissions, and settings as per organizational requirements. Monitor the deployment process closely to address any issues and ensure a smooth transition to the operational phase.
8. Monitoring
Monitor user engagement and platform performance post-launch. Track key performance indicators (KPIs) to measure the platform's effectiveness in meeting business goals and user requirements.
9. Support and Maintenance
Provide ongoing support and maintenance for the data analytics platform. Budget for regular software updates to incorporate new features and enhancements.
Cost To Develop Data Analytics Platforms like Tableau
Several factors come into play when calculating the cost of developing a Data Analytics Platform like Tableau. The team size, the developer's location, the type of technology being used to develop the software, features you want it to have, etc.
In fact, Tableau's efficiency increases when it is integrated with other data sources and systems, so it is important to consider integration costs in the overall development expenses.
Besides, if you need ai software development services, the cost will increase accordingly. It's essential to carefully evaluate all these aspects to ensure a comprehensive understanding of the investment required for such a project.
Moreover, below the cost range of the developers respective of their location, so can have a rough idea of the cost to develop a data analytics platform like Tableau.
Hourly Rates of Developers by Region
| Region | Hourly Rates (USD) |
| North America | $40–250 |
| Australia | $35–150 |
| Western Europe | $35–180 |
| South America | $25–120 |
| Eastern Europe | $25–110 |
| Asia | $20–80 |
Closing Words!
We come to the end of the blog; here we have covered everything that you should know to build a data analytics platform. Still, if you can figure out any stuff related to this, then the best idea is to have a best mobile app development company by your side.
Make sure, your tech partner has prior experience in building data analytics platforms like Tableau, Microsoft Power BI, etc. For this, you can consider hiring ScalaCode, a well-known IT company with a track record of 3000+ projects in different domains.
