All Demos > Data Lake for Reference Architecture, AWS, AZURE Demo

Data Lake for Reference Architecture, AWS, AZURE Demo

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dragon1 excel import export

Symbols Set

In Dragon1, you have access to a modern set of symbols for creating a data lake architecture diagram, but also a data warehouse or any artificial intelligence solution diagram.

lake amazon data aws symbols set

Amazon (Data Lake AWS) symbols for Solution Architecture

You can make use of Amazon (AWS) symbols and create, for instance, a solution architecture for your Data Lake AWS, like the one below.

solution data architecture lakes aws

Data Lake Azure Scenarios

Below you see one of the many storage scenarios possible on Azure, the Microsoft Cloud Service.

azure data architecture lake scenario

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What is Data Lake? (Definition)

A data lake is a system or repository of data, where the data is stored in its original (raw) format. Usually, this is in the form of files.

Often a data lake is a single store of all enterprise data including raw copies of source system data and transformed data used for tasks such as reporting, visualization, advanced analytics and machine learning. It is one of the most important architectural concepts to make artificial intelligence happen.

Create and View .dragon1 Files

Dragon1 supports you to work on the platform in a repository application and in a designer application. Dragon1 also supports you to work with .dragon1 Files.

Any XLSX or CSV file and any data in the Dragon1 repository can be converted into, imported and exported as .dragon1 Files. Below is an example screenshot of a .dragon1 File.

Data Lake vs Data Warehouse

Data Lakes can contain structured data from relational databases (in rows and columns or object-oriented nodes) or semi-structured data (such as XML, JSON, CSV and logs) or any unstructured data (like PDFs, documents and email) and also binary data.

They are both widely used for the storage of big data, but they are not interchangeable. Lakes are often pools of data in the raw original format, the purpose for which is not yet defined. A data warehouse is more like a repository for structured and filtered data that has been processed for specific purposes.

Data Lake Architecture Diagram

The dynamic example is repeated below as a static diagram. It is an effective way of visualizing this concept. It is a solution reference architecture diagram.

data lake template demo

Azure (from Microsoft) and AWS (from Amazon) are two well-known solutions that include all the capabilities required to make it easy for developers, data scientists, and analysts to store data of any size, shape, and speed, and do all types of processing and analytics across platforms and languages.

Why Create a Free Trial Account?

Want to skip the step of converting an excel sheet to JSON and upload the excel sheet directly in the Viewer? Or want to store data in the Dragon1 repository? Create a trial account!

If you want to (re)use your company data professionally, you can upload the data to your paid user account. Go to the Online Store to purchase your Dragon1 PRO user license. If you would like to purchase paid user accounts for your team, please contact

Demo Steps

Click on the steps

  • Step 1 Highlight Objects Click on an Importance button to highlight the critical parts of this system.
  • Step 2 Show Data Sheet Click on the Data button, go to the Elements tab, edit the names of some data objects and click Close to see the changes in your diagram.
  • Step 3 Download Excelsheet Click on the Download Excel Sheet button to download the excel sheet, go to the Elements tab and edit the name of the Business Analyst.
  • Step 4 Convert To .dragon1 File Click on the Convert .dragon1 File to convert the excel sheet into a .dragon1 File (JSON Structured).
  • Step 5 Upload .dragon1 File Click on the Upload & View .dragon1 button. In the Viewer, click on the Upload the .dragon1 File button, select the .dragon1 file from your download folder and check out the updated Data Lake diagram. Click on the Dashboard button to see its dashboard.
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