Combining All Data To See Opportunities
In every organization, many managed and unmanaged data exist. Most of them are disconnected. Think of the business processes and the software applications. They are closely connected, but their relationships and interdependencies are often unclear. Therefore, the impact of changing one or the other is not transparent.
Screenshot of an example Enterprise Architecture Visualization published in the Viewer. This is where users can slice and dice the visualizations and see patterns.
Common categories of sets of disconnected data are:
- Strategic Data
- Operational Enterprise Data (i.e. Process Logs)
- Concepts and Principles (Literature, References)
- Norms, Values, Legislation and Standards (Benchmarks)
- Solutions by Vendors
- Solution Requirements
- Transformation Data
- Reference
- Current Situation (CMDB)
- Audits and Lessons Learned
Imagine all the improvement and innovation you would see if you had all of these data managed and connected in your organization.
Dragon1, as a digital platform, helps to combine all of these datasets, so you see opportunities you did not or even know of before.
What is Data Mining?
Data mining is the computing process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. It is an interdisciplinary subfield of computer science. The overall goal of the data mining process is to extract information from a data set and transform it into an understandable structure for further use.
Read more about the Data Mining definition here.
Techniques for Data Mining
Data Mining: Follow these four steps.
1. Data Sources
First, you define and set up your data sources. Ensure you know the data source holders and the data quality. Make sure you agree on a format in which the data is extracted or delivered from the data source.
In the Import module of Dragon1, you can define a list of data sources you get your data from. And you define how the data is imported: manually, scheduled, or digitally (via SOAP/WSDL interfaces or REST-APIs)
2. Data Collections
After defining your data sources, it is time to collect and gather data from these sources so you have something to work with. Here, you use the Import module to import the data manually or by schedule.
You collect data using the Import module, and you enrich the data using the Architecture Repository web application.
3. Data Modeling
I. Models
Ok. So now you have imported managed and unmanaged data sets. Maybe because of your work, data sets on the loose have become higher quality. This is what attention does.
Modeling means relating data: what is related to what. Suppose you know which servers support an application, which applications support a process, which process produces a product, and which product is bought by clients. In that case, you know what products can be produced and sold if a certain server functions correctly. And one million other things, of course.
Modeling is done using the Visual Designer. You can create (design or draw) metamodels and next-user models. A metamodel is like the language rules, and a user model is like a story written in that language. With your metamodels, you can test the quality of your user models.
An example is: If you draw in your product metamodel that every product in your company may only use fair-trade materials, you can test every product module if non-fair trade materials are used. Or maybe you may only work with certified suppliers for certain materials. Also, this can be checked.
How well you do this job depends on your metamodels knowledge. But of course, Dragon1 has some reference models and templates to help you get going.
II. Views
A unique feature is that you can filter models. This is called creating views. Suppose a financial person is only interested in the financial data of a product model but not in the process data of the product model; you then create a financial view of the product model. This makes the financial person more likely to use the model to support his decision-making.
Creating views is done in the Visual Designer.
III. Visualizations
But there is more. After creating views, you can link any number of views to a visualization (a canvas or a template) and decide which symbols are used to show the data in the view or the model. You might want to visualize financial data with a financial icon to make things more effective.
Creating visualizations are done in the Visual Designer.
IV. Business Rules and Visual Indicators
Suppose there are patterns and rules you want to discover. Why not have Dragon1 help you see them? You can define patterns, rules, and visual indicators that indicate if patterns are present in a visualization or if business rules are followed or breached.
Working with visual indicators is done in the Visual Designer.
Deploying Data Models
After creating wonderful, good-looking visualizations, views, and models, people need to take action with them.
By publishing the data models in the Dragon1 Viewer, you enable people to access them and make decisions with them.
Example Screenshots
You see some example screenshots. We have grouped the screenshots here together and did not place them in the text above, so now the text above is better readable.
Screenshot of the Import module. You can import any data from any data source.
Screenshot of the Architecture Repository web application. Here, any data type can be imported and placed together. On the right, you have easy and quick access to certain data types.
Screenshot of a model created of the data in the Visual Designer.
You see that one of the stakeholders is colored red. That is because a business rule was defined as one in which every target audience must have its own business.
Screenshot of a view of a process showing the only flow of events and activities. The red line indicates that a certain trigger is not fired after an event occurs. Based on the process log, this could be spotted. Now, the organization has an opportunity to improve this fault situation in the process.
Dragon1 provides a template view layout, making providing strategic and transformation context easy for any model or view. On the left-hand side of the visualization, there is room for strategic data, like goals and objectives, and on the right-hand side of the picture, there is room for transformation data, like projects and deliverables.
And, of course, this template is highly configurable. Providing such a context to your model or view makes it a better decision-support diagram for executives. Use it wisely and wherever you can.
Start using Dragon1 for Data Mining
If you like what you see, then Dragon1 is the solution for data mining in a new way.
If you have any questions, you can contact our sales via phone or email. You can also start immediately with data mining by purchasing a Dragon1 PRO user license.
Good luck in spotting your overlooked opportunities and cash them!