I am able to:
Teach Software Engineering, Data Analysis, and Cyber-Physical Systems in undergraduate or graduate courses, as well as in company;
Conduct research in the areas of Software Engineering, Cyber-Physical Systems, and/or Sentimental Analysis (PLN);
Perform expertise and technical analysis in Information Technology (IT);
Manage and implement Software Engineering projects.
Competitive Intelligence based on Data – CIbD
The CIbD is a model for guiding organizations to create and develop processes for Decision-making. These processes are Data-based and must provide outcomes (artifacts or products) to business decisions. On the other hand, these processes need to be Agile for handling the business changes, which may arise without a warning. Thus, the Agile Decision Process Framework (ADPF) was thought for involving the Decision Process, Data, and Scrum. Figure 1, presents an overview of the ADPF, which was thought under the Decision-making and Agility aspects.
The ADPF may be seen in two parts: a) one where the decisions are made based on the data and their sources; b) another part contains the process based on Scrum to transform data into decision artifacts. Although these parts are integrated, we show the ADPF under the Decision Make and Data, and the Scrum method perspectives. The first part is organized into three levels:
- Level 1 represents the organizational operations (OP) grouped in frames. These operations can exchange data with each other, as well as the frames. At this level are the data sources of the organization;
- In Level 2, the Business Functions (BF) compose the Key Areas of the organization. This level represents the relationship between Levels 1 and 3. The BFs exchange data and information with Level 1, and with level 3, the BFs Exchange Information. Data and information also are exchanged with Customers, Suppliers, Government, and others;
- Level 3 represents the organization’s core concerning Decision-making (Level 2 also may decision make), where the decisions that impact the organization’s business are adopted. The organization needs to adapt quickly in the face of market dynamics. This adaptation is dependent on decision-making by managers. Therefore, managers need to be provided with adequate information tools in a timely manner. Decision-makers need agility. Thus, the exchange of information among internal and external environments is fundamental.
The second part of the ADPF is similar to the well-known Agil Scrum method. In the ADPF, the demand and priority by Decision Make Artifacts (DMA) constitute the Backlog Products. In this case are Decision-Make Products. From Decision Makers (Level 3), the Backlog is the input to the Sprint Planning activity, which involves Data Team, PO, or Decision Maker (both). In Sprint Planning, the Data Team identify whether is necessary to include the Data Exploration. The Data Exploration activity can incur the insertion of Other Data Sources, such as social media, the internet, open data, end others. A Data Team member assumes the Scrum Master role. At the end of each Sprint, a Decision Make Artifact must be derived to Decision Makers (Level 3) and revised.
We thought of the ADPF as a tool to insight and help to implement Data Analysis, Data Science, and Business Analysis Projects. For ADPF implementation contact us email@example.com.