Application Programming & Workflow

Expert software programming and workflow automation to integrate controls, optimize processes, and enhance industrial efficiency.

Core Programming Languages

Proficiency in Popular Languages:
- SQL
- Python
- Java
- C
- C++
- Visual Basic
Syntax and Programming Concepts:
- Data Types: Strings, integers, arrays, lists, etc.
- Control Structures: Loops, conditionals (if/else), and switches.
- Functions/Methods: Defining, calling functions, passing arguments, and returning values.
- Communications: : OPC UA & DA, LTCP/RTU, MQTT, RESTful APIs, SQL DBs, WebSockets, Edge Computing.

Basic Data Structures:

Arrays, linked lists, stacks, queues, hash tables, trees (binary trees, AVL, etc.), and graphs.
Algorithms:

Sorting, searching, and graph traversal techniques.
Dynamic Programming & Recursion:

Optimization problem-solving techniques.

Version Control (Git)

Managing source code with Git.
Debugging

Identifying and fixing bugs using IDE debugging tools.
Testing Methodologies:

Unit testing, integration testing, and functional testing.
Continuous Integration/Deployment (CI/CD):

Automating building, testing, and deployment.
Code Reviews & Refactoring:

Improving performance, readability, and maintainability.

Relational Databases:

SQL expertise with MySQL, PostgreSQL, Oracle – including normalization, joins, indexes, and transactions.
Database Design:

Structuring schemas for scalability and performance.

Expertise in organizing, optimizing, and automating processes for efficient data management and workflow design.

Data Quality Assurance:

Implementing validation rules, de-duplication, and cleansing methods.
Workflow Optimization:

Streamlining processes to reduce redundancy and improve efficiency.
Task Scheduling & Automation:

Utilizing job schedulers and automation tools.

Automation Platforms:

Orchestrating data and task flows.
Workflow Visualization:

Identifying bottlenecks using tools like Visio for process optimization.
Scripting & APIs:

Leveraging APIs and webhooks for seamless integration.
Version Control:

Managing workflow changes efficiently.

Data Analysis:

Extracting insights from structured and unstructured data.
Real-Time Monitoring:

Ensuring system performance visibility.
KPIs & Metrics:

Defining key performance indicators for workflow effectiveness.

Error Resolution:

Identifying and fixing issues in data pipelines and workflows.
Root Cause Analysis:

Investigating inefficiencies and data anomalies.
Process Iteration:

Continuously refining workflows for adaptability and efficiency.

Let’s enhance your application programming, workflow automation, and data management for seamless industrial operations.