Business Analysis Fundamentals

1. Introduction to Business Analysis

Let's embark on a journey to demystify the core essence of Business Analysis (BA). Here, participants will gain a profound understanding of a Business Analyst’s (BA) pivotal role within an organization and the diverse responsibilities and tasks that define this dynamic profession.

Business Analysis (BA) Overview

Common BA Responsibilities

BA Competencies

BA Prospects and Benefits

2. Software Development Life Cycles

Explore the vital role of Software Development Life Cycles (SDLCs) within business analysis. Discover how SDLC methodologies guide software development, aligning projects with business goals. Learn about various SDLC models and the crucial role of business analysts in selecting the right approach. Understand the significance of effective communication in ensuring successful software delivery that meets business needs and adds value to the organization, equipping analysts to navigate software development complexities in a business context.

What are Software Development Life Cycles (SDLC)?

Waterfall Methodology

Iterative Methodology

Agile Methodology

Agile Methodology Example

3. Requirements Specification

Now we will delve into the essential skill of requirements specification. Requirements specification is a critical aspect of business analysis, as it serves as the foundation for successful project planning and execution.

Stakeholder Analysis

Functional Requirements

Non-Functional Requirements

Requirement Specification Example

Data Requirements

Data Requirement Example: ROI Metric in Business Analysis

4. Modeling and Analysis

Explore Process Modeling, a crucial aspect of business analysis that delves into the systematic representation of business processes. Dive into the techniques and tools used to capture, analyze, and optimize organizational workflows. Gain insights into how process modeling enhances decision-making, streamlines operations, and contributes to overall business efficiency.

Process Modeling

Data Modeling

System Modeling

Data Modeling

Data modeling is a crucial aspect of business analysis that plays a pivotal role in understanding, organizing, and managing data within an organization. It involves the creation of abstract representations of data structures, relationships, and entities to facilitate efficient data management and decision-making processes.

Types of Data Models

Conceptual Data Model
- Offers a high-level view of data entities and relationships;
- Focuses on business concepts, not technical details;
- Helps understand the scope of data requirements.
Logical Data Model
- Defines data structures, entities, attributes, and relationships in a platform-independent manner;
- Represents data abstractly, irrespective of specific technologies.
Physical Data Model
- Specifies the physical implementation of data structures, considering database-specific details;
- Defines tables, indexes, constraints, and storage details.
Dimensional Data Model
- Commonly used in data warehousing and business intelligence;
- Organizes data for efficient querying and reporting using facts and dimensions.

Data modeling is an iterative process, involving collaboration with stakeholders, validation of assumptions, and model refinements. Effective data modeling ensures well-structured, accessible data aligned with an organization's strategic objectives, enabling informed decision-making and business success.

Logical model example

If you want to master your data modeling skills you can use our Relational Database and Normalization course.
Go here if needed.

¿Todo estuvo claro?

Sección 4. Capítulo 2

Contenido del Curso

Business Analysis Fundamentals

1. Introduction to Business Analysis

Business Analysis (BA) Overview Common BA Responsibilities BA Competencies BA Prospects and Benefits

2. Software Development Life Cycles

What are Software Development Life Cycles (SDLC)?Waterfall Methodology Iterative Methodology Agile Methodology Agile Methodology Example

3. Requirements Specification

Stakeholder Analysis Functional Requirements Non-Functional Requirements Requirement Specification Example Data Requirements Data Requirement Example: ROI Metric in Business Analysis

4. Modeling and Analysis

Process Modeling Data Modeling System Modeling

Business Analysis Fundamentals

Data Modeling

Types of Data Models

Conceptual Data Model
- Offers a high-level view of data entities and relationships;
- Focuses on business concepts, not technical details;
- Helps understand the scope of data requirements.
Logical Data Model
- Defines data structures, entities, attributes, and relationships in a platform-independent manner;
- Represents data abstractly, irrespective of specific technologies.
Physical Data Model
- Specifies the physical implementation of data structures, considering database-specific details;
- Defines tables, indexes, constraints, and storage details.
Dimensional Data Model
- Commonly used in data warehousing and business intelligence;
- Organizes data for efficient querying and reporting using facts and dimensions.

Logical model example

If you want to master your data modeling skills you can use our Relational Database and Normalization course.
Go here if needed.

¿Todo estuvo claro?

Sección 4. Capítulo 2