What is the role of data in business analysis? Isn’t it something to worry about later, when working on design specs? Is this even a business analyst’s job?
This topic comes up regularly, and no surprise. Organizations create data at neck-breaking speed – and often it results in more data than they can manage.
Without intelligent data management practices, organizations are not able to take advantage of their data.
Business analysts play a central role in defining requirements for organizational changes – and it’s not possible to do that without considering data.
Data connects business processes and the parts of an organization to create an integrated enterprise. Every single business change involves changing business data: creating new data, sharing it, using it to make decisions or to store information for future use. We cannot analyze business processes and disregard the data that these processes will use or update.
We need data to:
- develop the right products
- connect to our customers at the right time
- detect process inefficiencies
- learn the patterns of customer behaviour
- understand and predict customer needs
Organizations need data to make better business decisions.
Business analysts’ mission is to help their clients solve business problems. And this requires making smart business decisions based on clean, consistent, conformed, current, and comprehensive data. This means producing useful business analytics insights, and business analysis is essential to:
- understand the problem that needs to be solved
- identify what data is required to produce the insights
- define analytics requirements
A business analyst needs to understand the fundamentals of data management and data analysis to provide value to modern data-driven enterprises.
So what do business analysts need to know about data?
- what is data
- in what forms it exists
- where it can be stored
- how it may be structured
- understanding the difference between data, information and knowledge
Types of data
- structured, unstructured data, and semi-structured data
- quantitative and qualitative data
- nominal vs. ordinal qualitative data, understanding flags and codes
- quantitative data: discrete vs continuous, storing dates and times
Key concepts of structured data and relational data structures
- data entities
- What happens with data as it gets created, moves around, is transformed, restructured, used, shared, and eventually destroyed.
- Requirements for managing data at every stage of its lifecycle.
Types of analytics and questions it can answer
- descriptive analytics
- diagnostic analytics
- predictive analytics
- prescriptive analytics
Business intelligence personas and their needs
- casual consumers
- data analysts
- power users
- data scientists
To analyze these requirements for managing, using and sharing data, business analysts need to learn additional tools and techniques:
- conceptual data modelling
- defining and describing data (data dictionaries, metadata, and markup languages)
- data mapping
- querying structured data, basics of SQL (Structured Query Language)
- basics of data profiling
- data visualization
A business analyst that masters these fundamental skills and continues to develop their competencies in the areas of data management, governance, and business intelligence, will be a sought-after asset with more career paths opening up in their future.
Employers that empower their business analysis resources to learn more about data will create a powerhouse to elevate their organization’s analytics and decision-making maturity.
More resources in the Data category.