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News
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The Impact of Machine Learning on Business Analysis

By
Kenneth Gray

Emerging technologies like Machine Learning (ML) are altering old roles and functions as firms worldwide undergo digital transformation. Business Analysis is changing to the extent where we can now analyse data, forecast trends, and make strategic decisions using Machine Learning.

Simplifying Data Analysis

Analysts within an organisation typically collect and analyse data to detect trends and advise on decisions. Machine Learning (ML) automates data analysis, changing how Business Analysts (BAs) work.

1. Automated Analysis: Machine Learning algorithms can analyse massive data sets faster and more correctly than humans. This functionality speeds up and improves data processing and lets BAs handle larger and more complicated data sets.

2. Predictive Analytics: ML can learn from data and forecast patterns. This helps BAs predict market trends and customer behaviour offering a clearer insight into improving business processes.

Improving Decision-Making

Machine learning can aid business analysis decision-making.

1. Informed Decisions: Business Analysts can provide data-driven recommendations using ML algorithms. This improves decision-making by eliminating requirements that are irrelevant, unambiguous and untestable.

2. Real-time Insights: ML can analyse data in real time, allowing BAs to make timely recommendations within the business case. This is useful in fast-changing corporate contexts.

Role Change

BAs are becoming more strategic as ML automates numerous business analysis tasks.

1. Strategic Advisors: Business Analysts may focus on requirements analysis, understanding the business’ attitude and countermeasures to risk, the impact the changes will have on the organisation as a whole and advising stakeholders on strategic business choices with Machine Learning handling data analysis.

2. Data Science Liaison: As organisations increasingly use ML, BAs typically operate as a bridge between data scientists (who design ML models) and business stakeholders, ensuring that ML models meet business objectives and requirements.

Machine Learning Skills

Business Analysts need new abilities to adapt to Machine Learning.

1. ML Literacy - BAs must comprehend Machine Learning's strengths and limits. This enables people to use ML and communicate with data scientists and ML professionals.

2. Data Literacy: ML has made data literacy more critical. Understanding data architectures, quality, privacy, and security will be crucial for current and future BAs

3. T-shaped Skills: As business analysts grow more strategic, Bas focus on improving personal qualities such as communication, influencing and problem-solving will become increasingly important.

Final thoughts 

Machine learning is transforming business analysis, enabling new data analysis, decision-making, and strategic value. Business Analysts may lead their organisations into a data-driven future by embracing Machine Learning.