In today’s data-driven landscape, companies across industries depend on data analysts to transform complex, raw data into actionable insights.
With access to extensive customer data, operational metrics, and market trends, businesses require skilled professionals who can interpret this information, reveal meaningful patterns, and support strategic, data-informed decision-making.
Dorcas Folasade Oyebode, a data analyst at Eybrids, in a paper, “The Role of Data Analyst in Modern Business: Unlocking Insights for Informed Decision-Making,” believed professionals in this field have grown from mere number crunchers to essential partners in shaping business direction since data has become central to decision-making.
For her, data analysis is complex, and it involves a mix of data collection, preparation, interpretation, and visualisation, which contribute to generating reliable insight that supports decision-making.
She explained that data analysts generate reliable insights that support decision-making by collecting and gathering data from multiple sources: databases, APIs, or external files, while identifying data cleaning, which enables data accuracy, consistency, and reliability, as an important part of this process.
The analyst, she stated, ensures that there are no duplicates, handles missing values, and corrects inaccuracies to create a solid foundation for analysis.
Folasade also stressed the need for exploratory data analysis (EDA) to identify patterns, trends, and correlations since they always answer specific business questions, highlighting growth, optimisation, or problem-solving areas.
She observed that professionals in this area function maximally with collaboration and cross-functional teams.
“Data analysts hardly work in isolation. Instead, they collaborate closely with finance, marketing, operations, and sales departments to make shared data insights with strategic goals. A retail analyst, for example, can collaborate with a marketing team to elaborate on targeting customers based on their purchasing behaviour,” she stated.
Folasade identified one of the strategic impacts of data analysts on modern businesses as the provision of insights based on meticulous analysis that empower companies to make informed decisions grounded in data rather than intuition.
According to her, an analyst’s involvement in an organisation drives better operational efficiency, informed risk management, and customer engagement.
“For example, a finance analyst can predict cash flow or assess credit risk, enabling businesses or organisations to plan with greater confidence. At the same time, a retail analyst can segment customers based on their purchasing power or behaviour to tailor their marketing messages, making them more appropriate and effective,” she added.
Organisations and businesses can also streamline their operations across departments with the help of a data analyst, Folasade argued. This, she believed, can be achieved through data-driven analysis, where they pinpoint inefficiencies in processes and help organisations reduce waste and optimise resources.
Using supply chain management as an example, Folasade is of the strong opinion that data analysts can be used to analyse inventory levels, delivery times, and supplier performance to help streamline operations by pointing out bottlenecks and improving inventory turnover, enabling companies to respond quickly to demand changes and improving overall productivity.
Besides, she believed data analysts are crucial in the area of risk management, regulatory compliance and customer-centric strategies
On regulatory compliance, Folasade argued that data analysts play a crucial role by frequently monitoring and reporting on data-related risks and ensuring businesses avoid costly legal issues.
“Data analysts are vital in helping businesses build and maintain a competitive edge in an era when data is a significant asset. Continually assessing and adapting to market trends and customer behaviour, operational data analysts ensure that organisations are agile and responsive to change,” she stated.
Data crunchers play a critical role in modern business by transforming complex, raw data into actionable insights that guide strategic decision-making. Their responsibilities, from data collection and cleaning to interpretation, visualisation, and predictive modelling, ensure that businesses make informed, data-driven decisions.
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