The role of a Data Analyst in the modern enterprise

One of the Data Analyst's first tasks is to collect and prepare raw data from various sources: websites, CRM, social networks and IoT sensors. They use tools such as SQL, Python and database management platforms to structure this information. Data preparation, including cleansing, verification and standardisation of formats, is essential to ensure the accuracy and reliability of future analyses.

Once the data is ready, the Data Analyst begins exploring it to extract insights. They use statistical methods and analysis tools such as Excel, Tableau and Power BI to detect trends, anomalies and interesting correlations. This analysis phase is crucial, as it enables the figures to be translated into concrete information that can be used to guide decision-making. For example, an analyst may discover that certain product categories sell better at certain times, providing the company with leads for adapting its marketing campaigns.

One of the key roles of the Data Analyst is to make their findings understandable to non-technical teams. This is where data visualisation comes in: using tools such as Tableau and Power BI, they create graphs, dashboards and visual reports that highlight the results of their analyses. These visualisations enable decision-makers to grasp key information at a glance and use it to take concrete action.

The data analyst also plays a role in monitoring the company's key performance indicators (KPIs). By creating interactive dashboards and monitoring metrics in real time, they enable the company to adjust its strategies in line with changes in the data. This constant monitoring guarantees responsiveness and continuous optimisation of internal processes.

Data analysts do not work in silos; they work closely with the marketing, finance, sales and IT teams to align their analyses with the objectives of each department. This collaboration ensures that the insights provided meet the specific needs of each team. For example, an analyst may work with the marketing team to identify the characteristics of the most profitable customer segments, enabling campaigns to be targeted more effectively.

The role of data analyst requires both solid technical skills and people skills. Technically, an analyst needs to master data manipulation tools (SQL, Python), visualisation software (Tableau, Power BI) and statistical methods. At the same time, communication skills are essential to convey insights clearly and convincingly to non-technical teams.

In modern businesses, the data analyst is a key player who contributes directly to achieving strategic objectives. By transforming complex data into accessible, usable information, they help the company to better understand its environment and make well-founded decisions. Thanks to their expertise, data analysts ensure that every choice is based on concrete facts, thereby strengthening the organisation's competitiveness and agility.