One of the most sought-after figures on the market is the data analyst. Nowadays, the study and analysis of data represent key added value across almost all production chains and, more broadly, within companies. In today’s increasingly interconnected world, you can choose a data analytics consulting company to become essential for businesses to stay competitive. E-commerce, social networks, and various digital services generate an immense amount of data every day, with its value increasing exponentially. However, the real value of data is not in its creation but in the ability of providers of goods and services, not only digital, to analyze its trends and enable its aggregation. Ready to maximize your data’s potential? Partner with experts today!
Who is the data analyst?
A data analyst will be a person who has the analytical and aggregating skills of handling data to know, for example, the performance indicators of a certain product, so in that way enabling the company he or she works for to design its business models in a prospective way, creating its competitive advantage on the market. In fact, without data analytics consulting, the data collected by the company could not “speak”, becoming useful and understandable information, completely heterogeneous and taken individually.
Precisely because of the amplitude of data that can be collected and to which they could be used within the various market sectors, the professional entrusts a transversal skill to himself that is able to be both technical but also statistical, managerial, and communicative.
The activities that the company’s data analyst does
He or she will be called upon to:
- collect data from various sources;
- structure the data according to accurate aggregative logic;
- develop statistical methodologies for data interpretation aimed at finding possible critical issues or strengths in the business model;
- report, through reports, what emerged in the various company areas.
Based on the assessments and analyzes carried out by the data analyst, the company will therefore be able to make so-called data-driven decisions, that is, guided by the data.
Role of Data Analyst for companies
The data analyst is expected to mainly extrapolate the data considered fundamental, organize it, and process it according to statistical models so that the findings would flow into specific reports.
Based on the research conducted by the Big Data Analytics & Business Intelligence on job offers on LinkedIn, it emerged that, in practice, the data analyst carries out different tasks according to the type of sector and business context in which he operates.
In a company that operates in the business intelligence sector, for example, the data analyst is required to mainly use Microsoft Excel and relational databases or to create and update reports through the use of one or more data visualization software.
Big data analyst: What does this professional do?
In contexts that have to do more specifically with the analysis of data, the professional role of a data analyst is also charged with the task of implementing complex statistical models or of creating machine learning algorithms for the analysis of enormous quantities of data, in this case residual within the current job market: we speak, in this respect, of a big data analyst.
In general, the data analyst is supposed to know statistics and database management, both relational and non-relational. More precisely, his tasks are:
- to work with managers from different company departments-marketing, logistics, human resources, research and development, and sales with project managers and data scientists to identify the critical issues of the business;
- to understand if those critical issues can be solved by a statistical analysis of the data;
Collect data from a variety of sources:
- web analytics, environmental sensors, etc., analyze them, sort them, and agglomerate them to have comparable data to be studied;
- assure data quality, find out if some are duplicates, correct eventual collection errors, and filter irrelevant data.
So-called data cleaning:
- Report to the competent structures any anomalies, if found, in the systems responsible for data gathering and storage;
- interpret the data in statistical models enabling the identification of trends, or find repeated patterns in their structure that might point you to understand the origin of critical issues highlighted in the business model;
- present and share, with company managers, executives, and project managers, the results of the analyses carried out on data employing reports, tables, diagrams, and graphs that make immediate the statistical results of the data visualization activity.
Differences Between Data Scientists and Data Analysts
Compared to the data analyst, the data scientist is a high-level strategic professional figure who works alongside the management in strategic planning activities. while the former focuses on the analysis and raw interpretation of data, the latter carries out a further operation, building on the grounds of the data thus structured, actual strategic forecasting models.
Also within the data analytics consulting firms, the responsibilities and the classification of the two figures are different: in practice, the data scientist assumes a managerial role concerning the data analysts called upon to perform a series of activities based on the assumptions defined by the former.
More skills for the Data Scientist
Although both figures need to perform analytics and interpretation of data contained within company databases and to get various types of information from the same, the task of a data analyst usually does not encompass the construction of entire statistical models or machine learning algorithms or sophisticated programming. Moreover, he has to make the interpretation of the data in light of the whole story of the company, hence developing many scenarios’ analyses and a business road map. The required technical skills of a data scientist are more significant: as a matter of fact, he can easily use most systems for data processing, program in the most common programming languages, machine learning, and statistic processing systems.
Conclusion
Data analysts play a crucial role in transforming raw data into actionable insights, enabling data-driven decisions that enhance a company’s competitive advantage. Their responsibilities include data collection, cleaning, and analysis using statistical models to identify trends and business-critical insights. Unlike data scientists, who focus on strategic forecasting and advanced modeling, data analysts prioritize data interpretation and reporting. At N-iX, data analysts contribute significantly by collaborating across departments, ensuring data quality, and delivering comprehensive reports. Their technical expertise and collaboration with managers and project leads help companies streamline operations, improve performance, and build robust data-driven strategies in a competitive market landscape.
