Understanding the Roles of a Data Engineer, Data Analyst and Data Scientist
The collection, analysis and use of data has transformed the world and continues to do so. From helping cities like Copenhagen become smarter, to providing insight into shifts in consumer habits, data is the fuel that drives innovation and design of just about everything. Data is critical to how organisations develop strategy and plan to achieve their future visions.
As the importance of data has become clearer, and its use universal, new jobs have come into being. Three such jobs are data analysts, data scientists and data engineers. In this article, you’ll learn the key differences between these three functions.
What Is The Role of a Data Analyst?
Data analysts take collected information, crunch it to answer questions their organisation may have, and communicate their results to engage leadership to make highly informed and valuable decisions.
Data analyst jobs’ titles vary from company to company and between industries. In one business, the data analyst may be called a ‘business intelligence analyst’, in another a ‘business analyst’, and in another a ‘database analyst’. Irrespective of job title, the role is likely to include data cleaning, analysis, and creating insight, helping businesses at both technical and non-technical levels to connect their siloed operations and drive strategic direction.
While data analyst jobs are often entry level, they may also be performed at a senior level. Their job is to remove guesswork from decision making by analysing translating data into meaningful information. This information often acts as a bridge between otherwise segregated teams, aiding managers, supervisors and employees to recognise business-critical connections.
Data analysts must be adept with technical tools and be good communicators to deliver the game-changing results of which they are capable.
What is The Role of a Data Scientist?
Data scientists undertake similar roles to data analysts, though they will have a greater depth of knowledge and expertise. Many of their tasks are like those of data analysts, but with a greater knowledge of algorithms and statistics they are more likely to become engaged in training machine learning models capable of forecasting the future.
Data scientists employ a host of learning techniques (e.g. regression, clustering, neural networks, etc.) to inform machine learning, with the aim of identifying patterns to enable accurate forecasting. Data scientists have a deep technical knowledge, are focused, and with creativity founded on a logical approach. The work they do may include:
- Validating analysis by evaluating statistical models
- Training machine learning to develop improved algorithms
- Testing and training machine learning models
Data scientists add value to organisations by answering new questions and developing machine learning models that make forecasts from new data.
What Is The Role Of A Data Engineer?
Without data engineers, data analysts and data scientists would not exist. The role of a data engineer is to ensure that data is available to work with, by ensuring that it is collected and transformed, and stored effectively for use by others.
For organisations to benefit from data, data engineers create data pipelines capable of handling enormous amounts of data. Often using complex techniques and tools, the data engineer is likely to be skilled in software development with tasks that might include:
- Building APIs to allow data to direct correctly
- Applying new features on machine learning models
- Optimising system performance
- Integrating data from various sources into current data pipelines
Data engineers provide value by saving their organisations time and effort, helping to streamline data analysis and use. With companies increasingly reliant on vast amounts of data to drive decision making, the data engineer’s role is crucial to both strategic planning and financial performance.
How Data Engineers, Data Analysts And Data Scientists Fit Into Data Process
To understand how data engineers, data analysts and data scientists fit into an organisation’s process, consider this workflow:
- The data analyst extracts new data using an API that the data engineer delivered.
- The data analyst identifies trends from the collected data and presents them so that non-technical employees can understand them. This provides insight into what it is that the organisation is doing and how well they are performing.
- The data scientist takes the analyst’s work a step further, building greater depth of insight with advanced analytics and employing machine learning to provide a new vision for the future.
Where Is Your Career Path?
The use of data to inform decisions is only going to become more prevalent. We live in a data-driven world, and businesses and organisations are discovering new data to collect, new ways to analyse it, and improving its predictive capabilities at a breathtaking pace.Whatever your current level – whether a first-jobber or an experienced senior level executive – we would like to hear from you. There are many very exciting opportunities for data analysts, data scientists and data engineers. To discover your new role, contact the Data Analytics Team at Prime Insight.