Key positions in a data analytics team 

Although the team structure depends on the size of an organization and how that organization uses data, most data pools include three key roles: data scientist, data engineer, and data analyst. Other advanced positions, such as management, may also be relevant. Here’s a look at these important roles.

Data Science

Data scientists play a necessary role in the analysis team. These experts leverage advanced mathematical, programming, and instrumental tools (such as statistical modeling, machine learning, and artificial intelligence) to perform large-scale analysis. 

Although their roles and responsibilities vary across organizations, data scientists often do work designed to inform and shape data projects. For example, they can identify challenges that can be addressed with a data project or data source to collect for future use. Much of their time is spent designing algorithms and models for data mining and organization. 

Data collection. Soure: nois.vn
data team. Soure: nois.vn

Data Engineer

Data engineers are responsible for designing, building and maintaining datasets that can be leveraged in data projects. As such, they work closely with both data scientists and data analysts. 

The majority of data engineers perform work related to the preparation of the infrastructure and ecosystem on which the data team and the business rely. For example, data engineers collect and integrate data from a variety of sources, build a data platform for use by other members of the data team, and optimize and maintain the data warehouse. 

data team. Soure: nois.vn

Data Analyst

Data analysts use data to perform direct reports and analyses. While scientists and data engineers often interact with data in a raw or unrefined state, analysts work with data that has been cleaned up and converted into a more user-friendly format. 

Depending on the problem they are trying to solve, the types of analysis may be descriptive, diagnostic, predictive, or prescriptive. Data analysts are often responsible for maintaining digital interface pages (dashboards), generating reports, visualizing data, and using the data to forecast or navigate business activities. 

Data collection. Soure: nois.vn
data team. Soure: nois.vn

Additional positions

In addition to the job titles above, data groups often include management or leadership positions, especially in larger organizations. These positions include data manager, data executive and data director.

If you are not eligible to have A data team, how can you build data culture in your organization?

Having a dedicated team in charge of data for the organization brings many benefits; however, to build a data team that includes these positions or become a data-driven company is not simple. When resources and conditions are not allowed, enterprises can still build a data culture based on the following choices.  

Use or purchase tools for BI analysis

  • Excel, spreadsheets: easy to use, quick to set up, and easy to share with people; however, operations must be done manually; and with a very limited number of lines, which do not handle large data sets, it is difficult to see the change of data and often will not have a homogeneous source of information.  
  • Self-service Business Intelligence tools (tools and software that allow businesses to complete their own processes of data collection, filtering, comparison, visualization and analysis):  helping businesses to process the data they need without specialized knowledge such as Python, R, SQL,… All the necessary features for a “data life cycle” can be implemented using self-service tools without a data team.  
data team. Soure: nois.vn

Choosing to cooperate with a third-party data service provider with technical expertise

Although there are tools available, a lot of businesses still do not know where to start or they need quick solutions, partnering with a third-party company with technical expertise is an option worth considering. Highly specialized data companies can help businesses build or personalize an automated data collection, data processing, and reporting system that helps them make reliable data-driven decisions and save time and labor.  

Data Analytics, Machine Learning & AI
Data Analytics, Machine Learning & AI

Value of the data group

For organizations pursuing data-driven decision making, a high-skilled data pool is essential. Key positions include data scientists, data engineers, data analysts, and management and leadership roles. If your business is in the process of building an organization’s data group or intends to partner with a third-party data service provider, understand the roles and professional responsibilities of positions needed in a data team is key to achieve the best results. 

  1. Data Science 
  2. Data Engineer 
  3. Data Analyst 
  4. Additional positions  

Having a dedicated team in charge of data for the organization brings many benefits; however, to build a data team that includes these positions or become a data-driven company is not simple. When resources and conditions are not allowed, enterprises can still build a data culture based on the following choices.