A Complete Guide to Data Analytics Team Responsibilities

Data and analytics are at the core of the digital business today, being one of the most important parts to focus on.

If not handled appropriately, technology can be a point of failure, although it is rarely an impediment to advancement.

But, if you are new in the data analytics world, this post might help you acquire knowledge about the roles and responsibilities of a successful analytics team.

In this post, we’ll look at the core roles and responsibilities of a data analytics team.

So, without any further ado, let’s get into it:

Important members of a data analytics team and their responsibilities

Most data teams have three core roles:

  1. Data Scientists
  2. Data Analysts
  3. Data Engineer

Team structure varies depending on the companies that use data analytics and their structure. Other high-level positions, such as management, could be engaged as well.

Check this image from Gartner. You will find the core difference between all the data analytics profiles and their main skills.

Data Science Team

Source: Gartner

Take a look at these crucial roles.

What are the roles and responsibilities of Data Scientists?

On the analytics team, a data scientist plays a vital role. These specialists use programming, complex mathematics, and tools (such as statistical modeling, machine learning, and artificial intelligence) to undertake large-scale analyses.

Data scientists often carry out work that informs and shapes data projects, while their position and duties vary by business. They may, for example, suggest problems that might be solved with a data source or data project that can be collected for future use. They spend a lot of time developing algorithms and models to mine and organize data for business strategy.

The following are the responsibilities of Data Scientists in brief:

  • Model analysis and design
  • Create machine learning models and put them to the test.
  • Carry out quality control inspections to ensure that the models are of good quality.
  • Allow models to be released into production.

What are the roles and responsibilities of a Data Analyst?

A data analyst employs different methods for analyzing data and reporting. A data analyst works with data that has already been cleansed and turned into more user-friendly formats, whereas data scientists and engineers work with raw or unrefined data.

Their analysis could be informative, analytical, predictive, or prescriptive, depending on the problem they’re trying to solve or address. A data analyst is frequently in charge of managing dashboards, generating reports, creating data visualizations, and forecasting or guiding corporate activities using data.

A data analyst must be familiar with the technical aspects of data collection, analysis, and reporting. They must be able to spot patterns and trends.

Key data analyst tasks, according to Workable, include

  • Data analysis and reporting using statistical techniques.
  • Databases and data collection systems development and implementation.
  • Obtaining and maintaining data from primary and secondary sources.
  • Detecting, analyzing, and understanding patterns or trends in large data sets.
  • Data cleansing and filtering.
  • Collaborating with management to identify and prioritize business and information requirements.
  • Identifying and outlining new opportunities for process improvement.

What are the roles and responsibilities of a Data Engineer?

Data engineers are in charge of creating, maintaining, and designing datasets that can be used in data initiatives. As a result, they collaborate closely with both data scientists and analysts.

Data engineers spend a lot of their time preparing the infrastructure and ecosystem on which the data team and organization relies. Data engineers, for example, collect and integrate data from a variety of sources, provide data platforms for other members of the data team, and optimize and maintain the data warehouse.

Data engineers are accountable for organizing and managing data while also looking for discrepancies or trends that may influence business objectives. It’s a highly technical job requiring experience and knowledge in programming, mathematics, and computer science.

The following are a few of the roles of a Data Engineer:

  • Obtaining information and creating procedures for data collection.
  • Determine how to improve data efficiency, accuracy, and quality.
  • Conduct research to find solutions to industry and business-related questions.
  • To solve business problems, make use of enormous data sets.
  • Use advanced analytics software, machine learning, and statistical methodologies.

Other positions in data analysis team

When building a data analytics department structure, data teams often include a management or leadership function in addition to the job titles listed above, especially in larger firms. Data manager, chief data officer, and data director are examples of these positions.

What is a role of a Data Manager in the data analysis team?

A data analytics manager’s job is to maintain records of a company’s numerous data systems and networks. A project manager’s responsibilities include properly organizing, holding, and analyzing company data and maintaining a company’s privacy and safety standards.

What is a Role of a Chief Data Officer in the data analysis team?

The CDO is in charge of various data-related responsibilities, such as data management, data quality assurance, and data strategy development. They may also be in charge of data analytics and business intelligence, which is extracting useful information from data.

3 factors to consider when building a Data Analytics team

  1. Strength of the team

    Team strengths are critical to increasing productivity and ensuring your company’s success. You may enhance team trust and engagement by playing to your team’s strengths.

    Even before forming the team, you should concentrate on its strengths. This is especially true if you use team goals to set goals. A good leader will rely on the team’s talents to guide them through difficult situations.

    Strengths and skillsets exhibited and shared among a group of people are team strengths. They are characteristics that contribute to a team’s long-term success. Individual strengths bring people together around common aims and ideals, resulting in a cohesive team.

  2. Decentralization of the team

    Analytics programs are highly centralized in some firms, with a single data team serving the entire organization. Other companies embrace a decentralized strategy, with each department or business unit having its resources, processes, and workers. Some people use a mixed approach.

    While each technique has advantages and disadvantages, none is intrinsically right or wrong. Your organization’s data relationship determines the one you use.

    However, it has a huge impact on the organization of your data team and data governance processes. Therefore it’s vital to think about it.

    The data architect’s duty evolves to reviewing and curating the greatest ideas from the business’s margins, then cataloging them as standards for everyone to utilize. Collaborative analytics improves efficiency and consistency while allowing the company to make confident decisions that lead to the greatest results.

  3. Impacts of your data strategy

    Developing a data strategy is not a stand-alone task; your business plan must guide it. As a result, the business’s strategic objectives are an important beginning point for any data strategy.

    After all, what good is a data strategy – or even data in general – if it doesn’t assist you in reaching your organization’s objectives? So, before diving into your data strategy, take a look at your company plan first and then your data strategy.

    Every company function, department, and team may use data to make better decisions. In HR, for example, data is being applied to compute the likelihood of people leaving the organization, which allows HR and managers to engage critical personnel better and reduce turnover.

Importance of the Data Analytics team

Data will continue to drive how the world works as we know it. From a corporate standpoint, data analytics is the instrument that enables today’s business leaders to both comprehend how their company is performing and identify areas that require attention.

The data analytics team is the key to good decision-making since it provides critical insights into whether an organization is headed on the correct path. Skilled data analysts, the correct tools, and the right infrastructure will aid in identifying market trends and explaining the mechanisms behind the effectiveness of one product or service vs. another that isn’t performing as well.

The data analytics team helps businesses succeed by fostering focused thinking, maintaining key decision-makers, streamlining procedures, and streamlining communication between business executives and data professionals.

Frequently Asked Questions

What are the roles in a data team?

A typical data team consists of the following roles:

  • Product managers
  • Data analysts
  • Data scientists
  • Data engineers

What is a data analytics team?

An analytics team is a group of people tasked with collecting all of a company’s big data. They then use this information to create future company models and strategies.

Do data analysts work in teams?

Many data analysts work in groups, and they conduct a lot of their work on computers. Much of the job can be done from a remote office or home, though this varies depending on collected data.

What is the importance of data analysis?

Data analysis is critical in research because it simplifies and improves data processing. It enables researchers to evaluate data easily, ensuring that nothing is overlooked that could aid in discovering new information.

Conclusion

Data and analytics are becoming increasingly important and strategic, posing new difficulties for enterprises and their analytics and data leaders. Some conventional IT roles are being displaced by non-tech business users performing “citizen” responsibilities. Other new hybrid positions that span functions and departments and combine IT and business expertise are emerging.

Gaurang Bhatt

Written by

Gaurang Bhatt

Gaurang has 15+ years of experience solving complex business problems and enabling businesses with data-driven decisions using data analysis and predictive modeling tools like Tableau, Power BI, Looker, and Google Data Studio. His expertise lies in data visualization, reporting, and creating ETL pipelines. In addition, he is passionate about exploring different technologies like machine learning and AI. He shares his knowledge and learnings on the LabsMedia platform.