How to structure an unbeatable DataOps team

DataOps is a new approach that has come to revolutionize the areas of data science and analytics . And to keep up with advances and maintain a competitive advantage , your company needs a well-structured data team .

And we want to help you with that!

Check out now what this new approach is and which professionals are needed to form an unbeatable DataOps team .

What is DataOps?

DataOps is a new culture of collaboration between development , operations and data teams , in which companies, after joining, begin to result in data projects with increasingly more:

• quality
• efficiency
• delivery speed
• valor real

All this in a continuous and reliable way , until it reaches the end user, optimizing the daily lives of companies of all sizes.

Learn all about DataOps trends for 2021 here .

How to structure a DataOps team?

In fact, it's time to upgrade your data analytics team to a DataOps team .

To do this, it is necessary to review functions, tools and processes, since the DataOps methodology requires new ways of working, different from the standard followed to date.

For example, the team needs to have a certain degree of independence to meet the agility and flexibility required by DataOps. In addition, you also need the entire team to have access to computers, networks and other flow services, as well as an effective method of communication .

All of this is aimed at unifying previously fragmented data and transforming it into a high -quality resource that will create value for users. To achieve this, your company's data team should focus on these four tasks:

1. data provision
2. data preparation
3. data consumption
4. data flow management

And to carry them out, your team must be structured with some specific functions. So, find out below which professionals make up an unbeatable DataOps team .

Which professionals make up a DataOps team?

In the composition of a DataOps team , there are five main functions to perform the tasks mentioned above (data supply, preparation, consumption and management).

Among them, the first ones we are going to show are already known to those who work in the data area. And, in the end, you will discover the true innovation of DataOps: a new but essential function that makes teams much more productive .

Shall we get to know them?

Data engineer

Anyone who is a data engineer or data engineer has the responsibility of:

• ensure the first task, that is, that the data supply is flowing, from its origin to the correct destinations ;
• and develop data flows that will lay the foundation for other team members to perform analysis.

Two other practical functions of the data engineer profession are: moving data from operational systems (ERP, CRM, MRP, etc.) to a data lake ; and implement data quality testing .

Analytics engineer

As part of the second task of the DataOps team, which is data preparation , in the role of analytics engineer , it will be your responsibility to ensure the creation of a data infrastructure that is as robust as it is easy to understand.

It is a profession that involves:

• transformation and organization of data for analysis.
• data warehouse development .
• knowledge in SQL, DBT, BI , business strategies and programming language.
• and a lot of communication skills .

It is a function that acts as a bridge for analysts and end users to follow a technically efficient process to make the best decisions.

Data Analyst

The data analyst role is another key role within the DataOps team, ensuring the third task, data consumption .

It will also be your responsibility to prepare and answer business questions using data already prepared by previous professionals, and monitor indicators in business intelligence tools .

And the scope of this function also includes summarizing and synthesizing large amounts of data for consumption by end users, creating visual representations of data that facilitate the communication of information and enable the generation of insights .

Data scientist

The data scientist role is a real need for large companies or very specific projects.

Holding this position, you will have to go through tasks three and four working to build predictive and prescriptive models in order to optimize processes and generate innovative products using artificial intelligence .

And this will be based on data that has already been extracted, loaded and transformed (ELT), but you will also create new data using advanced statistical and machine learning techniques.

DataOps engineer

DataOps engineer is the role responsible for the fourth task: managing this entire flow between data professionals, applying agile development , DevOps and lean manufacturing techniques to data analysis.

In this role, you will orchestrate and automate the data analysis pipeline to make it more flexible, without losing quality.

How is this management carried out?

• Using tools that facilitate communication between development, operations and data analysis personnel.
• Providing data scientists with tools to instantiate development environments on demand.
• Creating testing and data monitoring platforms, among other functions.

In short, through the automations provided by the tools, the DataOps engineer eliminates bottlenecks in data flows, causing a significant increase in the team's productivity .

Work with an unbeatable DataOps team

Our Indicium team is a leader in data science and analytics in Latin America . And we really want to help you with your growth project.

Get in touch today here .