Squad: How iBlue directs data-driven multidisciplinary teams

Squad: How iBlue directs data-driven multidisciplinary teams

Squads are teams based on an agile culture for carrying out projects, which act in an autonomous but complementary way.

Decision-making is increasingly linked to assets, channels and resources made available by technology. Since data has become so important to organizational strategies, structuring a specialized team has become vital.

Many companies are opting for partnerships, such as iBlue to implement solutions and to become more capable of making more assertive decisions. Gartner surveyed nearly 1,000 fusion teams across industries and found that 43% already turn to external IT companies to get closer to delivering value. Continue reading to understand how these squads can be formed.

High performance squads

The term squad has gained fame in IT spheres as a group of solution specialists to enable a data-driven culture. To achieve success in these demands, it is essential that the team is composed of the most qualified professionals.

At iBlue, we understand that data science is a multidisciplinary field and needs diverse and integrated profiles for a high-performance squad. In addition, we understand each customer’s need for an increasingly personalized delivery.

Taking into account that the use of data involves speed of response for decision making, it is important for companies to have teams with an agile focus on continuous deliveries. We offer complete teams that work on different fronts to solve your business challenges.

These squads can be composed of professionals from different fields within data science. Look:

Data architecture professional – Is responsible for creating data governance planning, developing the design of frameworks/pipelines.

Data engineer – Professional responsible for the soundness of the infrastructure. He will be able to implement well-built databases to enable the following activities around the data.

Data analyst – His main activity is to collect, compile and transform data into reports to generate insights for decision making.

Data scientist – Develops algorithms and modeling to use data in predictive and prescriptive analytics. It is necessary that this professional has a business-oriented vision.

Machine Learning Analyst – Creates machine learning models and solutions to work with large volumes of data in an automated way.Business Intelligence Analysts – It is often confused with the role of data analyst, however, this professional has a more tool and operational focus on monitoring metrics.

iBlue Differentials

According to the world economic forum, the first of the most valued skills in professionals by 2025 is analytical thinking and innovation. At iBlue, this expertise starts with the tech recruiters team for a more assertive selection.

We have experienced professionals who carry out processes based on combinatorial strategies between the profile of the company and the professionals.

In addition, we have the ability to make changes quickly and easily adaptable, as we closely monitor all the team’s processes.Want to know more about how we build high-performance squads?
Let’s make an appointment.

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