Security News > 2021 > June > Data teams are discovering the benefits of automation and flexible coding

Ascend.io announced results from its research study about the work capacity and priorities of data teams, including data analysts, data scientists, data engineers, and enterprise architects.

Amid the significant increase in the number of data pipelines across their organization, 74% of data professionals indicated their organization's need for data products is growing faster than their team size.

When asked which tasks in their data ecosystem are the most backlogged, respondents were significantly more likely to identify their own function of the business compared to their peers - with enterprise architects 2.7 times more likely to indicate data architecture as the most backlogged, data analysts 4.5 times more likely to indicate data analysis, and data scientists 5.1 times more likely to indicate data science.

The most common bottlenecks across teams include the maintenance of existing and legacy data systems, data system setup and prototyping, and needing to ask for access to data or systems.

Among the respondents, data scientists reported the greatest need to ask for access to data at 39%. "Knapp continued,"Across the board, our research shows that data engineering has become a significant roadblock for many teams.

"This can lead to significant delays for downstream users, as well as drive many teams to address data engineering bottlenecks by attempting to self-serve the data they need access to, often with mixed results, depending on the maturity of their in-house platforms. As a result, each team becomes overwhelmed with their own workload - a dynamic that can quickly lead to organizational friction, if not properly addressed, as well as inhibit the ability to meet the data needs of the business."

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