Automation and greater involvement by business managers with the analytics team are just a couple of the changes that are in store for data science.
Data analytics is entering a new era, propelled by two trends in data science. First, business leaders are more frequently being moved into data roles, fueling the emergence of citizen data scientists. Second, technologies are making certain data science tasks – particularly data mining – more efficient, freeing data scientists to focus on insights. As these two trends converge, data science teams need to reshape their skillsets to reach their full potential today.
Business users increasingly charged with analytics roles
While the majority of data science leaders have years of experience in analytics, math and statistics, I have been working with many companies that are placing people from the business side (like operations or sales) into insights leadership roles. Overall, this is a smart strategy, providing data teams with better direction as to what the business really needs. It also allows the business side to understand exactly how data analysis works. With this information, they can better understand which analysis requests are most time consuming and how jobs are prioritized. However, this convergence of teams requires a new approach to data analytics.
Communication is the most fundamental skill in analytics
It may sound simple, but communication is the key to making this convergence a success. If I had to choose the single most important skill for data leaders on my team, it would be strong communication. Upcoming data leaders need to have a deep understanding of the business goals and a good relationship with department leaders, and communication is the only way to achieve these objectives. Data science leaders that align their priorities with the eventual consumer of their insights – the business team – are seen as trusted partners. This gives them an edge in gaining a seat at the strategy table and securing funding for additional resources.