Data science teams are no longer comprised of tiny groups of Ph.D. holders exploring cutting-edge projects. Organizations that wish to stay competitive in their marketplaces today need effective data science teams.
A strategy to effectively apply advanced analytics and data science to drive better products, services and decisions has many challenges. And it all comes down to people, processes and tools.
While every organization is searching for 'unicorn' employees with strong coding, analytical, interpersonal and data story-telling skills, they quickly find out that there needs to be more of them in the market and productivity solely depends on a selected few in the organization. At the same time, knowing how things work is a well-kept secret.
As discussed in a previous blog post, organizations have three common problems when it comes to data science:
- Productivity: Almost half of the developers say they need access to the tools they need to build applications fast enough to meet deadlines, while 90% of models don't make it into production.
- Skills shortage: There are hundreds of thousands of job openings worldwide in data science and the rise of data science needs will create roughly 11.5 million job openings by 2026.
- Employee retention: The average tenure of a data scientist is at most two years. Over two-thirds of data practitioners answered in a study that they are likely to leave their jobs in 2022.
The consequences are apparent and the organizational impact can be severe. Organizations need help finding the skillset they need in the market and replacing existing staff is difficult and costly. The remaining staff has too much to deal with, delaying time to market for data science projects. As a result, employees tend to:
- Burnout due to the excessive amount of work they must pick up.
- Quietly quitting due to lack of training.
- Eventually, find new opportunities with better development opportunities and work-life balance.
What does this mean for organizations? In simple terms: competitiveness and profitability slip. What can organizations do? Re-skilling its employees and opening recruiting to non-coders is an excellent start. Organizations can keep employee retention high by engaging them in continuous training and development.
Deploying low- and no-code analytics
The fact is that organizations need a faster, more productive AI & analytics platform. Deploying SAS® Viya®, a cloud-native, low/no code analytics platform that automates processes and incorporates best practices for various organizational personas, can be a decision that immediately yields substantial benefits. SAS Viya accelerates AI and analytics for maximum efficiency and results and offers a comprehensive low/no code UI with the richest data science capabilities out-of-the-box.
SAS® Viya® supercharges productivity
With SAS Viya, organizations have met goals by automating repetitive tasks and incorporating best practices into every stage of the analytics lifecycle. Organizations can use the platform to empower everyone to do more with less training and work. Studies show that low code/no-code solutions can reduce the development time by 90% and SAS Viya allows users, even without prior knowledge, to deliver significant results quickly.
In other words, it effectively democratizes data science inside an organization. Because of this, SAS Viya is listed as a representative vendor in both the Gartner Market Guide for Multipersona DSML Platforms 2022 and the Gartner Market Guide for DSML Engineering Platforms 2022.
SAS® Viya® tackles data science skills shortages
SAS offered 346 academic programs and trained over 357,000 people in 2020 to ensure that future data leaders and practitioners graduate from institutions with SAS abilities. Besides the engagement portals, SAS has tons of other training material on YouTube and Coursera.
Studies show that 96% of those who don’t use no-code tools would be willing to use them in the future and SAS makes it easy to reskill employees from different backgrounds and business areas.
SAS® Viya® empowers employee retention
Anyone in the industry may quickly learn SAS Viya regarding training and development. SAS provides a multitude of information across many platforms and engagement portals for users to receive personalized learning. It also features an open architecture, allowing current programmers to use any language they like, including Python and R. Because of this, SAS has demonstrated outstanding results in improving retention by, among other things, lowering attrition with clients worldwide.
Organizations choose SAS Viya to accelerate AI and analytics for optimum productivity and results.
