Every business wants the advantages of data solutions. But analytics insights are only as good as the data—and the people—behind them.
With companies committing million over the next year to analytics software, services, training and consulting, IT leaders are mobilizing to fill work force skill gaps, implement data quality assurance measures and improve data governance and security protocols, the report found.
A major part of these efforts center around recruiting qualified data professionals and upskilling existing IT personnel.
At Eli Lilly & Company, for example, an initiative to provide enterprise-wide analytics training to a work force of over 30,000 is underway.
Historically, chief data officers have looked at building data infrastructure, AI models, etc. Those are all important. But I think having an intentional effort to bring about organizational change and people involvement through upskilling are important parts of the success.
Individual companies have distinct data needs: internal business processes and IT operations automation, as well as customer insight, engagement and service, as the most common areas for analytics upgrades.
To get the most out of investments in new and emerging data technologies, the majority of survey respondents (83 percent) have prioritized self-service tools to facilitate better data access, and four in ten said they are looking to recruit talent with the skills to provide analytics training to non-technical staff.
On the technical side, data architects, data management, data security and data integration skills remain in high demand, according to industry analysts.
The biggest challenge in building a data skills training program is addressing the needs around both data infrastructure and data analysis.
Data analytics is a top objective for many companies; they are targeting three skill areas: data infrastructure, data security and database administration.
The demand for technical talent appears to be aligning with a broader, more nuanced understanding of what companies need in order to get the most out of data investments.
Companies have been working to address the need for data engineering, data science and AI/ML talent over the last five years, but it is not a game of the data scientists anymore. It is a game of getting the organization as a whole to be culturally evolving, to be performing in an AI enabled ecosystem.
The question in conclusion: What does Life need next?
The way we imagine and create new products, services and businesses is changing faster and faster—if we want to stay relevant we need to change along with it.
Innovation strategies and business designs are all changing because breakthroughs in science and technology come faster and faster. They are all changing because of a greater need for diverse points of view at these uncertain times.
So how can businesses stay relevant and create what life needs next?
We strongly believe that a lot of training in data science, data analytics and data management are needed to provide companies and their employees with the capabilities to stay relevant. Consequently, we have developed training in these areas. If support is needed, contact me at hjschumacher59@gmail.com