Data basics are now a must have
Posted on 4 December, 2019
A new study by MHR Analytics Research reveals that most organisations believe data analytics, automation and AI will be essential for business survival in the coming years yet lack the necessary knowledge that underpins it.
The study aimed to explore the levels which organisations across all sectors are developing their data strategies as businesses get ready to enter a new decade that promises unprecedented digital acceleration.
Without the crucial component of a good data foundation, it is impossible to implement advanced analytics, automation or AI, the research concluded. Despite a widespread appetite for adopting these technologies, the study showed that a better understanding of data strategy basics, such as data hygiene, will be vital for companies to launch the data-driven projects they know they need to compete.
The findings included:
- More than half (55%), believe data analytics will be essential for business survival in the next ten years, 53% say automation will be essential, and 42% believe AI will be essential
- A fifth (21%) of UK companies plan to implement AI yet they do not have a data strategy to support it, suggesting a better understanding will be necessary
- Skills gaps are delaying AI adoption, with 40% reporting this as a barrier to advanced analytics
- Data science skills will increase in importance, with 43% of senior professionals saying they will need to learn data science or analytics skills to progress their role in the next five years
- 43% say their role will become more strategic as traditional tasks become automated, with 91% saying their department will become more efficient due to automation.
At Wilmington Millennium we have long talked about the importance of data hygiene as a solid foundation for data science. Algorithms are only as strong as the data upon which they are built and if the data is flawed, then so too is the model. This is why we have been working with data scientist to help them ensure that their data is clean and up to date as possible for example removing people that have died from the dataset so that bias can be reduced.
With unprecedented digital acceleration in the offing having the basics down pat will be more fundamental than ever.