Organisations struggling to deliver on data strategy
Just 13% of organisations excel at delivering on their data strategy, according to new research from MIT Technology Review and Databricks.
A survey of 351 senior data officers worldwide found that the select few data “high achievers” are delivering measurable results across the enterprise.
The report attributes their success to paying attention to the foundations of sound data management and architecture, which enable them to “democratise” data and derive value from machine learning.
By contrast, over half of respondents indicate they are struggling to scale machine learning use cases, the report found.
Scaling machine learning use cases is exceedingly complex for many organisations, with 55% of respondents suggesting that the largest challenge is the lack of a central place to store and discover machine learning models.
Interviewees indicated that their organisations’ top data priorities over the next two years fall into three areas — improving data management, enhancing data analytics and machine learning, and expanding the use of all types of enterprise data.
“Managing data is highly complex and can be a real challenge for organisations. But creating the right architecture is the first step in a huge business transformation,” commented journalist Francesca Fanshawe, editor of the report.
“There are many models an enterprise can adopt, but ultimately the aim should be to create a data architecture that’s simple, flexible, and well-governed.”
Is the Australian tech skills gap a myth?
As Australia navigates this shift towards a skills-based economy, addressing the learning gap...
How 'pre-mortem' analysis can support successful IT deployments
As IT projects become more complex, the adoption of pre-mortem analysis should be a standard...
The key to navigating the data privacy dilemma
Feeding personal and sensitive consumer data into AI models presents a privacy challenge.