Clarity is the key to successful data strategies
Data strategies are most successful when complemented by clear objectives, but the hard part is ensuring clarity.
Skills shortage and technology should not be a barrier to entry to become a data-driven business
There must be investment in technology and tools to become a data-driven business, but tight budgets and a lack of technical expertise should not stop organisations from starting their data journey.
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DataIQ DEI Working Group – Initial challenges, finding allies and assessing impacts
DataIQ has set up a DEI working group and Manraj Othi, lead decision scientist at Starbucks, took the time to chat with our editor to discuss why DEI is important and his experiences.
The curious incident of the CDOs that didn’t bark
David Reed, DataIQ’s chief knowledge officer and evangelist, provides his thoughts on what can be done to re-bolster the status of data in organisations.
Innovation: The new agenda for data
The explosion of interest in generative AI during 2023 has emphasised an important fact – that the road to innovation goes through the data office.
Leveraging data within an AI strategy
As AI continues to grip the business world and open more doors than ever before, it is pivotal to have data on a pedestal within an AI strategy to drive decisions and inform stakeholders.
Unlocking success with a data vision: Is your entire organisation on board?
We have asked those who have made it into the DataIQ 100 to share their views and experiences regarding setting a vision for data and the scope of those visions.
DataIQ Awards 2023 Book of the Night
The standard has been extremely high and the competition fierce for the 2023 DataIQ Awards – the data industry’s most prestigious awards. Read about each organisation, team and individual that has been crowned a 2023 DataIQ Awards winner.
Future-Proofing Data Strategy
Explore the role of data apprenticeships in empowering CDOs.
Newspapers, radio and television – An insight into the impact of generative AI on media businesses
With generative AI paving the way for a new era of data, businesses are rapidly seeking ways to incorporate tools into their operations, DataIQ member News UK delves into their approach.
CDO Challenges – Data literacy means making better decisions
Business leaders are in a race against competitors to make the best decisions possible for their objectives and it is up to CDOs and data to guide them.
Data leadership unlocked: The must-have skills for success
We have asked those who have made it into the Future leaders list to share their views on what they believe are the most important must-have skills to achieve success as a data professional.
How to address inevitable data quality issues
Much like death and taxes, issues with data quality are a part of life for data practitioners – but there are steps to be taken to reduce any impact poor quality data may have on a business.
ChatGPT – Is English the final word?
Are tools such as ChatGPT cutting non-English languages out of the AI revolution? As these tools are currently only designed to work in English, do we risk alienating swathes of the global population?
Understanding organisational literacy rates
Data literacy is a challenge faced by all data teams, but to improve the rates and spread of data literacy, CDOs must understand how data literacy looks in different departments.
CDO Challenges – The rise of AI for data teams and being ready for the first step
It can be very easy for CDOs to be pushed into adopting AI tools because of excited decision makers, but CDOs need to ensure they have thought about how AI can successfully be implemented.
How well do you (need to) know your models? – A DataIQ member report
ML and AI tools have exploded in use for data organisations, but what more can be done to improve quality, compliance and efficiency with the models? DataIQ member Robert Bates, head of decision sciences, Currys, provides expert insight in this report.
How well do you (need to) know your models?
Over the past five years there has been a massive growth within retailers looking to use Machine Learning (ML) and Artificial Intelligence (AI) to improve performance, simplify the customer journey and increase innovation. But should we always trust the algorithms, and are they even required?
How to form a data vision
As a data leader it is imperative to create a data vision that can be demonstrated to decision makers for short and long-term projects, but how can one be formed?