Editorial - DataIQ

Machine learning – focusing on code misses the big picture

According to Rangarajan Vasudevan, CEO of data strategy company The Data Team, machine learning has received an extensive amount of hype and media coverage in recent times. However, he feels it is important to point out that machine learning syste…

Marks and Spencer to train staff in data skills

Marks and Spencer is to train over 1,000 employees in digital skills through a partnership with digital skills training organisation Decoded, with the aim of creating the world’s first data academy in a retail organisation. It also reflects th…

“No ivory towers” found on OS map for data knowledge sharing

According to Caroline Bellamy, there is a lot to be gained from having a data centre of excellence within an organisation. But she has a problem with the name and behaviour it encourages. Bellamy is the first chief data officer at …

Reading data right – the case for data literacy

“This illustrates the need for greater data literacy globally – consumers should be able to understand data not as an abstract concept, but as something that relates to their lives and the decisions they make every day.” These were the words of Dr…

Get data skills up to standard with ‘aristocrats’ leading the way

According to a new report, there are four types of people when it comes to understanding of and willingness to work with data. The most skilled people in terms of ‘data literacy’ are data aristocrats. The data aristocrat has a high aptitude for un…

Leaders discussion: Mental models of an effective analytics team

Team dynamics have a big impact on the effectiveness of the analytics function. Selecting the right candidates and understanding existing practitioners can be a worthwhile exercise for an analytics leader. This article looks at three psychological models that have gained traction in this discipline.

Turning the data and analytics function into a trusted advisor

The most advanced level of CARBON maturity sees the majority of senior management decisions being made on a stable base of trusted analytics with an ongoing feedback loop. This is by no means easy to achieve, however. This guidance looks at what builds trusted advisor status and the specific implications for data and analytics practitioners.

DataIQ Leaders briefing: CDO v CIO – the battle for the boardroom

DataIQ Leaders advocates the presence of a chief data officer in organisations and that CDO is a board-level position. But that is not how every firm sees it, with a number appointing or moving their data officer into the CIO’s team. David Reed considers the arguments against this approach.

Knowledge management – Turning data and analytics into a contact sport

As data and anaytics teams build innovative, transformative solutions and processes, the role of knowledge management becomes ever more important. Rather than leaving the understanding of how those assets were created locked up in the minds of practitioners, it needs to be formalised, documented and shared. This whitepaper considers how to apply knowledge transfer in this domain.

Key factors in deciding where to place your data organisation

Data and analytics may already exist in your organisation as expert practitioners within different functions. But that is not the same as having a data and analytics function. When deciding to create this as a standalone unit, a critical issue to settle is where it should sit in the broader organisation. This article considers possible options based on DataIQ Leaders member experiences.

Build and future-proof your skills with DataIQ Leaders

If data and technology are creating what has been called the Fourth Industrial Revolution, then data and analytics functions (D&A) find themselves right at the heart of this transformation. This article maps the skills you need now and in 2020 against the DataIQ Leaders programme to help you find the resources to equip yourself.

Improving soft skills in the data and analytics function

This guidance whitepaper considers how organisations should map soft skills, support teams in developing them, incentivise improvements and measure these abilities from the top down. It is intended to help DataIQ Leaders members to improve their scores on these factors when undertaking a CARBON™ assessment.

Creating a hub for intelligent data at Deutsche Telekom

Sven Löffler, business development executive of big data and data-driven business at T-Systems, a subsidiary of Deutsche Telekom, oversaw the launch of the Telekom Data Intelligence Hub. The Telekom Data Intelligence Hub is a secure market…

Moving from data silos to data assets

With every new system adopted by an organisation, data proliferates. Without the right management and governance, these sources soon become silos. The result can be an incomplete view of the business and its customer base, as well as flawed processes and lost value. This guidance whitepaper offers insights into how to improve your CARBON capability around data management.

Twin hubs and weird hours – How to manage a global data team

The obvious difficulty posed by having data teams- based in different cities around the world is coordinating meetings and having face-to-face time. However, according to the former global lead of customer intelligence and data at a leading retail…

“It’s not always the weather” – Optimising KPI development and delivery

Business intelligence is often the entry point for data transformations. As such, it brings the data and analytics teams into direct contact with lines of business to refine, support and deliver key performance indicators. This guidance whitepaper offers insights into how to improve your CARBON capability around this business-critical area of activity.