Tech
How to build a data dream team | Computer Weekly
Data is critically important to almost any business – it’s the lifeblood that makes an organisation function. But managing, leveraging and realising the commercial advantage of data is also hard.
If fully leveraging data is difficult enough, the bar is only getting higher – with AI changing the game. Traditionally, approaches to data have been through a systems-focused lens, ensuring that the systems a business operates on have the requisite data flowing through them. But now, the task has moved to ensuring that data is AI-ready. This means that it needs to be properly tagged so that AI applications know what the information is, where it came from and how it has been used before. This enables the AI to understand what the data signifies without having to interpret it for itself. Without this, the AI might guess incorrectly, leading to mistakes, unintended consequences and even hallucinations.
In the AI age, robust data governance has bever been more critical. Organisations need clear policies, rigorous standards and well-defined processes to ensure data quality. Equally important is the systematic management of data throughout its lifecycle, including consistent curation, secure storage and management so that data remains accurate, reliable and fit for advanced analytical and AI applications.
Building the data team
All of this means that having the right data team in place is imperative. However, it has also led to increased competition in the market for professionals with advanced data skills and experience. Clarity over the team and roles you are trying to build is therefore essential. So, what does a ‘data dream team’ look like?
In our experience, both from the recruitment side servicing the market and as a data practitioner building and running a team, you have to get the data team right, along with the necessary data processes and structures, before you can even think about pushing far into AI.
Several roles are critical. Firstly, data engineers are fundamental because they set the processes to collect, manage and store the data for the business to use; they lay the foundations. Data architects ensure that the data flows and connections between systems align to business needs, and can be properly scaled and supported. Then, skilled data scientists and data analysts use the data to draw out actionable insights including applying AI techniques and potentially starting the evolution towards machine learning and automation stages. BI (business intelligence) analysts also play an important role by bringing a business/sectoral lens to what the data is showing. As a business becomes more mature with both data and AI, the need develops for AI/ML engineers to design intelligent systems using the data flows created.
Another key emerging role is what one might describe as a ‘data translator’ or perhaps a ‘data solutions engineer’. These individuals form the link between the data team and the business, acting as a conduit to help translate the insights from the data into business actions that can be taken. This demands both technical skills and knowledge, and business acumen and understanding. It’s a role that often gets overlooked, although more businesses seem to be realising that it’s a vital part of the puzzle.
It is worth noting that these roles are all in high demand, and can be hard to fill. As a result, data-related salaries have jumped significantly in the last 18 months or so. Whereas many tech role salaries have only risen at or around the rate of inflation, some data roles have put on perhaps 15-20%. A good analyst may command somewhere in the region of £70-90k, engineers and scientists perhaps £80-110k, while an accomplished data translator/solutions engineer could attract £120k or more.
As can be seen from the above, a good data approach is about having a multi-discipline team comprised of different roles, working closely together. Therefore, it’s by no means simply about finding people with the right technical skills – cultural fit within the team and the business should also be key considerations. As so often the case, it’s as much about the people as it is about the technology. Businesses shouldn’t expect to assemble the right data team overnight. It’s an organic and incremental process that can take perhaps 12-18 months to fully reach fruition.
The leadership question
Then there is the issue of leadership: who should take executive responsibility for data and the data team? Most businesses have a Chief Data Officer or equivalent (Director of Data or Head of Data etc) – the key question is where this individual sits in the management hierarchy. In an ideal world, the head of data would be on a par with the heads of technology and product, and have a seat in the boardroom. In practice, this is often still not the case – but is something that we expect will change in the coming years, especially with the continuing march of AI. There are other variations. For example, in companies undertaking large-scale implementations of AI, we sometimes see a Chief Data Officer working alongside a Chief AI Officer, but in some businesses the two roles are merged into one. There are no ‘right’ answers here – it really is down to the individual dynamics within an organisation.
Finally, it is also crucial to realise that data is not only a matter for the data team: everyone is a data user. Therefore, data literacy across the business must be on the agenda, with training and resources available to help everyone increase their data competency and confidence. Only in this way will you fully realise the benefits of all the work you have put in to make high quality, granular and relevant data flow around the organisation, feeding business decision-making and unlocking commercial returns.
Jack Capel is UK south director of Harvey Nash. Adam Asprey is director of Data at Maximus UK.
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Joe Gebbia, cofounder of Airbnb and the US Chief Design Officer appointed by Trump, was spotted in San Francisco today using a mysterious metallic device. In a social media post on X viewed over 500,000 times, a man who looks like Gebbia sits with an espresso at a coffee shop. He’s wearing metallic buds that bisect his ears, with a matching clamshell-shaped disc in front of him on the counter.
After the video was posted Monday morning, social media users were quick to suggest that this could be some kind of prototype from OpenAI’s upcoming line of hardware devices designed in partnership with famed Apple designer Jony Ive. An OpenAI spokesperson declined to comment on the potential Gebbia video after WIRED reached out. Gebbia also did not respond to a request for comment.
The device Gebbia appears to be wearing looks quite similar to the hardware seen in a fake OpenAI ad that was widely circulated on Reddit and social media in February. That video from last month seemingly showed Pillion actor Alexander Skarsgård interacting with an AI device that had a similar-looking pair of earbuds and a circular disc. At the time, OpenAI denounced the widely seen video as not real. “Fake news,” wrote OpenAI President Greg Brockman at the time, responding to a social media post.
The earbuds seen in the video of Gebbia also look quite similar in shape to the Huawei FreeClip 2, a pair of open earbuds released earlier this year. However, the clamshell seen on the coffee counter next to Gebbia is different from Huawei’s most recent headphone case. It would also be quite surprising if a government official were seen using Huawei tech, considering the Chinese company is effectively banned from selling its phones in the US due to security concerns.
WIRED’s audio experts say he’s most likely wearing open earbuds, as Gebbia’s pair share some similarities with Soundcore’s AeroClips or Sony’s LinkBuds Clip, though the cases for those buds don’t match what’s on the table in front of Gebbia. WIRED also ran the photo and video through software that attempts to identify AI-generated outputs and other deepfakes. The detection software, from a company called Hive, says the odds are low that this imagery of Gebbia was generated by AI. Still, AI detectors are not always reliable and can include false outputs. It’s possible that the entire post could be a synthetic hoax.
Could this be some kind of soft launch teaser for OpenAI’s hardware? The timing of this trickle out would make sense, since the company may ship devices to consumers sometime early in 2027. Still, OpenAI denied any involvement with the previous pseudo-ad for the metallic AI hardware, with its shiny earbuds and matching disc.
“There are Chinese components as well—we are totally open about it—but the key is that as we compile the software ourselves and install it in Finland, we protect the integrity of the product,” Pienimäki says.
What makes Sailfish OS unique over competitors like GrapheneOS or e/OS is that it’s not based on the Android Open Source Project, but Linux. That means it has no ties to Google—no need for the company to “deGoogle” the software; meaning there’s a greater sense of sovereignty over the software (and now the hardware). Still, it’s able to run Android apps, though the implementation isn’t perfect. Another common criticism is that it’s not as secure as options like GrapheneOS, where every app is sandboxed.
There’s a good chance some Android apps on Sailfish OS will run into issues, which is why in the startup wizard, the phone will ask if you want to install services like MicroG—open source software that can run Google services on devices that don’t have the Google Play Store, making it an easier on-ramp for folks coming from traditional smartphones without a technical background. You don’t even need to create a Sailfish OS account to use the Jolla Phone.
Jolla’s effort is hardly the first to push the anti-Big Tech narrative. A wave of other hardware and software companies offer a “deGoogled” experience, whether that’s Murena from France and its e/OS privacy-friendly operating system, or the Canadian GrapheneOS, which just announced a partnership with Motorola. At CES earlier this year, the Swiss company Punkt also teamed up with ApostrophyOS to deploy its software on the new MC03 smartphone. Jolla is following a broader European trend of reducing reliance on US companies, like how French officials ditched Zoom for French-made video conference software earlier this year.
The Phone
A common problem with these niche smartphones is that they inevitably end up costing a lot of money for the specs. Take the Light Phone III, for example, a fairly low-tech anti-smartphone that doesn’t enjoy the benefits of economies of scale, resulting in an outlandish $699 price. The Jolla Phone is in a similar boat, though the specs-to-value ratio is a little more respectable.
It’s powered by a midrange MediaTek Dimensity 7100 5G chip with 8 GB of RAM, 256 GB of storage, plus a microSD card slot and dual-SIM tray. There’s a 6.36-inch 1080p AMOLED screen, the two main cameras, and a 32-megapixel selfie shooter. The 5,500-mAh battery cell is fairly large considering the phone’s size, though the phone’s connectivity is a little dated, stuck with Wi-Fi 6 and Bluetooth 5.4.
Uniquely, the Jolla Phone brings back “The Other Half” functional rear covers from the original. These swappable back covers have pogo pins that interface with the phone, allowing people to create unique accessories like a second display on the back of the phone or even a keyboard attachment. There’s an Innovation Program where the community can cocreate functional covers together and 3D print them. And yes, a removable rear cover means the Jolla Phone’s battery is user-replaceable.
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L.L.Bean Promo Codes and Coupons: Up to 75% Off
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