5 Data Trends to Watch in 2023
At this time of year you may be feeling deluged by trend lists, especially the ones that give you 15 or 20 trends to digest and track. When I was assembling my list of the big data trends to watch in 2023, I wanted to target no more than five and have a sound theory behind each one.
Where I ended up was a core theme and trend, which made it easy to branch off into four related ideas. I’ve also added some strategic ideas that data leaders can consider in response to these trends. Based on conversations I’ve had with Chief Data Officers and data scientists this year the main idea came into focus quickly.
The Trend: Data as a Product
Open any news site these days and you’ll see coverage of companies like OpenAI and its conversational model ChatGPT or Prisma Labs and its image editing app Lensa. Both demonstrate how we have entered the era of data as a product, and why I chose this as the core trend for the foreseeable future. ChatGPT in particular is a huge leap beyond data products as a fun diversion. You can use it to build a marketing strategy framework, write social posts, or even script code to perform tasks like merging data sets. No surprise that it jumped to a million users in just five days.
Data Leader Strategy: Building true data products will require going further than making data-driven decisions. Data leaders must inspire a product development mindset on their teams. If you haven’t identified the value of your data – how you could turn it into a product or how you might attach an actual revenue number to its value – then you’re not really thinking of it as a product yet. Also remember that your data product might be an internal one, which could still deliver a lot of value.
The Trend: Cloud First
If you buy the core trend of data as a product, you’ll need a technology infrastructure that allows you to build those products and scale them up as quickly as possible. Today that means being cloud first. In addition, being able to switch out your infrastructure team and reskill or transition them into data engineers or AI developers is a smart move in a recessionary economy. Whatever the business need, the cloud provides a lot of operational flexibility without having to accumulate added costs.
Data Leader Strategy: Make sure you not only have a cloud migration strategy, but a smart one. A staggering percentage of data in our organizations has no value at all, so does it really need to be moved over to the cloud, or can we make sure that we’re moving and storing what has the highest value?
The Trend: Expansion of Roles.
In 2010 a Venn diagram about qualifications for data scientists circulated widely online. Back then you needed the skills of a unicorn – computer science, math, statistics, hacking, and communications, to name a few. What we’re seeing today is that each of those job functions is getting split into highly specific areas. Now we have machine learning operations engineers, data product owners, and AI ethicists. This is a clear sign of any maturing market: segmenting the functions of once-overwhelming jobs into more discrete roles because they are no longer scalable.
Data Leader Strategy: Start looking at which areas of your current roles you could automate – or at least automate portions of those roles and then transition those team members to areas where you really need help.
The Trend: Privacy and AI Trust.
My prediction here is that we’re going to see more lawsuits against AI models based on concerns about safety, discrimination, and privacy. This really stems from the US government, which came out with its AI Bill of Rights blueprint in October of 2022. I encourage every data leader to read it as the government begins to set up more policy and regulation for these models.
Privacy questions about AI are entering the public sphere already. The debate about Lensa started quickly. What is this company doing with the photos that I uploaded to be able to get this data product as an output? What data did you use to train this app, and who owns it? Where else is my data being used? AI is triggering more of a privacy conversation, which we haven’t seen in the past when it was less consumer focused.
Data Leader Strategy: A concern with privacy from a technology standpoint is we’re quite far behind in digital literacy as a society. As we upskill and reskill our digital literacy to understand how these machines work, we can be better informed individuals in terms of the questions we ask, how we vote, and the policies that we would want to see in place. Raising awareness in this area is key for data leaders.
A good starting point for this is companies implementing an AI ethics review committee or a privacy committee, because at the end of the day we want to be ahead of the curve in terms of regulation and already implementing what’s best for our consumers and users.
The Trend: Metaverse & Web3.
This data trend for 2023 is less directly related to the main theme, but is out on the horizon and therefore important to understand. I don’t see us all working in the Metaverse in 2023, or logging on to discover that the internet has magically transitioned over to Web3. Despite metaverse and crypto scandals in 2022, people know that there is value and interest. They’re just not quite sure how to implement it.
Data Leader Strategy: Data leaders and CDOs need to be more aware of what’s happening in Web3 because Web3 is all about the blockchain, and that’s a shareable database that anyone can edit with a distributed compliance system. As data professionals, it’s key to track what’s happening in this space. If not, someone in your organization eventually will adopt that technology for a use case, and then that will be a system of record (and data) that you need to manage in your tech stack.
Keep your eyes open
When I was ten years old I wrote a letter to my future self, so I’ve clearly loved predicting the future from an early age. As I think about the big data trends coming at us in 2023 the future seems to be approaching ever faster, so looking at every dimension of your data and the value it can bring your organization and the world at large should be a daily practice. Your organization will be all the better for it.