The four priorities of data leaders

Based on our latest study, we explore the data initiatives that data driven organizations are investing in this year. We will delve into four main areas: the AI surge, the need for scalability, the analytics evolution, and the increasing focus on data governance.
Last updated
May 2, 2024

This article was guest authored by Jérémy Corbet, Founder at Hello World Recruitment


The data scene and more broadly the tech scene have been undergoing a shake-up in 2023. Amidst economic uncertainties and layoffs, companies are navigating through a rapidly evolving and ambiguous landscape. Despite the tense context, there is also some exciting news: the tech disruption brought by generative AI has created unprecedented opportunities for companies to innovate. 

In this context, what are the driving forces of the data industry this year? Now that AI is no longer limited to data connoisseurs, do CEOs make it a priority to invest in it? Beyond the AI surge, what are the other trends driving companies’ data strategies this year?

Based on my latest study, I explore the data initiatives that data driven organizations are investing in this year. We will delve into four main areas: the AI surge, the need for scalability, the analytics evolution, and the increasing focus on data governance.

Riding the AI Wave

Let’s address the elephant in the room. No matter where you look online, there’s no escaping news of the dawn of AI technologies. Generative AI is the most disrupting trend in the data industry this year. 

ChatGPT - OpenAI’s chatbot - is estimated to have reached 100 million monthly active users in January, only two months after launching. In comparison, it took 4.5 years for Facebook to reach the same number of active users. 

With impressive advancements in large language models (LLM), AI-based services have now opened Pandora’s box for data teams and their organizations. ChatGPT is just one example of the vast range of AI services available to companies. From natural language processing applications to computer vision and predictive analytics, AI services offer an array of solutions for teams to automate processes, gain valuable insights from data, and enhance decision-making (see Futurepedia or toolsai to access the myriad of AI tools). Their out-of-the-box accessibility through API connection enables companies to leverage LLMs at a low cost, swiftly. They no longer need to invest millions of dollars to develop their own LLM. They can almost just plug and play.

Addressing Problems of Scale

AI is not the only tech attracting interest this year. Organizations have been investing in the scalability of their data functions and are continuing to do so through hiring and future-proofing processes. From my latest study, data leaders recognized the importance of building and deploying large scale models to unlock the true value of their data assets. 

As datasets grow larger and more complex, businesses need robust infrastructure and techniques to process and analyze this data efficiently. Consequently, there is a significant focus on cloud initiatives, with 43% of data executives planning to focus on building or growing their cloud capability. 

On top of that, there is a technological shift driving scalability. Now more than ever, scalability is facilitated by a wide range of modern data stack tools that bring speed and quality to the data process, while requiring less manipulation from engineering teams. Tools like Fivetran allow reliable and clean data extraction with no-code. Snowflake stores infinite amounts of data and makes it available to a wide range of data applications, and dbt makes the process of transforming data simpler and faster.

Analytics as a Lifeboat in Uncertain Times

In 2023, data analytics continues to play a foundational part in helping companies navigate uncertain times. 

Firstly, analytics enables monitoring operational performance. By leveraging data analytics, businesses can identify inefficiencies, streamline processes, and allocate resources effectively. Real-time monitoring, predictive analytics, and anomaly detection enable proactive problem-solving, minimizing downtime, and enhancing overall productivity.

Secondly, digital analytics which looks at the optimization of online presence and customer experiences is a top priority for data driven organizations. E-commerce and digital channels remain a long-term priority for companies to compete and gain market share. The current tech changes in this field, such as the sunsetting of Google’s Universal Analytics, bring more work to digital analytics teams this year.

Lastly, the data leaders I interviewed don’t foresee 2023 to be the year of visualization powered by virtual reality, however, product advancements focused on user experience, adoption and storytelling are expected this year.  This comes as a natural evolution of the tools to address the users’ needs to derive insights effectively, and empowering users through storytelling.

Data Governance

Whether they are at the beginning of their journey, or are scaling their data infrastructure, data governance remains foundational for a vast number of leaders and is growing in importance for many companies. 

As a knock-on effect of the AI shift, AI governance is a new preoccupation of many data leaders.As companies begin to rely on AI services, they must be even more diligent about managing the access of sensitive data. In fact, some companies like Amazon have forbidden their employees to use ChatGPT. Beyond internal governance, it’s also a question of how they handle their customers’ and stakeholders’ data through AI services. 

Another interesting trend this year is data sharing. Indeed, companies are willing to monetize their data assets by building data products they can share (and sell) to other companies. In that context, an interesting solution coming into play this year has been data contracts. They provide a framework for data producers and consumers to align on a shared understanding of how data is utilized and drive value. For more on this topic, I recommend following Chad Sanderson’s posts on LinkedIn.

Key takeaways

In 2023, data leaders are taking onboard the AI revolution as it becomes more accessible and understood by decision makers. Beyond AI, they are continuing investment in long-term data capabilities such as cloud migration, which supports the growing volume and complexity of data; analytics, which helps companies navigate the ambiguous economic landscape; and data governance, which grows in importance due to the evolving utilization of data and regulatory changes.

More than a revolution, 2023 sees data teams focusing on their long-term data initiatives while incorporating modern data tools to drive fast and reliable value from their data assets.

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