{"id":44650,"date":"2023-12-13T12:48:51","date_gmt":"2023-12-13T12:48:51","guid":{"rendered":"https:\/\/www.elixirr.com\/en-us\/?p=44650"},"modified":"2025-11-10T15:49:32","modified_gmt":"2025-11-10T15:49:32","slug":"2024-trends-data","status":"publish","type":"post","link":"https:\/\/www.elixirr.com\/en-us\/2024-trends-data\/","title":{"rendered":"2024 Trends: Data"},"content":{"rendered":"\n

Heading into 2024, companies are considering how to best manage their data assets. Innovation will be driven with economics in mind, and budgets are expected to promote initiatives that prioritize automation and deliver tangible business results and process improvement. Across all industries, businesses will be evaluating their tech stack efficiency against cost expenditure to optimize processes and ways of working accordingly.  <\/strong> <\/p>\n\n\n\n

Our team, including our data experts at iOLAP and Responsum (now Elixirr Digital)<\/a>, aim to support business leaders in deriving concrete advantages from their data initiatives and enhancing operational efficiency. Principal Nick Larsen<\/a> outlines the key data trends for 2024 that business leaders should consider, as they prepare for the upcoming year, if they want to remain ahead.<\/p>\n\n\n\n

AI\/ML \u2013 robotic processing reality<\/h2>\n\n\n\n

Artificial intelligence (AI) and machine learning (ML) technologies have come a long way. From simple regression models used to predict and forecast the future, to the emergence of computer vision and image recognition for data categorization, the development of robust large language models (LLMS) and today’s generative AI <\/a>technologies, AI\/ML has rigorously pushed what’s possible. Over the last year, there\u2019s been increasing talk and interest in generative AI\u2019s novelty potential. However, the deployment and development of real-life generative AI solutions and application across businesses and industries is still in the infancy stage.  <\/p>\n\n\n\n

In the upcoming year, technology providers and business leaders can expect a dialled-in focus on realizing tangible business benefits from generative AI. The focus on real-life solutioning will be driven from two ends. Firstly, by technology providers such as Amazon, Microsoft, and Google, who have developed the infrastructure required to support generative AI expansion at scale, and secondly, by business leaders who are eager to innovate. In 2024, companies looking to derive meaningful business value from generative AI will increase the market demand for internal and external resources \u2013 those who have experience in identifying how to best target innovation areas \u2013and tailor generative AI solutions to support their business vision.  <\/p>\n\n\n\n

We have experience doing exactly that for our clients across data <\/a>and AI & ML<\/a> services \u2013 including developing models and platforms that our clients can quickly deploy into their business. For more on trends in AI and how we\u2019re helping leaders in this space today, connect with our experts here.<\/a><\/p>\n\n\n\n

Monolithic platform \u2013 distribution of costs<\/h2>\n\n\n\n

In what can now only be described as “the old days”, companies seeking to uplevel technological capabilities would have to upfront innovation and technological expansions with in-house infrastructure and resourcing, often taking on excess capacity on both fronts to account for planned scalability. The introduction of The Cloud disrupted the monolithic platform model by providing companies the ability to offload infrastructure responsibilities with serverless solutions, increase tech stack agility and flexibility by adopting microservice architectures, and reduce costs with pay-as-you-go computing fees. Today, the ways by which companies are managing serverless services are becoming increasingly sophisticated. <\/p>\n\n\n\n