At the start of this year, we breathed a sigh of relief thinking that the unprecedented events of the previous two years were behind us. But as 2022 progressed, it became clear that change on a macro scale was here to stay, and we now find ourselves stuck in a perfect storm.
An economic recession is on the horizon, conflicts continue to impact global markets and organisations all over the world are looking at their bottom line, working out what would be a smart investment and why.
We’re already seeing the effect of this period of uncertainty on the technology landscape with venture capital (VC) funding declining, tech de-coupling happening, continued lack of access to data skills and more complex regulations coming into place.
With so much pressure to innovate it can be hard for decision-makers to know what to focus on.
However, what’s clear is that achieving decision accuracy and integrating siloed and distributed data sets to accurately see the big picture, in real time will be vital for the survival and future success of organisations.
From Qlik’s perspective, we have outlined five key trends that every data-driven business should act upon in 2023.
- AI will move deeper into the data pipeline: As economic uncertainty continues; many companies will see a pull back on investment and hiring. However, with the global skills shortage continuing to impact companies of all sizes, ensuring technologies such as artificial intelligence (AI) and machine learning (ML) are able to automate some of the more menial data preparation tasks will be crucial. By moving AI deeper into the data pipeline before an application or dashboard has even been built, we can finally start to shift the breakdown of time spent on data preparation versus data analytics. Right now, less than 20 percent of the time is spent analysing data, while just over 80 percent of the time is spent collectively on searching for, preparing, and governing the appropriate data. Moving AI deeper into the data pipeline would enable hard-to-come-by data talent to focus on value-add; cross-pollinating and generating new insights that weren’t possible before. That would be a far more productive use of their time.
- Invest more in derivative and synthetic data to prepare for unprecedented events: If the last few years have taught us anything, it’s the value of investing time and resources into risk prediction and management. Unfortunately, prior to Covid-19 there wasn’t enough real data on pandemics readily available to the average operation to prepare for such a crisis, and this is precisely where synthetic data plugs the gap. Research suggests that models trained on synthetic data can be more accurate than others; and it also eliminates some of the privacy, copyright, and ethical concerns associated with real-world data. Derivative data allows us to repurpose data for multiple needs and enables crucial scenario planning needed to prepare for future issues and crises.
- Be ready for natural language capabilities to rival humans: Many organisations have been using language AI in its basic form for some time now. Think about how often you’ve interacted with a customer support chatbot to resolve your issues with your bank or insurance provider. The popularity of this technology is not only set to grow at around 18 percent for the next few years; it will also evolve dramatically. There are several new models in development which are significantly more powerful than anything we use today. Where those will take us, we can only imagine but what we do know is that natural language capabilities will have huge implications for how we query information and how it’s interpreted and reported. We’ll find not only the data we’re looking for but also the data we hadn’t thought to ask about. That's why businesses need to capitalise on this.
- Mitigating supply chain disruption with real-time data: The aftershocks of Covid-19 and continued global conflicts are still compromising supply chains. Anyone who has attempted to buy a new car (a computer, or even something as basic as toilet paper) in the last couple of years knows how seriously supply chains have been impaired. Things show no sign of abating over the next few years and so there is a need to react quickly, or ideally “pre-act” to forecast supply chain issues before they occur. Having the power to analyse data in real time and in context is key to doing this. It’s no wonder that IDC predicts that by 2027 sixty percent of data capture and movement tech spending will be about enabling real-time simulation, optimisation, and recommendation capabilities.
- X fabric connects data governance as it becomes even more complex: Investment in data and analytics has dramatically accelerated thanks to the pandemic and will continue to do so with 93 percent of companies indicating that they plan to continue to increase budgets in these areas. However, rapidly shifting rules and regulations around privacy, as well as the distribution, diversity and dynamics of data hold back the ability of organisations to squeeze the best competitive edge out of data and analytics. This has become especially challenging in a fragmented world, as data governance becomes even more complex. Improving access, real-time movement and advanced transformation of data between sources and systems across the enterprise is crucial for organisations in order to realise the full power of data. This is why an architecture, an X-fabric not just for data, but also for applications, business intelligence (BI) dashboards and algorithms, enabled by catalogues and cloud data integration solutions is required. This is a critical component in the modern distributed environment for any organisation that wants to act with certainty.
The good news is that after the last few years, we’re better prepared to roll with the punches than ever before. As data and analytics professionals, we need to adjust to more fragmentation, with disparate data centres, disrupted supply chains, the consistent need for innovation, and hampered access to skilled labour.
In a world where crisis has become a constant, calibrating for it becomes a core competence – so we can react at the moment and anticipate what’s coming next.
