This time last year, we touched on the hysteria surrounding Gen AI and the squabbles inside OpenAI that led to Sam Altman’s exit and reinstatement. More importantly, we provided our Top 10 forecasts in data and analytics that focused on the growing importance of data governance, data security, no-code self-service platforms, sustainability and valuable advances in AI technology.
Even if we say it ourselves, we kind of got it right. Looking at what happened in data and analytics during 2024, you’ll see a gradual evolution in all the areas we described. For example, awareness of data governance and ethics is greater than ever. The software market for data governance tools is expected to reach $11.8 billion worldwide in 2024 as companies seek to improve management, quality, security and compliance around their critical assets.
When it came to Gen AI, we didn’t pull any punches. We predicted that companies would be shocked when they embarked on their Gen AI journeys and uncovered their actual data. More than likely, it would neither provide the quantity nor quality they needed.
In the last 12 months, many companies have been allocating plenty of resources to cleaning tools to get their data into shape. The data-cleaning solutions market is expected to increase rapidly worldwide between now and 2028, reaching a market value of $5.8 billion.
What we think will continue to be key themes and trends in 2025
Okay, no more talking about the past—let’s get back to the future! This year, we’re focusing on six predictions about the areas that will dominate data and analytics. You’ll see they build on last year’s developments and introduce some new concepts you mightn’t be familiar with.
We’re writing this, of course, with the caveat that any sensible person would add when making predictions—it’s all based on current trends. Therefore, we’re discounting “black swans.” However, anyone looking at the odds would say what we’re proposing are undoubtedly good bets. So here goes:
AI Insights
AI insights are advanced analytical tools that use AI to extract valuable information from complex data sets. They go beyond traditional data analysis by offering real-time exploration of vast amounts of data, pattern recognition, predictive analytics, and automated recommendations. Plus, unlike conventional analysis, they don’t rely on a predefined hypothesis: AI allows the data to lead the study.
AI insights will increasingly empower businesses to make better strategic decisions. They’ll also help more companies enhance customer experiences and optimise operations. Businesses of all sizes will increasingly leverage the technology in the coming months. According to one recent survey of small businesses, 77% of respondents have already integrated AI into their daily operations, primarily in marketing and sales.
Data Democratisation
We included data democratisation in last year’s predictions, discussing how no-code self-service platforms will drive its continued adoption. In 2025, democratisation will continue with key developments in areas such as self-service analytics that help reduce the pressure on IT teams.
With AI-powered digital assistants like Microsoft 365 Copilot, non-technical employees can query and analyse data without technical support. Nearly 70% of the Fortune 500 now use Copilot for data analysis and visualisation. What’s clear is that over the next 12 months, companies will continue to empower frontline workers with tools for better and faster decision-making support.
Synthetic Data
Over 2025, synthetic data will become a significant part of the analytics landscape across most industries. As the name implies, synthetic data is artificially created and not based on real-world events. Algorithms produce the numbers to imitate actual data’s characteristics and statistical properties. The reasons for using synthetic data include improving the quality and diversity of information, reducing costs and time to value, enhancing decision-making, and enhancing security and compliance.
The adoption of synthetic data is already widespread, but we expect it to grow significantly this year. For healthcare, it could be as high as 50% to enhance disease protection models, and in retail, it could be 30% to support greater personalisation. According to Gartner, by 2026, 75% of businesses will use Gen AI to create synthetic customer data, up from less than 5% in 2023.
Furthermore, synthetic data will likely be used to simulate environments and identify new product development opportunities.
Artificial Datasets
Expect similar growth in usage for artificial datasets, a subset of synthetic data, during the coming year. Based on data augmentation, random number generation, and mock data, artificial datasets are more straightforward to generate than synthetic data. However, they offer similar benefits, and people often interchange their terms.
Improved Data Cataloguing
Technical advancements will drive significant changes in data cataloguing this year. Ensuring consistent, complete and up-to-date information within a catalogue remains a challenge. The various formats, security, cost management and scalability are also major hurdles. Yet, AI and ML are transforming cataloguing as we’ve traditionally known it.
We’ll increasingly see automated metadata extraction and generation using AI, automated data classification and tagging using ML algorithms and intelligent data profiling of data structures, just to name a few advantages. The critical point is that improved data cataloguing will also drive data democratisation, allowing personnel to find and use data more efficiently. It’ll bring a new level of effectiveness to data management for better decision-making business-wide.
Using Dark Data
Dark data is the information businesses collect, process and store as part of their operations but do not use. If Gartner is correct, more than 50% of a company’s data is considered dark. Failing to leverage dark data has significant downsides. The costs associated with storing the data are high, and the compliance and security risks are real. Then, of course, there are missed opportunities from all the insights the disregarded data contains.
With the advanced tools for data cleaning, integration, analytics and visualisation, more companies will start to extract value from their dark data over the year. The global market for data analytics is growing at 21.3% CAGR as more companies see how it could help increase revenues, provide a competitive advantage and support product development. So, maybe it’s time to fix your dark data strategy if you haven’t done so already.
Get in touch for support
How much your business can take advantage of these trends depends on its data and analytics maturity. That said, wherever you are on the maturity spectrum, there are major gains from developing your data and analytics strategy. Our customers aren’t all at the same stage of development in these areas, but each one is making progress with our support.
It’s abundantly clear that strategic data management has become essential. Delivering on your transformation goals without a solid data plan isn’t going to happen.
At Ipsos Jarmany, our expertise and experience help customers design, build, and develop their strategies to achieve data-driven success and improve their KPIs, enabling their organisations to thrive. If you’d like to have an honest conversation about how we can help you develop a data-driven approach to success, contact us today.
