Between record inflation and supply chain challenges to the sudden shift from rampant hiring to widespread layoffs, the last 12 months have proved to be a roller coaster for businesses. As a result, organizations struggle to determine where to focus their attention beyond just the bottom line.
Businesses can’t sit idly by waiting for the next disruption. They, instead, must take a closer look at where data can be used to their advantage to mitigate and navigate challenges that are sure to come in 2023.
AI and ML Take Over Menial Data Tasks
Many organizations are turning to artificial intelligence (AI) and machine learning (ML) to assist during this difficult period, in which businesses are expected to do more with less. While adoption is overall a positive development in applications used by many staff, the technology can be applied differently to create even more value. If AI is moved deeper into the data pipeline – before an application or dashboard has even been built – it will shift the time spent on data preparation to actual data analysis.
The current breakdown is far from ideal: a report by IDC shows that 82 percent of the time is dedicated to the search, preparation, and governance of data. That means that only 18 percent is being allocated to the actual analysis of data.
Data talent can better use their time, and organizations can better utilize their employees by using AI and ML to handle the more menial parts of data. By doing so, data talent will be empowered to focus on value creation through insights, improving their performance as well as the performance of the organization.
Derivative and Synthetic Provide Invaluable Insights
The world wasn’t prepared for COVID-19 in most ways. One data-related glaring gap was the lack of enough readily available real data on pandemics to prepare for such a crisis. This is precisely where synthetic data can become incredibly valuable. The benefits are quite significant: synthetic data allows organizations to better plan for future challenges in areas where real data comes up short. Healthcare organizations and financial services firms are among the highly regulated industries that could use synthetic data to their advantage.
While derivative data – –real data that’s been transformed, processed, aggregated, correlated, or operated – is still important, researchers at MIT, the MIT-IBM Watson AI Lab, and Boston University found that, in some circumstances, synthetically trained models perform better than models relying on real data. In other words, we may not need to experience it with real data to accurately predict and properly prepare for the next black swan event. What’s more, synthetic data may reduce the collection of personal customer data, allowing businesses to avoid nearly three quarters (70 percent) of the violation sanctions that weigh over them in today’s market.
X-Fabric Empowers Organizations to Act with Certainty
Research from EY shows that more than 93 percent of businesses intend to increase their investment in data and analytics, but they must remember to include governance in their planning. In addition to the California Consumer Privacy Act (CCPA), which regulates how consumer information can be collected, stored, and shared, the general sentiment around privacy has changed. A report by McKinsey shows that some consumers don’t trust digital services for that very reason. At the same time, the distribution, diversity, and dynamics of data may interfere with an organization’s ability to achieve a data-driven competitive edge. This becomes especially challenging in a fragmented world as data governance becomes even more complex.
Enterprises need to improve access to data and the real-time movement of information and advance data transformation between sources and systems. A growing number of businesses are achieving these goals and subsequently realizing the full power of data by turning to data control plane architecture – an X-fabric. Organizations that use an X-fabric data control plane – that is, multiple fabrics, including an application fabric, BI fabric, and algorithm fabric – will be better equipped to act with certainty while maintaining governance.
Doing What’s Necessary to Endure the Challenges Ahead
Disruption is now a permanent part of the business world. Whether caused by an innovative startup, a black swan event or even a simple mistake, organizations will flounder if they aren’t prepared. As enterprises make their 2023 preparations, they should take note of the trends that are set to shape the coming year.
AI and ML will allow enterprises to do more with less while empowering data talent to eliminate some of their most menial objectives and focus on higher-value tasks. While derivative data will continue to provide immense value, synthetic data will have its moment in the spotlight as organizations prepare for future crises. And with an X-fabric data control plane architecture, businesses will be better prepared to act with certainty in an uncertain world.
[Solutions Review’s Expert Insights Series is a collection of contributed articles written by industry experts in enterprise software categories. In this feature, Qlik Market Intelligence Lead Dan Sommer offers key 2023 data trends which he believes can help organizations limit future disruption.]