Published on: January 6, 2025 / Update from: January 6, 2025 - Author: Konrad Wolfenstein
Companies' undiscovered treasure trove of data: How generative AI can uncover hidden values - Image: Xpert.Digital
Untapped data treasures: Why 80% of all company data remains unused
There is immeasurable wealth in the archives of digital information, a data treasure of gigantic proportions that remains largely untouched in most companies. It is estimated that around four out of five bits of data that companies hoard never see the light of day in the analytical world, even though they hold immense potential for artificial intelligence applications. This unused data not only represents a tempting opportunity, but also harbors latent risks, because sensitive information could lie in its depths, the existence and explosiveness of which no one is aware of.
The hidden potential of unstructured data
A significant portion of this untapped data wealth manifests itself in the form of unstructured data - a diverse collection of information that defies traditional categorization in database tables. Imagine the countless customer contracts lying dormant in digital archives, each one a mosaic of agreements, obligations and customer preferences. Think about the detailed product specifications that are the result of intensive development work and provide valuable insight into design decisions and technical intricacies. Not to forget the employee handbooks, which embody a company's consolidated knowledge and best practices.
But the world of unstructured data extends far beyond these examples. It includes the incessant stream of emails that characterize daily communications, documents of all kinds from internal reports to marketing materials, and the growing flood of images, audio and video files that capture moments, document processes and convey knowledge . This unstructured data is believed to represent up to 80 percent of the global data volume. They often contain a wealth of detail and complexity that simply does not find room in the orderly structures of conventional databases. They contain the nuances of human interaction, the subtleties of technical descriptions and the visual and acoustic evidence of reality.
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The challenges of usability
Despite this immense potential, many companies face significant difficulties in unlocking the full value of their unstructured data. The biggest hurdles are a lack of specialized know-how and the lack of adequate tools. There is often a lack of professionals who are able to apply the complex algorithms and techniques of machine learning to extract patterns and insights from this flood of data. At the same time, there is a lack of user-friendly and powerful software solutions that can facilitate and accelerate the analysis process.
These challenges are reflected in the hesitant acceptance of corresponding technologies. A significant majority of companies have not yet made significant investments in tools that would enable them to extract valuable information from their unstructured data. In fact, only about 16 percent of companies have purchased specific tools to accomplish this task. This suggests that most efforts to leverage unstructured data are still at a very early stage, often no more than pilot projects or the first tentative steps toward a more comprehensive data strategy. Many companies are still at the beginning of the journey to realizing and unlocking the true potential of their unstructured data. The complexity of the data, the need for specialized skills and the initial investment costs represent significant barriers to entry.
Generative AI as the key to unlocking data value
Amid these challenges, generative AI emerges as a promising key to unlocking the hidden value of unstructured data. Advances in artificial intelligence and machine learning are opening up new possibilities for automatically processing and structuring large amounts of unstructured information. Imagine intelligent forms that can extract relevant information from scanned documents or handwritten notes and transform it into structured data. Or consider automatically extracting detailed product information from images, which could significantly reduce manual effort.
AI-supported tools can not only help with structuring, but also act as attentive observers that point out anomalies in data quality or act as digital assistants to support those responsible for data in their various tasks. However, generative AI goes one step further. Not only can she analyze and structure data, but she can also create new content, summarize texts, develop ideas and propose innovative solutions based on the patterns and insights she has discovered from the unstructured data. For example, marketing teams could use generative AI to create personalized advertising campaigns based on preferences contained in emails and customer feedback. Product developers could use AI to generate new design ideas by analyzing information contained in product specifications and customer comments.
The ability of generative AI to recognize complex relationships and derive creative solutions from them makes it a powerful tool for companies that want to maximize the value of their unstructured data. It can help uncover hidden patterns, gain new insights and develop innovative products and services. Automating data processing and analysis tasks through AI also allows companies to save time and resources and focus on strategic initiatives.
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Necessary steps for successful data use
To unlock the immense potential of their untapped data for generative AI and other applications, companies must take proactive steps and fundamentally rethink their data management strategies.
1. Investment in modern and powerful data management systems
Investing in modern data management systems forms a solid basis for using data. This includes not only the implementation of powerful databases and data warehouses, but also the introduction of technologies that enable the collection, storage, processing and analysis of large amounts of data efficiently. Cloud-based solutions often offer a flexible and scalable infrastructure that meets growing requirements. The selection of the right technologies should be tailored to the specific needs of the company and take both structured and unstructured data into account.
2. Consider architectures such as data mesh
As data landscapes become increasingly complex, companies should consider adopting architectures such as Data Mesh. Data Mesh is a decentralized approach to data management in which departments take responsibility for their own data products. This enables greater agility and flexibility in data usage and promotes a data-driven culture across the organization. Decentralizing data responsibility can break down silos and improve collaboration between different teams.
3. Promote data literacy through training
Data is only valuable if employees have the necessary skills to use it effectively. Companies should therefore offer comprehensive data literacy training to ensure that their employees are able to make data-driven decisions. These training courses should not only be aimed at data analysts and IT experts, but should cover all areas of the company, from managers to employees in operational business. Teaching basic knowledge about data analysis, visualization and interpretation is crucial to establishing a data-driven culture.
4. Implement a scalable unstructured content platform
Processing and analyzing unstructured data requires special tools and technologies. Companies should invest in a scalable platform that allows them to integrate, process and analyze unstructured content from various sources. This platform should provide capabilities for text analysis, image recognition, audio and video analysis, and relevant information extraction. Platform scalability is critical to keeping up with the growing volume of unstructured data.
5. Establish clear guidelines for handling AI and data
The use of AI and the use of data raise important ethical and legal questions. Companies must establish clear policies for handling AI and data to ensure these technologies are used responsibly and in accordance with applicable laws and regulations. This includes aspects such as data protection, data security, transparency and fairness. The guidelines should be binding for all employees and should be regularly reviewed and adjusted to reflect advances in technology and changing social expectations.
From data chaos to competitive advantage: How companies can unlock their data treasures
By proactively adapting their data management strategies to the specific requirements of AI systems, companies can gain a decisive competitive advantage for the future. They can unlock the hidden value of their previously unused data, develop innovative products and services, optimize their business processes and make more informed decisions. Transforming from a company sitting on a treasure trove of data to one that actively uses this treasure requires a strategic vision, investments in technology and skills, and a corporate culture that recognizes and promotes data as a valuable asset. The era of generative AI offers a unique opportunity to unleash the potential of unstructured data in unimagined ways and to open up new value creation potential. Companies that seize this opportunity will be able to secure a sustainable advantage in an increasingly data-driven competitive environment. The journey to discover the hidden treasure of data has just begun.
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