Andrew Ahn

The Hidden Perils of Unstructured Data in Established Organizations

Established organizations, those that have been around for decades or even centuries, often face unique challenges when it comes to data management (Manyika et al., 2011). One such challenge is the prevalence of unstructured data, which can pose significant dangers to the organization if not properly addressed (Gantz & Reinsel, 2012). In this blog post, we will explore the risks associated with unstructured data and suggest strategies for managing and mitigating these dangers.

What is Unstructured Data?

Unstructured data refers to information that lacks a predefined format or structure, making it difficult to organize, analyze, and interpret (Gantz & Reinsel, 2012). These can be emails, documents, images, audio files, and videos. These can often accumulate over time, creating a complex web of information that can be challenging to navigate and manage (Manyika et al., 2011).

The dangers of unstructured data in established organizations encompass various aspects. Inefficient data management arises from the lack of structure in unstructured data, leading to lost productivity and increased costs as employees spend excessive time searching for and organizing information (Manyika et al., 2011). Inadequate data governance presents challenges due to the difficulty in maintaining unstructured data and increased risk of data breaches (O’Neil, 2018). 

Hindered decision-making occurs when organizations struggle to effectively analyze and interpret unstructured data, potentially leading to misguided decisions or missed opportunities for growth and innovation (Chen et al., 2012). Additionally, security risks are prevalent when sensitive information within unstructured data is not adequately protected, exposing the organization to data breaches (Vormetric, 2016).

Strategies for Managing Unstructured Data in Established Organizations

Developing a comprehensive data strategy is essential for established organizations aiming to effectively manage unstructured data (Loshin, 2013). This should outline the organization’s goals and objectives related to data management while establishing guidelines for data governance, storage, and analysis.

 Implementing data governance policies can ensure consistent management and maintenance of unstructured data, including the development of data classification and retention policies and assigning data stewardship responsibilities to specific individuals or teams (O’Neil, 2018). 

Leveraging advanced technologies, such as artificial intelligence (AI) and machine learning, can help manage unstructured data by automating analysis and insight extraction processes. (Chen et al., 2012). Investing in data integration and analytics tools enables established organizations to make sense of their unstructured data (Halevy et al., 2005), driving better business decisions. 

Embracing data strategies will ensure that established organizations not only overcome the challenges posed by unstructured data but also unlock its potential value. By harnessing the power of unstructured data, these organizations can drive innovation, improve decision-making, and maintain a competitive edge in an increasingly data-driven world (Manyika et al., 2011).


Chen, H., Chiang, R. H., & Storey, V. C. (2012). Business Intelligence and Analytics: From Big Data to Big Impact. MIS Quarterly, 36(4), 1165-1188.

Gantz, J., & Reinsel, D. (2012). The Digital Universe in 2020: Big Data, Bigger Digital Shadows, and Biggest Growth in the Far East. IDC iView: IDC Analyze the Future, 2007.

Halevy, A., Franklin, M. J., & Maier, D. (2005). Principles of dataspace systems. ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems (PODS), 1-9.

Loshin, D. (2013). Big Data Analytics: From Strategic Planning to Enterprise Integration with Tools, Techniques, NoSQL, and Graph. Morgan Kaufmann.

Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., & Byers, A. H. (2011). Big Data: The Next Frontier for Innovation, Competition, and Productivity. McKinsey Global Institute.

O’Neil, C. (2018). Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. Broadway Books.

Vormetric (2016). 2016 Vormetric Data Threat Report. Vormetric Data Security.