How IT Leaders Leverage Unstructured Data

Data-driven organizations are accustomed to using structured data. This type of data is well-defined, organized, stored in a tabular form, and typically managed in a relational database management system (RDBMS). The data is predefined and formatted to fit a set structure. A vast range of tools have been developed to optimize this type of data, which includes customer names, sales data, and transaction dates. The data is easily searchable by programming languages and data analytics tools, unlike unstructured data.

Unstructured data is different.  It does not have a predefined data model or structure, making it more challenging to organize, process, and analyze using traditional databases or structured data formats. Unstructured data lacks a specific schema or format, and it can take many forms, including text, images, videos, audio recordings, social media posts, and more.  

Let’s explore how IT leaders can leverage unstructured data to gain a better business advantage. 

Automate Workflows for Unstructured Data

The majority of data—between 80% and 90%, according to some estimates, is unstructured. This means the data represents a huge treasure trove of value to businesses that can leverage it and use it effectively. 

Bringing automated processes to unstructured data can help ensure the data is properly ingested and stored in a way that makes it accessible and usable across the enterprise. Automating processes improves efficiency, yet automation is oftentimes complex due to the data’s variability, size, and lack of a standard format. At the same time, organizations that can successfully automate unstructured data can unlock insights faster to drive decision-making. 

According to TDWI, “Automating workflows to curate and deliver data to cloud-native analytics tools will help IT organizations efficiently leverage massive stores of unstructured data while reducing the manual effort required for data curation by data analysts and researchers. Data workflow automation is becoming a new requirement of unstructured data management platforms.” 

IT leaders who implement the tools and technologies to harness unstructured data and make it available to analysts and business users can realize a variety of benefits such as: 

• Extracting information from texts to better understand customer needs, customer sentiments, and market trends. 
• Reviewing social media and other unstructured data to understand customer sentiment, preferences and behaviors, then delivering personalized recommendations for products, services, or content. 
• Analyzing text in documents such as legal contracts to ensure compliance. 
• Performing analysis on images for use cases spanning medical imaging diagnosis to quality control. 
• Identifying positive and negative customer reviews to understand how customers view a brand and to inform marketing strategies. 
• Reviewing unstructured data sources, including emails, text data, and transaction records to help detect fraud. 
• Integrating unstructured data with structured customer data to provide a complete view of customers, which can be used to personalize campaigns, improve customer service, and enhance customer experiences. 

Using Unstructured Data for AI

Organizations across all industries are looking to implement Artificial Intelligence (AI) or Generative AI use cases. These use cases require data—often large volumes of data—and that can include unstructured data. 

Fast Company writes that “unstructured data is the fuel needed for AI, yet most organizations aren’t using it well. One reason for this is that unstructured data is difficult to find, search across, and move, due to its size and distribution across hybrid cloud environments.” 

Making all data readily available can support a diverse range of use cases, including those involving AI. For example, chatbots can analyze unstructured data to route customer questions to the appropriate source for an answer. 

In addition, unstructured data, including streaming data from social media posts, news articles, sensor data, and other sources, can enable new possibilities for AI and machine learning. These possibilities include enabling AI to understand context and quickly analyze large data sets or volumes of text to identify relationships or summarize the information. 

Integrate Data on an Easy-to-Use Platform

Managing and leveraging unstructured data allows organizations to gain deeper, richer insights into all aspects of the business. Likewise, implementing a data management strategy that includes unstructured data gives IT visibility into where the data is stored, which team owns the data, the costs to store it, and other pertinent information. 

The ability to leverage alternative data, such as unstructured data, helps businesses make more informed decisions, identify changing market conditions sooner, and reach business objectives faster. Accessing unstructured data can advance priorities that may not be readily apparent. For instance, it can help with environmental, social, and governance (ESG) initiatives by enhancing transparency, assisting with ESG reporting and disclosure, and benchmarking ESG performance against industry leaders. 

The unified Actian platform makes data easy across cloud, on-premises, and hybrid environments to empower business users and drive data-intensive applications. It also supports businesses’ confidence in their data, improves data quality, assists in lowering costs, and enables better decision-making across the business. 

The Actian Data Platform is unique in its ability to collect, manage, and analyze data in real-time with its transactional database, data integration, data quality, and data warehouse capabilities in one easy-to-use platform. Try it for free to see how it can benefit your business. 

About Emma McGrattan

Emma McGrattan is the CTO at Actian leading global research and development. She is a recognized authority in data management and analytics technologies and holds multiple patents. Emma has over two decades of experience leading a global software development organization focused on innovation in high-performance analytics, data management, integration, and application development technologies. Prior to joining Actian, Emma was Vice President for Ingres at Computer Associates. Educated in Ireland, Emma holds a Bachelor of Electrical Engineering degree from Dublin City University.