Unstructured Data: A Complete Guide

To reduce costs, remove data redundancy and secure sensitive data.

  • Type: Blog
  • Date: 28/04/2023
  • Author: Ohalo
  • Tags: Unstructured Data, Data Governance, data discovery, Data Management, Data Quality

90% of enterprise data is defined as unstructured data. Moreover, this unstructured data is increasing at the rate of 55% to 65% year on year. But what is unstructured data, and how does it add value to your business? Here is a detailed overview of what qualifies as unstructured data.

Before we begin, let us understand the various types of data commonly found in an enterprise. Data exists in two forms — structured and unstructured. Structured data refers to organized and easy-to-analyze data set in a preset model or schema, such as data in a spreadsheet or database. On the contrary, unstructured data refers to data that lacks a definite structure, is unorganized, and is not set in a predefined manner, making it challenging to analyze using traditional methods.

Characteristics of Unstructured Data

Unstructured data is rapidly growing and is often more challenging to manage. Here are some key features that distinguish unstructured data:

  • Does not fit into spreadsheets
  • Lacks a predefined format or structure
  • Does not follow any preset rules or logic
  • Difficult to find and analyze

Common Unstructured Data Sources

Files: PDFs, presentations, and other rich media records are common unstructured data sources that often contain business critical or sensitive information, making their proper management and protection crucial for organizations.

Emails: The presence of free-form text, multimedia attachments, and metadata in emails makes them difficult to classify and interpret. Additionally, the sheer volume of emails makes managing it a significant challenge for organizations.

Images: Yet another rich source of unstructured data are images. These include product images, marketing material, and user-generated content such as photos and memes.

Video and Audio Recordings: Videos such as video resumes and audio recordings of customer care interactions, are prime examples of unstructured data that can contain sensitive information.

Social Media: Digital platforms like Facebook, Twitter, and Instagram generate large amounts of unstructured data in the form of posts, comments, likes, and shares.

Unstructured Data Benefits For Businesses

An enterprises' unstructured data may contain a wealth of information that can provide unique insights into customer behavior, market trends, and other factors that can impact a business's success, including:

  • Improved Customer Insights: Unstructured data provides information, such as customer preferences, behaviors, and opinions to improve customer segmentation, develop targeted marketing campaigns, and ultimately curate personalized customer experiences.
  • Enhanced Product Development: By identifying emerging industry trends and gaps in the market, enterprises can gain a competitive edge over their rivals by developing new products that meet changing demands.
  • Heighten Operational Efficiency: Enterprises can identify and explore roadblocks in their data management processes. For example, analyzing email attachments can help businesses identify common customer issues and develop solutions to address them. This can assist in the establishment of efficient workflows, resulting in increased operational efficiency.

In the following section, we will discuss why you must manage enterprise-wide unstructured data.

Critical Role of Unstructured Data Management

Simply sitting on piles of data without proper management and protection can pose significant risks, like:

  • Security Risks: If the data is not properly secured, it can be vulnerable to theft, hacking, or other forms of unauthorized access. This can result in data breaches, which can compromise sensitive information such as customer data, financial information, and intellectual property.
  • Compliance Risks: Many industries are subject to data management and privacy regulations, such as the General Data Protection Regulation (GDPR) or the Health Insurance Portability and Accountability Act (HIPAA). Failure to comply with these regulations can result in legal and financial penalties.
  • Reputational Risks: Data breaches or other data-related incidents can damage a company's reputation and erode customer trust. This can lead to a loss of business and revenue.
  • High storage costs: As the amount of unstructured data continues to grow, businesses must consider the high costs associated with storing and managing this type of data.

To effectively manage data, defining the objective and scope is crucial. By answering key questions related to the volume, location, content, and more, organizations can gain a better understanding of their data and develop an effective data management plan.

Identifying the Scope and Objective

  • What is the volume of data?
  • Where are the data files located?
  • What information do these data files contain?
  • Who has access to the files?
  • How old is the data?
  • How much does it cost to store the data?

However, the question remains, how and where to start? The following section will outline practical steps you can take to address these questions and ensure the proper management and protection of enterprise-wide unstructured data.

Best Practices for Handling Unstructured Data?

Automate Data Discovery: Data discovery helps you understand the metadata related to your data. By analyzing metadata such as location, format, ownership, and usage, you can gain valuable insights into the context, relevance, and usage of your files.

Apply Smart Data Classification: By incorporating deep content analysis and Smart Labeling, you can separate crucial information from unnecessary files and take action to safeguard them. As a result, this will result in reduced storage costs and enhanced data control.

Audit or Keep Track of Changes Made to Files: Regularly scan and maintain an audit trail to ensure the accuracy and confidentiality of your data. With these measures in place, you can have complete confidence that any modifications made to your data will be promptly detected, and any unauthorized changes dealt with effectively.

Streamlining Tagging and Remediation Processes: Examine unstructured data across the enterprise and implement automated tagging and remediation methods to protect business-critical or sensitive information. This will enable the detection of any access issues or policy breaches, allowing you to take appropriate measures in time.

Leverage Unstructured Data Management

Make unstructured data accessible: Automating unstructured data discovery and analysis saves time, money, and accelerates the extraction of insights.

Improved Data Analysis: Removing inconsistencies and discrepancies in your data by eliminating duplicates, repairing corrupt files, and anonymizing sensitive information will ensure accurate analysis.

Gain deeper data insight: Using NLP techniques to uncover data patterns and trends, extracting relevant information for sentiment analysis, entity recognition, topic analysis and more.

Ensure Data Security and Privacy: Automatically classify, tag, and analyze data to make it useful, and ensure compliance with privacy regulations.

You may even consider deploying a data governance tool to help you govern and protect your data throughout its data lifecycle.

Enter Data X-Ray: Unstructured Data Governance Solution

Deploy an unstructured data governance solution to discover, classify, and redact sensitive information from unstructured data sources within your organization.

Data X-Ray by Ohalo scans 100,000s of words per second, across dozens of varied sources on-premises and in the cloud. Powered by ML and NLP algorithms, it automates data discovery and classification across the enterprise.

While handling unstructured data can be challenging, it is not impossible.

In this article, we have covered the definition of unstructured data, characteristics, sources, tools, techniques, and best practices for managing unstructured data. In the next article, we will take you through scenarios that require the management of unstructured data. Watch this space.

If you have any questions or need any information, feel free to connect with us.

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