Unveil the Power of Unstructured Data Discovery

According to Statistica, the amount of data generated, gathered, copied, and consumed will reach 180 zettabytes by 2025. Up to 80% of this is unstructured data.

In such a data-rich environment, unstructured data management becomes essential. On one hand, it serves as a gold mine for marketers, unlocking valuable insights and enabling informed decisions. On the other hand, mishandling unstructured data can expose a business to regulatory and security risks. Organizations who prioritize understanding their unstructured data at scale will unlock untapped potential, improve operational efficiency, and stay ahead of their competitors.

Understanding Unstructured Data Discovery

Unstructured data discovery refers to the process of identifying and extracting relevant metadata from diverse and varied data sources, such as text documents, emails, social media posts, audio, and video files. These sources may contain either sensitive information that requires protection or valuable insights that can be utilized for various use cases.

By discovering such data, businesses can effectively prioritize their data management efforts, streamline compliance procedures, and unlock untapped opportunities for growth and innovation. Additionally, this process ensures that sensitive information within unstructured data is appropriately safeguarded, preventing any unauthorized access or misuse.

Why is Unstructured Data Discovery Important?

Continuous enterprise-wide data discovery enables you to know the full scope of data stored within an organization, pinpointing duplicate, obsolete, fragmented, and redundant files.

Scanning through data lakes and repositories and finding previously unnoticed data will allow you to maintain data quality. This includes detecting missing or incorrect data and ensuring the accuracy and reliability of the information being stored. By pinpointing these data quality issues, you can take corrective actions to enhance data integrity and reliability, ultimately improving decision-making processes and business outcomes.

Categorize Data

Classifying data helps you organize and structure the vast amounts of files, making it easier to navigate, locate, and retrieve specific information when needed. This enhances efficiency and saves valuable time for your employees, allowing them to focus on analyzing the data rather than searching for files.

By bringing order and structure to the data landscape, you can apply appropriate security measures and access controls based on the sensitivity and confidentiality of different data categories. You can ensure compliance with regulations and protect sensitive information from unauthorized access or misuse.

Protect Sensitive Information

Data discovery can flag and identify files that contain sensitive information, such as financial data, which may require specific handling. By monitoring access to these data sources, an unstructured data governance tool can help prevent unauthorized exposure, ensuring that only authorized users can interact with it. This proactive approach enhances data security and protects sensitive information from potential breaches.

Cut Down on Storage Costs

Optimizing data storage and associated costs is a major challenge for organizations. As the amount of data you accumulate increases, it becomes more difficult to manage. This is where records and retention comes into play. It helps tackle this challenge by identifying redundant or duplicate data that occupies valuable storage space without any real purpose. By pinpointing such data, organizations can free up storage resources and optimize their data storage strategy.

Maintain a Data Audit Trail

Without a comprehensive record of data activities, organizations may struggle to identify who accessed or modified data, when and why such changes occurred, and whether data integrity was compromised. This can hinder investigations, impede compliance audits, and result in potential legal and reputational risks.

By implementing file activity monitoring for all unstructured data assets, you can establish a data audit trail that provides a clear and traceable record of all data-related activities. This enables transparency, accountability, and adherence to regulatory frameworks.

Now, let us explore how you can deploy best practices for unstructured data discovery across your organization.

5-Step Unstructured Data Discovery Process

1. Define Objective: Begin by drafting a data discovery strategy and clearly define the objective of your data discovery process. What specific information are you seeking to uncover?
2. Identify Relevant Data Sources: Make a list of all data sources to be examined, including data lakes, document management systems, content management systems, and cloud-based file storage systems like Amazon S3, Google Cloud Storage, or Microsoft Azure Blob Storage.
3. Auto-Scan Data Sources: Leverage a software solution capable of scanning all data sources. Analyze files like financial statements, call transcripts, and social media posts in various formats like PDFs, Word documents, or scanned images to uncover valuable insights.
4. Classify Data Based On Various Attributes: Utilize advanced data classification techniques that employ machine learning, natural language processing, and data visualization to effectively explore and analyze data. Organize files into categories to facilitate easier location.
5. Monitor and Control Data: Data discovery is an ongoing process. Regularly monitor to capture new data sources, understand the locations of all your files, determine who has access to them, identify changes made to files, and track when these changes occur.

By following this 5-step process, you can extract maximum value from your data assets while also ensuring compliance with legal and regulatory requirements.

A Go-To Data Discovery Tool

Data X-Ray is designed to discover files both on-premise and in the cloud. Powered by ML and NLP, Data X-Ray can accurately examine petabytes of data at a rate of 100,000 words per second, providing results within minutes and tagging files containing specific information. This makes it easier for you to classify files or records based on contextual cues and detect file activity anomalies.

If you've missed our previous article about unstructured data management, you can read it here. And watch this space for our next article, where we will delve into data protection, its importance, and more.

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