Critical migration strategy that is essential to Big Data

With the increasing demand for scalability, flexibility, and cost-effectiveness, cloud computing has become an essential part of most modern organizations. However, migrating data to the cloud is not a simple task. It requires proper planning, execution, and most importantly, data security. In this article, we will discuss why capturing the origin data and metadata of unstructured documents is essential for a cloud migration project and how it can aid security and future big data initiatives.

What is Unstructured Data?

Unstructured data refers to any data that does not have a pre-defined data model or structure. It is usually stored in different formats like text, audio, video, images, and more. Examples of unstructured data include email messages, social media posts, digital images, videos, and documents. Unlike structured data, unstructured data does not follow a specific format, making it difficult to store, process, and analyze.

Why is it important to capture the origin data and metadata of unstructured documents?

Capturing the origin data and metadata of unstructured documents is essential for several reasons, including:

Compliance: Unstructured data often contains sensitive and confidential information that needs to be protected from unauthorized access. Capturing the origin data and metadata of unstructured documents helps ensure compliance with regulatory requirements, such as HIPAA, GDPR, and CCPA.

Security: Capturing the origin data and metadata of unstructured documents helps to track who accessed the data, what changes were made, and when. This information is crucial in detecting and preventing unauthorized access and data breaches.

Data Governance: Capturing the origin data and metadata of unstructured documents helps organizations maintain proper data governance. It provides a clear understanding of where data came from, how it was created, who owns it, and how it can be used.

Knowledge Management: Capturing the origin data and metadata of unstructured documents helps organizations identify and organize relevant information. This information can be used to improve business processes, optimize performance, and gain valuable insights.

How capturing origin data and metadata of unstructured documents can aid security?

Capturing the origin data and metadata of unstructured documents can aid security in several ways, including:

Access Control: Capturing the origin data and metadata of unstructured documents helps organizations implement proper access controls. It provides a clear understanding of who has access to what data, and when it was accessed. This information can be used to identify unauthorized access and prevent data breaches.

Monitoring: Capturing the origin data and metadata of unstructured documents helps organizations monitor data access and usage. It provides a clear understanding of how data is being used, who is using it, and when. This information can be used to detect and prevent data breaches.

Forensics: Capturing the origin data and metadata of unstructured documents helps organizations conduct forensic analysis. It provides a clear understanding of what changes were made to the data, who made the changes, and when. This information can be used to identify the source of a data breach and prevent similar incidents from happening in the future.

Incident Response: Capturing the origin data and metadata of unstructured documents helps organizations respond quickly to security incidents. It provides a clear understanding of what data was affected, who was affected, and when. This information can be used to contain the incident and prevent further damage.

Why is capturing origin data and metadata of unstructured documents critical to future big data initiatives?

Capturing the origin data and metadata of unstructured documents is critical to future big data initiatives for several reasons, including:

Data Quality: Capturing the origin data and metadata of unstructured documents helps ensure data quality. It provides a clear understanding of where the data came from, how it was created, and what it represents. This information can be used to validate and improve the accuracy of the data, which is critical for big data initiatives.

Data Integration: Capturing the origin data and metadata of unstructured documents helps organizations integrate data from different sources. It provides a clear understanding of the data's structure, format, and content, which is critical for data integration and transformation.

Data Analysis: Capturing the origin data and metadata of unstructured documents helps organizations analyze data. It provides a clear understanding of what the data represents, how it was created, and how it can be used. This information can be used to identify patterns, trends, and insights that can help improve business processes and performance.

Data Visualization: Capturing the origin data and metadata of unstructured documents helps organizations visualize data. It provides a clear understanding of the data's structure, format, and content, which is critical for data visualization and exploration.

Supporting Data

According to a recent report by Gartner, by 2022, more than 50% of enterprise data will be unstructured. The report also highlights that unstructured data is growing at a rate of 62% per year, compared to structured data, which is growing at a rate of 20% per year.
Another report by IBM estimates that the cost of a data breach is $3.86 million on average. This cost includes direct expenses, such as legal fees and regulatory fines, as well as indirect expenses, such as lost revenue and damage to brand reputation.