In the world of data, there is structured, semi-structured, and unstructured data.
Structured data has a fixed schema and consistent structure. Types of structured data include a variety of databases, whether just standard databases (e.g., Microsoft SQL, Oracle, PostgreSQL), application databases (e.g., ERP, financial & accounting systems), on-premises, or in the SaaS cloud (e.g., Salesforce, ServiceNow, ZenDesk).
Semi-structured data is defined by a flexible schema, mix of data types, partial consistency, and varying data streams. Types of semi-structured data include .csv, .xls, .avro, JSON files.
Unstructured data is defined by open formats and various file types. Examples of unstructured data include Word documents, PowerPoint slides, PDF files, txt files, image files, media files, amongst many others.
When analyzing these various data sets for identification, classification, and remediation, structured data is the most straightforward, followed by semi-structured data. Given the inherent flexibility of unstructured data, this format is the most difficult, challenging, and time consuming to accurately identify, classify, and remediate.
Unstructured data management (UDM) is the ability to identify what files are and what they contain, classify files based on identification and various business rules and logic, and remediate files based on identification and classification. UDM also requires managing these files on a wide variety of data sources such as
- Generic file shares such as CIFS and NFS
- High-end storage devices such as NetApp, EMC Isilon, Pure, and others
- Document management systems (DMS) such as SharePoint Server, iManage, Documentum, and others
- Cloud repositories such as SharePoint, Azure blobs, AWS S3 buckets, Google drive, Jira, Confluence, Slack, and others
- Email systems such as Exchange server, Exchange online, Google mail, Lotus, and others
Lastly, UDM requires the ability to manage at the levels of gigabytes, terabytes, and petabytes … or billions of files spread across multiple data centers and cloud repositories.
The market-leading UDM solution is Congruity360’s Classify360, which consists of Insights, Insights + Actions, and Comply360. The Classify360 solution empowers customers to take a crawl-walk-run approach to identifying, classifying, and remediation the millions and billions of files. Classify360 is a single-pane-of-glass that centralizes the knowledge and management of these files, which replaces file lists, reports, and help desk tickets, leading to increased efficiency and productivity while reducing or eliminating errors … and more DATA!
The first step is Insights, our easy and fast metadata scanning solution to provide quick understanding (or Insights!) of your unstructured data estate. How and when do you know to start with a UDM solution such as Insights? The following are a few key examples and questions that our customers considered before leveraging Insights:
- Storage savings – Are you about to make a storage renewal? Are you adding more storage? Has the business stated the need to reduce storage costs? The storage savings powered by Insights pays for the solution, plus more!
- Storage optimization – Have you been told to figure out ways to use less storage? Or to reduce data insecurity attack plane? Duplicates? Aged files? Inactive files?
- Cloud migration – Are you about to start or have started a data migration to the cloud initiative? Have you gotten questions about “what data really needs to be migrated to cloud”? Have you been tasked to shorten the cloud migration timelines? Have you asked to reduce overall storage costs (on-prem + cloud)? Does some data need to be migrated, but off the grid?
- AI readiness – Are you starting gen AI projects and initiatives? Have you gen AI providers given you full disclosure of AI costs? Have you considered what data to not put into gen AI? And what to include? The gen AI is not inexpensive, and if you’re including irrelevant data, your AI costs will soar.
- Initial security risk identification – many files have names identifying risk such as passwords.txt, credit_card_list.xlsx, and similar
- Target specific content analysis – not all data needs content scan and analysis
- If in HR folder, then it’s HR data
- If in GC folder, then it’s GC data
Contact us today to get started with Classify360 Insights on your unstructured data to rapidly reduce storage costs and project timelines while decreasing security risk!
