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Blog

Data Classification and Data Loss Prevention (DLP): A Comprehensive Data Protection Strategy

Data is the world’s currency and has been for some time. Protecting data should be at the top of the list for organizations of any size, and the heart of any security strategy. Think about it: the purpose of any firewall, email solution, compliance regulation, or XDR platform is to keep data safe. Why not cut to the heart of it with a dedicated Data Loss Prevention (DLP)...
Datasheet

How Fortra Supports the Zero Trust Journey

What Zero Trust means, tips for getting started, and how Fortra solutions support your Zero Trust security journey.
Article

The Difference Between OCR and IDP

Compare optical character recognition (OCR) and intelligent document processing (IDP) to learn when to use each to make structured and unstructured data more usable.
On-Demand Webinar

Intelligent Automation: The Smartest Way to Automate

  Robotic process automation (RPA) is great for handling repetitive manual tasks, but what about tasks involving data that require more critical thinking? Turn to Intelligent Automation (IA). Discover how IA uses machine learning and other cutting-edge technology to take the pain out of data classification and analysis. Whether your data is structured (from a spreadsheet,...
Blog

Database Transaction Log Management

Don't let database transaction logs weigh you down. Find out how to preserve data integrity and consume less disk space.
On-Demand Webinar

Quick and Easy IBM i Disk Space Management

Studies show that the amount of data stored worldwide will grow by 4,300% within 7 years. 80% of that growth is on enterprise servers like your IBM i. If you want to be prepared to manage that kind of big data, watch this webinar!
Article

Robot Best Practices

Wondering about best practices for automating your IBM i processes with Robot systems management solutions? Take a look at this list and get off to a good start.
Article

Is the i Ready for the Three Vs of Big Data?

The three Vs of big data are volume, velocity, and variety, but in order derive value from big data, IT departments need tools to store massive amounts of data (volume) and make sure it is always available for quick analysis (velocity).