This post first appeared on blog.netwrix.com and was written by Antony Moillic. Organizations are experiencing explosive growth in the volume and variety of data they collect, store and process. Unfortunately, many of them do not understand what types of data they are handling — and what value that data has — so they cannot maintain proper control over it. As a result, they often suffer serious legal ..read more

This post first appeared on blog.netwrix.com and was written by Farrah Gamboa. Data lifecycle management (DLM) is the process of safeguarding data appropriately throughout its existence. The basic data lifecycle stages are creation, storage, data usage, sharing and destruction:  Figure 1. The 6 basic data lifecycle management stages The goal of DLM is to ensure data security and regulatory compliance during all stages without throttling business productivity ..read more

When a network contains an excess of redundant, obsolete and trivial (ROT) data, productivity and desired outcomes can take a hit. The good news is that organizations can significantly reduce the impact of ROT data when they plan properly and invest in the right tools. Handpicked related content: [Free Guide] 2020 Market Guide for File Analysis Software What is ROT data? ROT data is redundant, outdated and trivial content that is stored by an enterprise: Redundant data is duplicate data stored in multiple places within the same system or across multiple systems. Intranet networks often co ..read more

Your data assets are vital to the success of your business. Are your data management practices as good as they can be? This article explores the nature of data governance and explains the key data governance best practices to keep in mind when developing and implementing a data management program. Handpicked related content: [Free eBook] Building Effective Information Governance with Data Discovery and Classification What Is Data Governance? The Data Governance Institute defines data governance as follows: “Data Governance is a system of decision rights and accountabilities for information-r ..read more

Knowledge management (KM) is the discipline of not only capturing knowledge, but also storing, using and sharing knowledge. While defining the term in a general way is straightforward, each KM program needs its individual definition and techniques, depending on the organization’s specific goals and available resources. The main objectives of knowledge management are to enable the organization to increase the value of its intellectual capital and leverage its knowledge assets to achieve its goals. The idea is enable corporate knowledge to be effectively shared and reused among individuals or or ..read more

Traditionally, data protection has focused on securing the perimeter — trying to keep intruders out of systems and networks where sensitive data is stored. But with the rise in cloud computing, sensitive data can transit through or be stored in systems that are outside the traditional perimeter. Simply put, the cloud has no borders; data is free to flow anywhere and everywhere it might be needed by an increasingly mobile workforce. Therefore, cybersecurity strategy needs to shift from trying to maintain a secure perimeter around your systems and applications to securing your data against unaut ..read more

Data management is critical to the success of any business endeavor larger than a lemonade stand. A business must be able to supply its people with the data assets they need to carry out their day-to-day tasks successfully. Whether they’re positioned in accounting, production, logistics, or any other area of an organization, all staff members rely on one thing: effective data on which to base business decisions. Handpicked related content: Free eBook: Building Effective Information Governance with Data Discovery and Classification Effective is a key word here. Ensuring that you have reliably ..read more

Data is a crucial asset for businesses today. Ensuring that high-quality data is readily accessible can drive competitive differentiation, healthy business operations and regulatory compliance. Therefore, data governance is a critical initiative for many organizations. One data governance definition is that data governance (DG) enables control over the creation, distribution, use, maintenance, security and availability of business data. A DG program involves people, processes and technologies for establishing and implementing formal data management policies and procedures to manage internal an ..read more

The importance of a formalized data governance program rises with the amount of data in the organization. Smaller companies often have separate data governance processes that help with a limited scope of data-related problems, but larger enterprises commonly need to get a more formal corporate data governance program. The need for data governance originates from several issues: unreliable and poor-quality data can leave users unable to quickly find the data they need, which in turn can impede decision making, limit the efficiency of business processes, interfere with meeting regulatory require ..read more

Today, organizations often have terabytes of data, any of which could possibly be relevant to a legal case. Making this data discoverable is critical for legal professionals, but it’s an arduous task for the IT teams that support them. This article explores what eDiscovery is and strategies for making the process fast, efficient and cost-effective. What is eDiscovery? eDiscovery (electronic discovery, e-discovery, ediscovery, e-Discovery) is a legal process that involves the identification, preservation, collection and delivery of electronically stored information (ESI) as evidence in lawsuits ..read more