Data security and privacy are two of the most important aspects of any business. Data security is the practice of protecting digital information from unauthorized access, corruption, or theft throughout its life cycle. Data privacy is a guide to how data should be collected or handled, depending on its sensitivity and importance. It is essential for businesses to understand the differences between data security and privacy, as well as the best practices for keeping data secure and private when using managed IT services over the internet.
Data security is the process of protecting corporate data and preventing data loss through unauthorized access. This includes protecting your data from attacks that can encrypt or destroy data, such as ransomware, as well as from attacks that can modify or corrupt your data. Data security also ensures that the data is available to anyone in the organization who has access to it. To properly protect your data, you need to know the type of data, where it is located and what it is used for.
Data privacy generally applies to personal health information (PHI) and to personally identifiable information (PII). This includes financial information, medical records, social security or identification numbers, names, dates of birth, and contact information. Compliance regulations reflect this difference and are created to help ensure that companies enact user privacy requests. Increasingly, organizations are looking for standardized ways to store and manage data so that it is portable in the clouds.
Management and access controls The principle of “access with minimum privilege” must be followed throughout the IT environment. Backups are an effective defense against ransomware. If an organization has a recent copy of its data, it can restore it and regain access to the data. Part of ensuring data privacy is understanding what data you have, how it is handled and where it is stored. Learn about digital asset management (DAM), a business application that stores rich media content, and how to manage and protect it.
When ransomware spreads to backups, “the game is over” for data protection strategies, as it is impossible to restore encrypted data. Enterprise Resource Planning (ERP) is software designed to manage and integrate the functions of basic business processes, such as finance, human resources, supply chain and inventory management into a single system. Learn about Elasticsearch, a popular enterprise search and NoSQL database solution, and how to manage and protect it. Identity and Access Management (IAM) is a business process, strategy and technical framework that allows organizations to manage digital identities. However, cloud platform providers, such as Amazon Web Services (AWS), Google, and Microsoft, have made it easy to set up and manage Hadoop clusters in the cloud.
Customer relationship management (CRM) is a combination of practices, strategies and technologies that companies use to manage and analyze customer interactions and data throughout the customer lifecycle. Another complementary solution is a business password manager that stores employee passwords in an encrypted form, reducing the burden of remembering passwords from various corporate systems and making it easier to use more secure passwords. Splunk is a software platform that indexes machine data, allows it to be searched and turns it into actionable intelligence. When using analytics and reporting tools from managed IT firms services over the internet, businesses must ensure their data remains secure by following best practices for data security and privacy. This includes understanding what type of data they have, where it is located and what it is used for; implementing access controls; backing up their data; using encryption; understanding compliance regulations; using digital asset management; using identity management; using customer relationship management; using password managers; using enterprise resource planning; using NoSQL databases; using Elasticsearch; using Splunk; understanding cloud platform providers; understanding ransomware; understanding Hadoop clusters; understanding machine learning algorithms; understanding artificial intelligence algorithms; understanding natural language processing algorithms; understanding blockchain technology; understanding quantum computing algorithms; understanding distributed ledger technology; understanding edge computing algorithms.
