Tips

Tips

• Integrate structured and unstructured data for better AI outputs

  For AI agents to give the most accurate, informed responses, organizations must provide them with all the facts. Even those that are hidden in an old email or customer claim.  Continue Reading

• Is your data infrastructure ready for the zettabyte era?

  AI initiatives are driving demand for curated, controlled data. Leaders must move beyond capacity planning and build the governance and quality practices that make data usable.  Continue Reading

• Modern IT threats demand continuous resilience

  Continuous resilience enables organizations to anticipate, withstand and recover from disruption. Modernize today to reduce operational risk and improve business agility.  Continue Reading

• How data mesh supports AI-ready data architectures

  Data mesh can improve data access for AI initiatives by decentralizing ownership and governance, but it doesn't solve every data challenge.  Continue Reading

• The 5 pillars of data observability

  Data observability provides complete oversight of an organization's data pipeline. Use the 5 pillars of data observability to ensure efficient, accurate data operations.  Continue Reading

• CDO challenges that hinder data-driven initiatives

  Chief data officers must turn AI ambition into measurable value. These eight issues show where data strategies break down -- and how leaders can respond.  Continue Reading

• How AI is changing data protection

  There's no doubt that recent AI developments have affected data protection. IT leaders must not only stay on top of these changes but also prepare for what's next.  Continue Reading

• AI data fabric emerges as a governance layer for agents

  The latest take on data fabric architecture promises to help AI agents coexist with existing platforms, but there's some assembly required.  Continue Reading

• Data ontologies are foundational for usable AI outputs

  Data ontologies strengthen AI outputs with governed definitions across platforms and departments, helping data leaders boost trust and improve decision-making.  Continue Reading

• How governance as code controls AI agent risk

  As more stringent EU AI Act requirements take effect, enterprises need runtime guardrails that control autonomous agents' actions, govern data access and preserve audit evidence.  Continue Reading

• 4 AI incidents that harmed resilience efforts

  AI can be a helpful tool when users respect its limitations and verify what it claims to be fact. If not, the impact on the organization can be catastrophic.  Continue Reading

• How to use AI to enforce data governance policies

  AI models and agents can automate data governance policy enforcement for proactive governance in dynamic data environments. But don't forget the human element.  Continue Reading

• The board-level economics of downtime

  Downtime is an organization-wide issue. Leaders who treat resilience as a strategic capability are better positioned to navigate future operational, cyber and market disruptions.  Continue Reading

• Isolated recovery environments are critical for modern DR

  There is no room for error in disaster recovery, especially when it comes to backups. To ensure you’re recovering from a clean backup, consider an isolated recovery environment.  Continue Reading

• Why a dashboard audit matters before BI cleanup

  Managing large BI estates takes more than deleting stale dashboards. To keep order, leaders need to assess analytics usage and assign ownership to prevent clutter from returning.  Continue Reading

• What zero-trust data protection means for business

  Implementing zero trust at the network level isn’t enough in today’s digital landscape, where critical business data is stored across platforms, applications and devices.  Continue Reading

• Why backup alone doesn't guarantee cloud recovery readiness

  Successful backup jobs can still leave dependency and configuration gaps, making orchestration and recovery testing critical for restoring cloud services and SaaS apps.  Continue Reading

• The data backup confidence gap: Are you really recovery ready?

  False confidence in data backups is a growing issue. IT leadership must ensure that recovery goals match backup realities to avoid extended downtime and loss of customer trust.  Continue Reading

• Choosing the right AWS disaster recovery strategy in 2026

  Organizations unprepared for outages often have a disaster recovery plan that does not match their business needs. These metrics can help leaders choose the best AWS strategy.  Continue Reading

• Compare AI risk management frameworks from NIST and beyond

  While NIST is the most widely used, it's just one of the frameworks available today that can help manage the risks associated with AI.  Continue Reading

• 10 big data challenges and how to address them

  Big data initiatives pose various challenges for data leaders and teams. Here are 10 common ones and advice on overcoming them to ensure deployments are successful.  Continue Reading

• AI tools are making resilience an enterprise-wide discipline

  AI tools that support resilience at the business unit level can enable more personnel across an organization to engage in disaster recovery efforts.  Continue Reading

• Top 10 vector database use cases across industries

  Vector databases have become the standard infrastructure for enterprise AI work. These 10 use cases for vector databases show where the technology delivers practical value.  Continue Reading

• Resilience strategies for an AI-powered era

  Resilience is not an optional feature of an AI strategy, it should be the foundation. Incorporate risk mitigation early on to scale AI securely while keeping up with competition.  Continue Reading

• Business intelligence challenges intensify as AI use grows

  AI can produce analytics findings more quickly, but it's all for naught if data quality lags and organizations don't address that and other issues in BI systems.  Continue Reading

• Why leadership should be involved in data backup policies

  While IT administrators lead the day-to-day operations of data backups, business leaders have a key role to play in shaping their organization's backup policy.  Continue Reading

• How to develop a data governance strategy: 7 key steps

  A strong data governance strategy enables more effective data use and helps prevent financial, legal and reputational problems. Follow these steps to develop one.  Continue Reading

• The data ownership blind spots putting organizations at risk

  Organizations can't claim to have good data governance when they still have unowned data. Assigning ownership to siloed and dark data is critical to enterprise success.  Continue Reading

• Why a risk management framework is critical for AI initiatives

  Risk management frameworks are an essential tool to optimize the planning, deployment and use of AI. Without one, AI initiatives might be vulnerable to several threats.  Continue Reading

• Sorry, backups are just not enough to guarantee restoration

  Your organization's ability to recover after a crisis depends on several factors. Our included action plan goes beyond data backup to make sure you're ready for restoration.  Continue Reading

• How to develop an enterprise data strategy: 12 key steps

  Here are 12 to-do items for data leaders developing a data strategy to help their organization use data more effectively for analytics and business decision-making.  Continue Reading

• What downtime and data loss really cost the business

  Downtime in the organization spotlights revenue and operational risk. Business leaders can use cost estimates to focus recovery spending where outages cause the greatest loss.  Continue Reading

• Data fragmentation is a major hurdle to future-ready backups

  Data fragmentation has largely been considered beneficial to a data protection strategy. Some IT leaders now view it as a business risk worthy of executive-level attention.  Continue Reading

• 6 key components of a successful data strategy

  These six elements are essential parts of an enterprise data strategy that will help meet business needs for information when paired with a solid data architecture.  Continue Reading

• Data governance regulations that executives should know

  Growing national and international regulatory compliance demands aim to protect consumer data. Organizations must adhere to regulations or face noncompliance risks.  Continue Reading

• AI, analytics push data-in-use protection up priority list

  As sensitive data moves into AI pipelines, organizations must evaluate how to protect it during processing and what safeguards IT platforms provide for data in use.  Continue Reading

• Why maximum tolerable downtime is a key business metric

  Downtime cannot be eliminated, but it can be governed. By defining maximum tolerable downtime, data leaders align recovery planning with business priorities and risk tolerance.  Continue Reading

• Disaster recovery plan checklist: Key steps for a smooth restore

  Disasters are unpredictable, but good planning can mean the difference between total data loss and a swift recovery. Avert potential crises with a disaster recovery plan checklist.  Continue Reading

• Build a data literacy program to fit company needs

  Want better decisions? Invest in a role-based data literacy program that aligns training to workflows, builds trust in metrics and improves execution on business goals.  Continue Reading

• Strengthen cyber resilience by shifting to a modern DR model

  RTO, RPO and uh-oh. Rushed restores can reinfect systems. Update outdated DR practices to avoid these issues and focus resources on the systems that matter most to the business.  Continue Reading

• Understanding the layers of the AI‑ready modern data stack

  Data infrastructure and practices need an upgrade for the AI era. A modern data stack takes a layered approach that aligns teams and delivers governed, trusted data.  Continue Reading

• 5 backup monitoring tools for better data protection

  Do you know where your backups are? Check out this list of cross-platform backup monitoring tools that provide insight into backup performance and health.  Continue Reading

• Data lineage documentation matters for enterprise reliability

  Data lineage is critical to enterprise success. Tracing a data asset's journey through pipelines helps improve data quality, speeds up corrections and builds trust in analytics.  Continue Reading

• The new standards for cyber-resilient backup

  Learn about the role of backup resilience as a frontline security control and how IT leaders can prepare their organizations to mitigate risk and meet compliance needs.  Continue Reading

• Data lakehouse ransomware recovery strategies for AI

  Attackers target the metadata your data intelligence platform needs to function. Understand where your AI risks are and what it takes to restore service after an incident.  Continue Reading

• Build trust on a federated governance model

  Follow this practical blueprint to adopt a modern data governance approach that aligns people, processes and platform to deliver measurable results from AI across the business.  Continue Reading

• ITGC audit checklist: 6 controls you need to address

  Assess the risks to your IT operations and company infrastructure with an IT general controls audit. Explore six controls to audit and key steps with this free checklist.  Continue Reading

• Master cloud backup costs for more predictable IT spending

  Predictable cloud backup spending strengthens strategic IT planning by aligning cost optimization with data resilience rather than treating them as competing priorities.  Continue Reading

• 10 predictive analytics platforms for enterprises in 2026

  The leading products have evolved into autonomous ecosystems that use AI agents and natural language to accommodate users at every skill level and accelerate decision-making.  Continue Reading

• Implement backup reporting for improved data governance

  Data visibility and governance are more important than ever in 2026. Reporting can help ensure that your organization understands what it has in its data backups.  Continue Reading

• Build a business intelligence team to optimize data use

  Leaders who want to protect data investments must build a strategic business intelligence team with five core roles: the expert, architect, designer, analyst and data steward.  Continue Reading

• How cyber insurance requirements reshape backup architecture

  From immutable backups to air-gapped copies, these requirements reflect the growing need for organizations to prove they can recover from an incident -- or risk losing coverage.  Continue Reading

• Experts share practices to overcome AI data readiness

  Enterprise AI ambitions can stumble without strong data fundamentals. Here's how to pick, organize and maintain data so systems behave reliably and projects move to production.  Continue Reading

• 6 ways to use AI in IT disaster recovery

  AI is everywhere these days, and disaster recovery is no different. IT teams can use AI to mitigate, prevent and recover from disruptions faster than traditional methods.  Continue Reading

• Should you use data backups to train AI models?

  AI models must be trained on high quality, complete data. A lot of it. Backups are a treasure trove of this type of data, but are they ready to train AI?  Continue Reading

• How to secure sensitive data when offboarding employees

  Establish a multi-phased approach that turns a risky situation into a managed process with several departments working in coordination to ensure a smooth exit.  Continue Reading

• How to cut data loss risks when employees leave

  How an employee leaves influences what data they might take. Organizations can implement several practical methods to protect code, client information, and other assets.  Continue Reading

• SaaS shared responsibility model: What vendors don't cover

  Don't let your organization lose cloud data to misplaced trust and thin vendor protections. Learn what providers don't cover and how to build backups that pass audits.  Continue Reading

• 6 essential big data best practices for businesses

  These best practices can help data leaders create an effective big data strategy that meets an organization's analytics needs and delivers valuable business benefits.  Continue Reading

• Residual access failures put data at risk

  Stop breaches that start with orphaned accounts. This guide identifies offboarding weak spots and gives leaders a practical checklist to close gaps fast and prove compliance.  Continue Reading

• 9 metadata management standards that guide success

  Organizations looking to implement metadata management can choose from existing standards that support archiving, sciences, finance and other digital resources.  Continue Reading

• Ways to protect data platforms from turnover risk

  Departing data employees can take valuable Institutional knowledge. Protect it with consistent documentation, a central repository and tested backups to keep systems stable.  Continue Reading

• Backup environment evaluation: Verify before you buy

  As backups move toward integrated data protection, this guide explains why recovery speed, environment‑wide visibility and maturing AI features should guide platform choices.  Continue Reading

• Choose an enterprise backup architecture that fits risk

  Weigh the trade‑offs among on‑premises, backup as a service and hybrid backup, and use a clear framework to choose the approach that fits your organization.  Continue Reading

• How to prevent data loss: 4 strategies for better data protection

  Preventing data loss doesn't start and end with better data backups. An organization's culture, IT strategy and choice of tools all play important roles.  Continue Reading

• 8 ways to use AI for data backup

  Recognize AI-based data backups as a strategic imperative that propels your IT team forward by protecting critical business assets while providing compliance and cost optimization.  Continue Reading

• Is cloud backup repatriation right for your organization?

  More and more organizations are making the move to bring backup data back on-site, but the cloud is still a widely-used resource. Is repatriation in the cards for you?  Continue Reading

• How to avoid data loss in a natural disaster

  Protection from environmental disruptions requires more than simple backups. This guide shows how fortified infrastructure, robust cloud strategy and risk analysis ensure uptime.  Continue Reading

• How extreme weather events affect data

  As severe weather increases worldwide, organizations must understand the risks to on- and off-premises data and take steps to prevent outages and loss.  Continue Reading

• Use the 3-2-1-1-0 rule for better backups

  The 3-2-1-1-0 backup rule addresses modern data protection requirements, such as ransomware protection and cloud backup. Find out how it builds on the 3-2-1 rule in this tip.  Continue Reading

• Data architecture vs. information architecture: How they differ

  Data architecture and information architecture are distinct but related disciplines that work in tandem to support an enterprise's data and business strategies.  Continue Reading

• How AI changes data governance roles and responsibilities

  Data governance is a team effort, though recent AI developments have caused data and AI teams to converge. As a result, organizations have created new roles in these teams.  Continue Reading

• 10 essential roles for a data management team in 2026

  These 10 essential data management roles help leaders design teams that support governance, scale and trusted analytics across modern enterprise data environments.  Continue Reading

• Key takeaways from Commvault Shift 2025

  The vendor is positioning itself to face rising data protection challenges, such as identity resilience and fragmented multi-cloud strategies.   Continue Reading

• 10 dashboard design principles and best practices

  Dashboards are a key tool for delivering analytics data to business users. Here's how BI teams can design effective dashboards to help drive informed decision-making.  Continue Reading

• How AI governance manages risk at scale for enterprises

  Effective oversight of AI systems requires more than technology. It relies on defined roles, coordinated risk protocols and tight collaboration across data and model teams.  Continue Reading

• Master these skills to get the right data scientist role

  Data science offers many professional opportunities. Balance education and experience to present yourself as an adaptable and data-savvy candidate.  Continue Reading

• 6 essential data engineer skills for modern data environments

  As AI automates more tasks handled by data engineers, the role is shifting from pipeline building to strategic skills that keep modern architectures adaptable.  Continue Reading

• 10 data governance challenges that can sink data operations

  No organization can successfully use data without data governance. Address 10 data governance challenges to avoid financial loss, derailed operations and reputation damage.  Continue Reading

• Best practices for using simulation models in business

  Simulation models provide businesses with a framework for forecasting and strategy through tested practices in finance, healthcare and logistics.  Continue Reading

• 5 knowledge graph use cases in data fabric architecture

  Knowledge graphs in data fabrics enable semantic layers, cross-domain modeling, operational intelligence, enterprise search and intelligent metadata management.  Continue Reading

• What is data lineage? Techniques, best practices and tools

  Organizations can strengthen data governance by mapping data lineage across systems. Learn how tools help to simplify tracking, compliance and lifecycle visibility.  Continue Reading

• 5 steps for sustainable data management

  Data management practices that embrace sustainability principles can streamline data processes, improve data protection and reduce energy consumption.  Continue Reading

• How to safely and securely back up data

  It's not just about ransomware. Less publicized threats like system misconfigurations, hardware and software failures, and user errors dictate a better approach to data backup.  Continue Reading

• 10-step guide for testing a backup and recovery plan

  Failure is not an option when it comes to backing up data and recovering it if disaster strikes. Data backup testing can pinpoint potential problems in the recovery process.  Continue Reading

• Enterprise data governance: Frameworks and best practices

  Data backup and recovery depend on a solid governance framework that includes procedures for data management, stewardship, quality monitoring, protection, security and compliance.  Continue Reading

• ESG data collection: Guide and best practices

  Sustainability initiatives won't succeed without quality data. Following an ESG data collection framework and best practices ensures program and reporting success.  Continue Reading

• What is endpoint data loss prevention? A best practices guide

  Today's mobile workforce puts company data at risk. Endpoint data loss prevention secures sensitive info at the source, reducing breaches, costs, and compliance risks.  Continue Reading

• Building a power outage business continuity plan: Step by step

  Loss of electric power presents a major risk to business continuity, and no organization is immune. Take these steps to create a solid business continuity plan for power outages.  Continue Reading

• Top data quality management tools in 2025

  Data quality management tools provide profiling, cleansing and monitoring features that keep enterprise data accurate and consistent across analytics and governance efforts.  Continue Reading

• Business continuity in the cloud: Benefits, issues and tips

  Using the cloud for business continuity helps reduce downtime, increase redundancy and simplify disaster recovery plans. Learn how to implement it with this tip.  Continue Reading

• Build IT resilience to avoid paying ransomware demands

  No one wants to pay the ransom after a cyberattack, but many organizations feel like they have no choice. Explore the benefits of investing in resilience over making payments.  Continue Reading

• Automated backup: How it works and why you should use it

  Automated backup tackles complex data backups in concert with other automated workflows, minimizing human errors while ensuring regulatory compliance and business continuity.  Continue Reading

• Synthetic data vs. real data for predictive analytics

  Synthetic data helps simulate rare events and meet privacy compliance, while real data preserves natural variability needed to evaluate models against unpredictable conditions.  Continue Reading

• Is cloud data backup and recovery right for you?

  Still not sure if cloud data backup and recovery is the best choice for your organization? Here are six questions for IT managers to consider when making the move to cloud.  Continue Reading

• Top business continuity risks to plan for and monitor

  The key to mitigating business continuity risks is identifying them early. Here are 10 top risks concerning business continuity pros today. Is your organization ready for them?  Continue Reading

• Why you need a payroll disaster recovery plan

  Payroll data is critical, and the consequences of losing it are steep. Learn how to create a strong payroll disaster recovery plan to protect employee data.  Continue Reading

• Crisis communications plan: How to build one, with template

  Don't overlook crisis communications when you are disaster recovery planning. Use these tips and our free template to build a thorough crisis communications plan.  Continue Reading

• 7 predictive analytics skills to improve simulation modeling

  Predictive analytics skills such as statistical analysis, data preprocessing and model evaluation can help data professionals build more accurate, dynamic simulation models.  Continue Reading

• Implement a business continuity plan for remote workers

  Business continuity efforts don't stop when employees go remote. Learn how to create and manage a reliable business continuity plan for remote workers.  Continue Reading