The complexity of gathering, maintaining, and interpreting huge volumes of data continues to plague organizations. It’s challenging to clean, integrate, and maintain data with goal of gaining rapid insight to help the business. But it’s not slowing down organizations in their prioritization of data initiatives. They recognize the value and game-changing potential of harnessing the power of data. It starts by properly defining objectives and desired outcomes and ends with data driving decision making and action to fuel innovation.
Data Management, Analytics & AI
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Research Objectives
Organizations are increasingly reliant on SaaS for many of their mission-critical applications and workflows. This means that a significant amount of business-critical data associated with these applications is now also cloud-resident. As a result, it is more important than ever that this data is available or at least recoverable. However, there is (still) a problematic misunderstanding about the responsibility for protecting SaaS data. While maintaining application uptime is the responsibility of individual SaaS providers, the onus for the availability and protection of data typically falls on IT organizations. This data protection gap exposes organizations to potential data loss, compliance and governance violations, and general operational risks.
In order to gain further insight into these trends, Enterprise Strategy Group surveyed 398 IT professionals at organizations in North America (US and Canada) personally familiar with and/or responsible for SaaS data protection technology decisions, specifically around those data protection and production technologies that may leverage cloud services as part of the solution.
This study sought to answer the following questions:
- What steps, if any, do organizations take to protect the data associated with the SaaS applications they currently use?
- Have organizations experienced any data losses or corruption with any of the SaaS applications they use over the past 12 months?
- What are the most common causes of data loss or corruption for SaaS-based applications?
- What benefits have organization realized as the result of using a solution to protect SaaS application solutions?
- What are the biggest challenges organizations have experienced with the data protection solution(s) they use for SaaS applications?
- What are the most important characteristics or considerations of a data protection solution, whether third-party or internally developed, for SaaS applications?
- How do organizations characterize the mission criticality of the major SaaS applications they currently use?
- What are the recovery time objectives (i.e., downtime tolerance) for the SaaS applications and workloads organizations protect today?
- What are the recovery point objectives (i.e., transaction or data loss tolerance) for the SaaS applications and workloads organizations protect today?
- Over the next 12-24 months, what level of IT priority do organizations expect to give to protecting SaaS applications, customizations, and associated data?
- How do organizations typically fund the data protection solutions used to protect their SaaS-based applications?
Survey participants represented a wide range of industries including manufacturing, technology, financial services, and retail/wholesale. For more details, please see the Research Methodology and Respondent Demographics sections of this report.
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Most organizations are not doing a very good job of protecting all their mission-critical data and applications. And, after suffering a ransomware attack, these victimized companies further report difficulties in recovering clean and recent data that might also have been compromised. Businesses have several options to protect their data and applications from attack but are slow in adopting perhaps the most viable and practical solution: air-gapped data protection infrastructure.
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Ransomware attacks are frequent, disruptive, and costly, but paying a ransom to the perpetrators as a quick fix is a bad idea. Ransom payments usually don’t guarantee the return of all the stolen data or prevent further attacks. Even the data that’s returned may have been encrypted or compromised. That’s why ransomware attacks must be prevented before they happen. And if they do occur, a foolproof data backup and recovery process must be in place to avoid suffering the consequences of paying a ransom and rewarding bad behavior.
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Findings from a TechTarget’s Enterprise Strategy Group survey gauging the state of the ransomware preparedness market conclude that much work lies ahead for many organizations as they holistically address and resolve ransomware’s ongoing threat to disrupt IT and business operations. Though most organizations are at a relatively low level of ransomware preparedness maturity, a notable gap exists in attack prevention and data recovery between the companies most prepared and the industry average.
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The demand for rapid actionable analytical insights is forcing organizations to prioritize agility, transparency, and speed across their data ecosystems. These enterprises are investing in data-driven initiatives that maximize operational efficiency, improve collaboration, and accelerate time to value. They’re turning to DataOps.
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Gone are the days when the data engineer was the key persona driving DataOps. IT operations, line-of-business leaders, developers, and end-users can all claim roles in the direction of their company’s DataOps initiatives. While this cross-functional team approach to DataOps is viewed as a positive trend, the ongoing technical skills gap in key DataOps positions continues to plague most organizations, overburden stakeholders, and compromise the value of DataOps initiatives.
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Data quality issues, distributed data, tool proliferation, overburdened and underskilled teams, rising costs, and increased risk all contribute to the complexities of today’s data ecosystem that hinder the democratization of data and analytics. As a result, organizations are looking for ways to empower data teams to reliably deliver data and analytics to all consumers. DataOps processes liberate data silos and democratize workloads throughout the data lifecycle, yielding significant improvements in data quality, cross-functional collaboration, and analytics outcomes.
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Ransomware attackers disrupt business operations by targeting a variety of data sources and leveraging multiple types of infrastructure to get what they want: business’ money. But the most often targeted point of entry in successful ransomware attacks is not a bad link in an infected email. Rather, the most vulnerable points of attack lie in the software and misconfigurations. Therefore, organizations must plan for every contingency, look beyond safeguarding the obvious vulnerabilities, and protect all components of their IT environment.
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Despite global macroeconomic conditions, aggressive technology investments are expected to continue among more digitally transformed organizations. See highlights from research into these trends by TechTarget’s Enterprise Strategy Group with this infographic, 2023 Technology Spending Intentions.
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Research Objectives
Based on a survey of 742 senior IT decision makers at midmarket and enterprise organizations, the 2023 Technology Spending Intentions Survey analyzes private and public sector technology spending expectations, the business and technology priorities driving those plans, and year-over-year trends in technology adoption and customer preferences. This year’s study from TechTarget’s Enterprise Strategy Group finds that enterprise technology spending will generally slow due to global macroeconomic conditions and the threat of a worldwide recession, but aggressive investments are expected to continue among more digitally transformed organizations.
For more information on this research, please visit www.esg-global.com/2023-technology-spending.
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IT leads the modern data platform, functioning as the conduit, efficiently delivering the correct data to the right users, to empower data-driven decision-making in organizations. Over the last decade, IT vendors have been trying to develop and offer solutions to address the flood of data that companies manage. A modern data platform tries to solve this problem. It’s a combination of interoperable, scalable and modular technologies, working together to deliver an enterprise’s overall data needs.
IT leads the modern data platform, functioning as the conduit, efficiently delivering the correct data to the right users, to empower data-driven decision-making in organizations. Over the last decade, IT vendors have been trying to develop and offer solutions to address the flood of data that companies manage. A modern data platform tries to solve this problem. It’s a combination of interoperable, scalable and modular technologies, working together to deliver an enterprise’s overall data needs.