In this video, I talk data protection with Joe Noonan of Unitrends. Our topics of discussion included:
For more from my Data Protection Conversations series, please visit: https://www.esg-global.com/coverage/data-protection-conversations.
Data teams and developers continue to serve as the lynchpin to businesses, overcoming shortcomings associated with more rapidly and reliably gaining insight from growing data sets. With improving data analytics for real-time business intelligence (BI) and customer insight consistently ranking as one of the business priorities driving significant technology spending, how are organizations enabling more end-users to actually leverage data? Skills gaps, collaboration, and accessibility have created several barriers for democratizing analytics across organizations, and pressure is being placed on data and software teams to make business intelligence easier to leverage and consume. But with the dynamic nature of the business being what it is today and the constant shifting of priorities, timeliness of delivery and accessibility of simplified analytics are being scrutinized. Embedded analytics is increasingly becoming the answer.
While AI is still considered nascent, the impact it is having on organizations that are embracing it early and often is profound. This serves as a key component to why organizations continue placing bets on AI. Even as skills gaps remain when it comes to incorporating AI into the business, organizations simply cannot afford to wait in adopting the technology as they risk being disrupted by the competition using AI today. With the rise of AI tools that simplify and automate several, if not all aspects of the AI lifecycle, expect adoption of AI to continue exploding for years to come.
Organizations continue to prioritize AI investments with a goal of achieving a more data-centric future. While business objectives point to several areas where AI can help improve businesses both internally and externally, time to value continues to be scrutinized as organizations make massive investments in people, processes, and technology in support of AI initiatives. Opportunities to reduce time to value continue to pave the way for AI technology vendors that can help simplify the adoption and use of AI technology to support a growing number of use cases throughout the business.
Though the cyclical AI lifecycle is riddled with complexity, the last mile of AI is proving to be the greatest challenge for organizations in their quest to leverage AI. Between diverse and distributed application environments, the rate at which growing data sets change and create data drift, and the dynamic needs of the business, several contributing factors lead to organizations suffering from AI deployment challenges. Both new and mature businesses leveraging AI continue to prioritize opportunities to simplify the last mile of AI—deploying AI into production—with a goal of reducing the amount of time it takes to get from trained model to production. This has paved the way for the emergence of technology to better enable businesses to deploy, track, manage, and iterate on a growing number of ML models in production environments.
As organizations strive to utilize more data, data lakes are increasingly becoming an attractive option with limitless potential. Data lakes enable organizations to unite disparate data silos and make data more accessible across the business by serving as a centralized repository or collection of data, regardless of shape, speed, or size. Organizations can then leverage a data lake to feed other data-centric tools or utilize tools that sit on top of a data lake to work with the data in-place, such as query optimization solutions that can minimize data movement while enabling improved processing and analysis. And the economic advantages cannot be understated as organizations increasingly leverage cost-effective cloud storage and minimize operating costs through the consolidation of infrastructures silos.
As with any event, Sapphire 2021 was loaded with product launches, updates, and delighted customers who shared how they are working with SAP to better leverage data that can enable them to adapt to a dynamic business environment. At the root of the keynote and breakout sessions was a common theme that likely resonated with most, if not all, attendees and that was the idea of extending the value of working together as a community to the business.
In this video, I share my perspectives on VeeamON 2021.
Cloud-based data protection is the new norm according to recent Enterprise Strategy Group research, but many IT professionals are misinformed about the data protection levels SaaS solutions provide—leading to risk.
See the data behind these trends and more with this infographic.
ESG conducted a comprehensive online survey of IT professionals from private- and public-sector organizations in North America (United States and Canada) between January 22, 2021 and January 31, 2021. To qualify for this survey, respondents were required to be IT professionals responsible for data protection technology decisions for their organization.
This Master Survey Results presentation focuses on understanding cloud data protection challenges, plans, and strategies by probing how organizations are protecting data in the cloud, as well as how they are leveraging cloud services to protect data to the cloud.
The broad adoption of public cloud services as a source and repository of business-critical data is placing the onus on data owners to deliver on data protection SLAs of applications, and their associated data, that are cloud-resident. Many users are confused about what exact data protection levels public cloud infrastructure and SaaS solutions provide, leading to potential data loss and compliance risks. Concurrently, on-premises backup and disaster recovery strategies are increasingly leveraging cloud destinations, resulting in hybrid data protection topologies with varying degrees of service levels and end-user tradeoffs and opportunities. How do IT organizations utilize cloud services as part of their data protection strategy today?
Commvault is celebrating its 25th birthday and what a ride it has been so far! I have to admit that Commvault has a special place in my heart because I pretty much started in this space at the same time and have known the company as a partner and then as a (fringe) competitor for many years when I was on the vendor side.
The past couple of years are really the most important, in my view, as they totally changed the game for the company. I blogged about this a few times in the past. (Check out my blogs here.)
Commvault’s strategy was revisited by CEO Sanjay Mirchandani, with the effect of fundamentally changing the company’s portfolio, but more importantly its future prospects for many years to come in line with what I see as the fundamental market trend of intelligent data management.