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Basically everything in IT these days revolves around managing waves of data coming in from multiple outside sources: mobile devices, ecommerce sites, data streams for analytics, enterprise ecosystems, sales/marketing partnerships and so on. Thus, the function of data management is constantly evolving to handle the influx of files, logs, images and everything else.
What’s relevant today may not be relevant tomorrow, much less next year, requiring companies to constantly evaluate data, innovate, evolve and maintain agility–all while tiptoeing the line of data management and analysis to ensure the right data is on hand when you need it most.
The sheer volume of data continues to increase at a staggering rate, and while some of it is beneficial, much of it is irrelevant. Moreover, a disturbing portion is dark and potentially dangerous. This has led to data protection giving way to data management, where data is the fuel for company success, driving insights, customer targeting and business planning–and even more so today, training artificial intelligence (AI) and machine learning models.
Any way to extract additional value from it is critical to business success and the shift to management ensures data is properly archived, easily searchable, can be leveraged for analytics, and is compliant the entire time.
This eWEEK Data Point article features an industry perspective for 2019 from Prem Ananthakrishnan, vice president of products at Druva. Here’s a look at his expectations for the new year.
Data Point No. 1: We’ll see the rise of smart clouds. The adoption of streaming data capture from the internet of things (IoT) and sensors, data governance policies, security standards, expanded data curation and compilation and widespread adoption of AI and machine learning have made it impossible to rely completely on on-premises solutions. Technologies such as AI, machine learning, and analytics thrive in environments with expansive amounts of data and compute abilities beyond those available in on-premises solutions. These trends greatly favor cloud-based architectures, and will only increase as vendors offer more advanced solutions.
Data Point No. 2: The cloud wars will escalate in 2019. Serverless architecture will drive down costs even further, and I would expect hybrid and multi-cloud to become more popular with pushes from VMware and Amazon Web Services (AWS). Online marketplaces will shift spending from offline distribution and vendors, and resellers will increasingly adopt digital VAR-like models. Machine learning and AI will continue to rise in adoption, become embedded within cloud-based solutions and increase the allure of cloud computing. Because of these technologies, public cloud will become the de-facto choice for developers.
Data Point No. 3: Unrecovered data loss will be on the rise. Ninety percent of respondents to Druva’s 2018 State of Virtualization in the Cloud survey noted they will be using public cloud in 2019, however many companies are still backing up their IaaS/PaaS/SaaS with manual processes. Even more concerning, notes W. Curtis Preston, Chief Technologist at Druva, is that some are not backing up their IaaS/PaaS/SaaS environments at all, based on the assumption that the protections offered within the service itself are “good enough.” These protections–in Office365, for example–do not mitigate risks associated with hackers, ransomware, malicious users, or typically anything deleted more than 60 days ago.
Data Point No. 4: 2019 is the year of government data compliance. Data management is no longer simply a consumer vs. corporation battle; it has quickly elevated to the country and federal level. In the wake of GDPR, others are using it as blueprint to enact more stringent compliance standards. The California Consumer Privacy Act goes into effect January 2020, and we should expect to see more of the same in the coming years from other jurisdictions. Such regulations mean company obligations will become more complicated and will need to meet new standards. Having the flexibility and scalability to store data within specific regions will become a key buying consideration and increasingly favor cloud deployments over on-premises solutions.
Data Point No. 5: Blockchain will become a commodity. Vendors are fighting for a share of the rapidly increasingly market for blockchain applications, but the reality is it’s a race to the bottom. As standardization continues, there will be little differentiation, and blockchain will slip into the background of applications, taking place behind the scenes. Industries such as data management will begin adopting this technology, since it offers a way to validate and trust the data as records are pulled into other resources.
For a good example of how blockchain works in an enterprise, see this eWEEK article.
Data Point No. 6: The autonomous car will create data center chaos. There is a massive investment right now in autonomous and connected cars, and soon this investment will need to cascade to the data center. The success of autonomous cars relies on telemetry data from vehicles to inform driving decisions, but how do you properly archive this data for compliance? With so many data points becoming created every minute, how do you properly isolate necessary data, such as from any accidents or incidents and retain it for the multiple years necessary? Proper data management architectures will be key to ensuring their success.