As organizations develop business strategies for the coming year, more attention is paid to data management. Once seen as an IT management task, it quickly becomes a priority at the executive level, sometimes down to the board level, as organizations turn to true data management.
About the Author Simon Field, Field CTO at Snowflake Inc. This change is happening for several reasons. The increase in IoT-connected devices has generated exponential data growth. IDC estimates that there will be 175 zettabytes of data globally by 2025. The increase in data volumes means that approaches that have worked in the past are no longer effective. Organizations are also increasingly aware of the value of the data they hold. Decision makers in all industries and services recognize that better use of their data can provide them with a point of differentiation and an advantage over their competitors. There will be a number of key trends shaping data strategies over the next 12 months. But the main ones that will affect businesses of all sizes are:
Greater migration to the cloud
By 2022, according to Gartner, Inc., 75% of all databases will be deployed or migrated to a cloud platform, and only 5% will be considered for on-site repatriation. This trend is largely due to the databases used for analysis and the SaaS model. Rather than deploy and maintain on-premises data systems and infrastructure, an increasing number of organizations will choose to shift their resources to cloud services. The main driver of this development is the need to improve the agility of companies and be able to maintain their competitiveness in difficult market conditions. Senior executives are fed up with the traditional approach where IT infrastructure needs often had to be estimated years in advance. Leveraging cloud storage and IT resources means capacity can be scaled up quickly to meet changing business and user demand, and this approach is especially important when it comes to efficient analytical data processing with your high variability in demand.
Temporary growth of hybrid data stores.
Businesses will need hybrid configurations, where some capacity is kept on-site and other is placed on a cloud platform. For some organizations, this may be a desired end state, but for most, it will be an intermediate state resulting from the longer journey involved in the migration. to the cloud Organizations will identify applications and data stores that can be easily migrated and move them first. Gradually, this will be followed by others, eventually leading to a full enterprise-wide transition to the cloud. As a result, organizations will end up with a hybrid data storage infrastructure as a "stepping stone" into the longer-term strategic shift to be in the cloud, at least for most companies.
Appearance of data environments in multiple clouds.
Many customers want to pursue a multi-cloud data strategy. However, they find that their hands are full just to operate a single cloud-based infrastructure effectively and efficiently. Over the next 12 months, technologies will emerge that will make it easier to manage multi-cloud environments. Automation tools will eliminate much of the need for manual intervention, reducing the workload on IT teams and improving user performance. Organizations will increasingly begin to view their data infrastructure as a single entity, regardless of whether it is likely to include resources from a variety of different clouds.
Continuous focus on security and privacy.
As the importance and value of data continues to grow, it is essential to maintain adequate security at all times. This will continue to be the case for the next 12 months, with security and confidentiality becoming more of a concern at the board level. Major organizations will take the time and effort to carefully review all data collected and stored and to ensure that the measures put in place to ensure its security are sufficient. Compliance with regulations like the GDPR and severe penalties for non-compliance provide all the motivation needed to succeed.
Increased use of AI
Even though the hype around the potential of artificial intelligence has been high and may have finally peaked, most organizations are still not taking advantage of the technology. While some organizations are deploying AI tools to solve specific tasks, many are still in the early stages of their use, and the road to implementation in applications and business processes remains difficult. However, as automation skills and understanding of what is possible develop, this usage will increase rapidly. AI is used to automate processes, classify data, and detect patterns or anomalies in large data sets that previously would have gone undetected. With this knowledge, organizations can be much better positioned for strategic business planning.
Growth in data sharing and monetization.
A growing number of organizations are realizing that the data they have is not only useful for themselves, but also for others. As a result, many will explore opportunities to share data sets externally and potentially generate new revenue streams. The commercial potential of data sharing illustrates the importance and value of data in all industries. Before embarking on this strategy, it is important to ensure strict adherence to confidentiality rules. Beyond removing or hiding personally identifiable information, organizations must ensure that data cannot be disaggregated at the source. Data will continue to grow in volume and value over the next year. The greatest strategic and competitive advantage will go to organizations that understand its value, put initiatives in place to store and process it cheaply and efficiently, and transform their corporate culture to become increasingly data-driven. In the age of "big data" and the cloud economy, it is only a matter of time before most organizations migrate to the cloud to unlock the full potential of their data.