Data management has become just as important an enterprise function as accounting and operations, with the enterprise data management market valued at $92.99 billion in 2022, according to Grand View Research. With advanced tech such as AI being introduced to Big Data, companies and organizations have much more capabilities at their disposal to elevate their performance solely through data management. Here are some of the ways they’ll be able to do that from 2023 onwards.
More Proactive Data Security
For many years, data has been regarded as the single most valuable asset of businesses in the digital age. But as many post-mortem analyses of bankrupt businesses go, one of the biggest reasons they failed was the underutilization of data. All too often, data is either lost or otherwise rendered inaccessible. This is why more sophisticated recovery and backup methods are becoming more prevalent.
At the moment, data has ended up being split off into multiple platforms to accommodate a certain “feature creep,” so to speak, of new tech adoption within businesses and organizations. This is partly to protect against cyber attacks, but it comes at the sacrifice of data loss and unrecoverability. Hence, the natural development here would be increasing the resilience of cyber security solutions by being more proactive rather than merely reactive. This will allow companies to consolidate more of their data, thus significantly increasing ease of access.
Cloud-Native Apps and Tech
Now not only data, but the applications that make use of it, are taking to the cloud. While slightly compromising in terms of security, this has the great advantage of removing the need to maintain one’s own hardware and software tools in order to keep up operations. This advantage can be invaluable for enterprises with limited budgets since you only pay based on how much you use the service. To add to that, cloud-native apps and tech are fully scalable and user-friendly for maximum growth.
Cloud-native apps are containerized, meaning that they work out of the box regardless of the underlying OS or server. This enables dynamic deployment on any hardware without needing to concern oneself with the code base or system resources. Aside from scalability, these apps also tend to be more reliable and robust compared to traditional applications.
Comprehensive Analytics Automation With Amazon Web Services
One of the main reasons data access is so pivotal to keeping enterprises efficient is analytics. This is reflected by Amazon’s recent updates to their AWS suite, with the biggest ones being Zero-ETL integration between Amazon Aurora and Redshift and integrating Redshift into Apache Spark. These two together, says Amazon, will effectively make Extract, Transform, and Load processes as a whole obsolete. In conjunction with the Amazon Relational Database Service, this will make data practically manage itself. Knowing this, making sense of AWS RDS pricing is a little easier. Since so many database functions are relegated to AWS, they also have to spend a lot on security, driving the price up even further.
But as things stand, AWS is the most powerful easy-to-use cloud platform to date, and these updates will take it even further ahead of the competition. It does have a few significant security issues that need dealing with, but the alternative to using AWS is hunting for the right service and heavily tweaking it until it suits your purposes. On top of the current AWS suite, Amazon is also releasing Amazon DataZone to make data cataloging much easier. DataZone will enable enterprises to quickly search, share, and make use of data throughout AWS, as well as their in-house databases and any third-party sources linked to it or AWS. All of these together take care of most of the heavy lifting in database management and the collection of metadata to boot.
Smarter Data Migration
Having all of your data in the cloud can be convenient in some cases, but it can be exceedingly expensive. A better method would be to make use of different cloud storage classes. Shifting high-traffic data to more expensive cloud tiers such as NAS and lower-priority data to more affordable tiers like Azure Blob Cool will let you make much more efficient use of your data management resources. Given that the majority of data today is unstructured employing this method will add a vital layer of organization to make everything easier to manage.
One of the biggest advantages of focusing resources on high-traffic data is it opens up the possibility to employ things such as analytics and indexing without depriving access to the files thanks to file-object duality. This way, you can perform analysis, maintenance, and workflow adjustments without interrupting regular operations.
More AI-Assisted Management Tools
The labor pool remains a big issue, still reeling from widespread disruption due to COVID-19 and other factors, such as skill gaps in IT teams. Fortunately, better AI assists are now ready to be deployed for data management tools, enabling even entry-level IT staffers to perform effective optimizations, performance reporting, policy executions, and other operations. It also contributes to automating analytics by using sophisticated algorithms to catch relationships and insights in smaller data sets that bigger-picture systems such as AWS may not detect immediately.
We’re beginning to see more and more easy-to-use tools that will enable companies and organizations to relegate high-skill data management tasks previously to lower-skill staff, reducing labor costs and increasing efficiency in general. Industry experts expect that by 2025, analytics will be much more context-aware thanks to AI, allowing data management tools themselves to dynamically create, manage, and retire data pipelines as needed, all without human intervention. All the while harvesting vital trend data to report key areas that management can use to gain competitive advantages.
Data management is only one of the sectors being skyrocketed to peak efficiency by AI and automation. But out of everything these advanced techs are upgrading, data management could perhaps be the most impactful to our daily lives simply because of how many facets of modern life are driven by databases.
