Multi-Cloud Data Management of Today
Multi-cloud has evolved: what was once a relatively ad hoc practice of using public clouds to augment data storage and processing on an as-needed basis has now become a strategic focus for many enterprises. Companies are finding value in using multiple public clouds to manage costs and risk, and increase flexibility and agility. In fact, 84% of enterprises say they have a multi-cloud strategy in place, and 85% of senior IT decision-makers say they store data in two to five public clouds.
However, when you have “multi” anything, it brings complexity. A multi-cloud environment can result in siloed data and significant challenges for cohesive data management and governance – particularly when a multi-cloud environment has developed without a plan over time.
One global survey found that while more than 90% of respondents said they originally believed the public cloud would help simplify operations and provide greater data insights, the reality has been a different story. Of those who felt let down by the promise of the public cloud, 91% believed the problem was fragmented data in and across public clouds that would become extremely difficult to manage over time.
The appeal of multi-cloud ultimately comes down to minimizing costs and reducing risk. Companies use multiple public clouds to optimize costs by deploying workloads on different cloud providers as needed to be more efficient and/or leverage preferred tools. The use of multiple clouds also protects against the risk of vendor lock-in, which could have major business repercussions.
As the top cloud vendors – Amazon Web Services/AWS, Google Cloud Platform, and Microsoft Azure – continue to diversify (e.g., will Amazon make a foray into banking?), relationships with their customers may become more complicated – perhaps even competitive or a conflict of interest. Also, vendor lock-in can affect what cloud tools and services a company is able to use.
Even if a company isn’t planning on implementing a multi-cloud strategy, multi-cloud can become a six-month-plus reality if a decision is made to transition from one cloud provider to another, or as a result of an acquisition or merger.
Preparing for a multi-cloud world
The many paths to multi-cloud all lead to the same need: a way to consistently and efficiently manage and govern all data, no matter where it resides – without disrupting the business or requiring huge investment to rip and replace systems and tools. To help evaluate your current needs, consider:
- Can you create a virtual “data lake” without having to move data from where it currently resides?
- Is your IT team spending too much time managing data and could automation help lighten the load?
- Are you at risk of vendor lock-in or hindered in any way from leveraging multiple cloud services or preferred tools?
- Can your business users easily discover and use data from across the enterprise (i.e., not only across public clouds but on-premises as well)?
- Do you feel confident that you will be able to scale the management and governance of your data into the future?
Multi-cloud data management platform essentials
What is the best solution in order to reduce complexity, not increase it? When working to determine what data management platform makes sense for a multi-cloud environment, here are some key features to consider:
1. Centralized visibility and governance
Multi-cloud makes “vendor agnostic” a must-have feature of a data management platform. A platform that can talk to any system or tool provides the flexible connections that unify and integrate siloed data for centralized visibility and data governance – without the need for your IT team to move data around in order to find, manage and govern it. Centralized control using one, comprehensive platform allows administrators to set up consistent governance rules for data quality, compliance, privacy, and security.
From a business user perspective, a centralized platform that can crawl and recognize data across all cloud providers and create a self-service catalog that’s a single source of truth can significantly accelerate time to insight.
2. Automation and machine learning
Unlike traditional data catalogs that simply provide an inventory of data, modern data catalogs that leverage machine learning and AI help reduce the complexity of multi-cloud by automating workflows along the entire data pipeline, from ingestion to provisioning.
Automation of repeatable tasks, such as metadata collection and data profiling, not only speeds up workflows and frees up team member time, it reduces errors and ensures consistent governance across multi-cloud data sources for data quality (change capture, duplicate identification), data privacy (tokenization and masking), as well as data security (enterprise-wide, role-based access rules).
3. Hybrid and cloud flexibility
The point of using the public cloud is to leverage its storage and processing power to reduce costs and increase speed; you need a data management platform that can flexibly manage this across cloud providers.
There are many data management platforms capable of data orchestration within a single cloud provider. What’s rarer is a data management platform for multi-cloud – enabling governance in cloud-native storage, as well as flexible data transformations and delivery across multiple clouds (and hybrid environments, let’s be real), without companies having to give up existing systems and tools.
For example, a platform for multi-cloud should automate repeatable, on-demand native processing, depending on where the data resides – if the data is in AWS, the platform should spin up processing power on AWS. In the near future, some platforms will automate moving data between cloud providers to achieve even better efficiencies – so seamlessly that the business end-user won’t even know.
A multi-cloud strategy can make a lot of sense for businesses – but it requires having the right data management and governance platform in place to simplify multi-cloud environments for both administrators and business users. Learn more about how Zaloni can help conquer data sprawl and effectively build a multi-cloud data environment. Then, when you’re ready to have complete visibility into your data, get your custom demo!