Save on your Cloud Data Management with these four hacks

, Dec 17, 2020

Moving data management from strategy to execution  

There’s plenty of material out there on how data is the most valuable asset in for any digital business, but it can also be one of its biggest headaches.    

From mining data for actionable insights to fuelling AI, data has massive potential to create value. It’s great having lots of it, the challenge is to collate and manage it effectively to maximise value and optimise costs.

Hybrid cloud adds another layer of opportunity and challenge around having the right data in the right place at the right time, with the right controls around it.    

Effective execution is just as important as a strong data management strategy. Taking practical steps to deliver immediate tangible cost, time and management benefits maintains momentum and focus. 

Which is where these four hacks for data management in a hybrid cloud world come in. Ideally, they should be implemented as part of a wider coherent data management strategy, but they have the advantage of delivering substantial benefits in their own right. 

Hack #1 – Cloud Data Efficiency

IT organisations have spent years looking to maximise the efficiency with which they store data in datacentres and move it across networks, compressing, deduplicating and generally making sure it occupies the smallest footprint possible.   

In the Cloud, data is generally stored in its raw state. Data costs are metered so that, as data volumes mushroom, so do costs.      

Cloud data efficiency appliances reduce the volume of stored data by extending data efficiency capabilities like deduplication and compression to the Cloud. Ratios of 3 or 4 to one can be achieved, packing 100 terabytes of raw data into 20-25 terabytes.   

Naturally you have to factor in the cost of running HA pairs of appliances across each region of each cloud that you use. Fortunately, many appliance vendors offer cost/benefit calculators which take into account the appliance costs, so you can easily establish what savings are achievable.

Hack #2 – Auto Cloud Tiering

Automatically optimising data tiering across data centre reduces data costs by automatically moving data between storage tiers so that expensive performance data storage only holds data that needs to be there.

There could be a single data centre tier of flash-based, performance data storage in the data centre, with policy driven automation to move ‘cold’ data, say over 30 days old, to cheaper object-based cloud storage. The cloud data is still visible from the performance tier and is automatically pulled back to the performance tier when it’s needed, so the whole process is transparent to the user.

Encryption is maintained in transit and at rest, and, if the data is compressed and de-duplicated, it is only rehydrated when it is actually used.

Hack #3 – Copy Data Management

Data centre copy data management capabilities can be extended to the cloud, to improve information security and compliance, reduce data storage costs, and eliminate the operational overhead of providing and maintaining data copies.   

The key word here is management. It’s easy to create snapshots and copies of data, making it easier still to lose control of data versions and end up paying for data which isn’t being used.

There needs to be a simple, automated, preferably self-service mechanism to provide controlled copies and snapshots quickly and easily, servicing data protection and recovery, Devops, data scientists and AI.

Automated copy data management automates identification of existing snapshots and copies and classification of master datasets, provides APIs for self-service or programmatic data copy creation, enables visibility of all data copies across data centre and cloud and, most important, automates policy by setting automatic expiry dates for copies.  

Hack #4 – File Sharing and Caching

The growth in remote working has highlighted once more the value of local shared or cached data. Relying on data which is centralised or scattered across multiple clouds raises the constant challenge of cloud and network latency.

Cloud data management enables automated creation and management of local file shares and copies, with continuous file synchronisation. This avoids the risk of having multiple versions of the same data getting out of synch with each other and improves local access times. 

Where next? 

These four hacks can deliver tangible cost, time and operational management benefits as part of a hybrid cloud data management strategy.

To find out more and continue the conversation, contact us at

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