<div id="readability-page-1"><div>Rob Tribe: Vice President, Systems Engineering, EMEA, Nutanix. 
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Although cloud computing was first proposed in the 1960s, its wider popularization didn't start to take effect until after the millennium. But, even in the post-millennial early days of cloud era 2.0, most of the data services, applications and software tool functions were generally the preserve of network engineers and software architects working in the trenches. 
A decade later, things are different again in cloud era 3.0. We all now have an opportunity to access an increasing number of cloud services as users at different levels, often from the comfort of our mobile devices.  
 
This latest epoch has seen the technology industry go to extensive pains to provide abstraction layers to give every user the chance to store, analyze, access and retrieve data that resides in cloud-based data repositories inside dedicated datacenters. We call this data democracy.  
 
More Than A Buzz-Phrase 
Although data democracy has become an overused industry buzz-phrase, it is a term with real meaning and substance. It is the notion that anyone can use heavyweight back-end analytics tools through upper-tier visualization layers that feed familiar desktop and mobile computing tools to exploit data for competitive advantage in live environments. 
 
In this age of cloud, we all create, store, analyze and exploit data. Modern businesses are sitting on vast pools of data and creating more daily. As contemporary digital organizations drive increased use of cloud-native technology, intelligent machines and smart software systems sit alongside human beings in the data-growth stakes.  
The impact of the way data is growing and being consumed throws up some questions; the common notion that every application requires its own database, for example, needs to be questioned. It may have been true once, but is no longer the case. It also leads directly to one of the major roadblocks that all businesses now face in trying to fully exploit the data they hold — let alone any newly generated data.  
The notion that every application requires its own database is how data gets trapped inside silos, each dedicated to the retention of that specific data set. There is now a fundamental contradiction for businesses to deal with. It may make sense for data to be stored in silos, but they need to appear to be one coherent source of information. 
All About The DBaaS 
Here, the notion of cloud-based Database-as-a-Service (DBaaS) comes into its own. 
DBaaS allows any number of different databases to be created — be that because the data is created and most often used at a specific location or perhaps the data requires storage in a specialized database. Cloud services make that easy to organize. It also makes accessing the data easy, subject to a user having the appropriate permissions and following compliance or governance regulations that allow them to exercise those permissions.  
The key &#34;service&#34; is not the process of storing data. It is the ability to provision users with the data they require, at the point where it's needed, at the time it's needed, regardless of where or how it is stored. A business can choose to have a fully private cloud service to run its DBaaS resources on, which will often suit users where security, confidentiality and performance are important. Though, for some, these are occasionally traded off against flexibility, cost and the ability to scale services up or down rapidly. 
Operating DBaaS as part of a hybrid cloud environment is the likely option for most businesses as it offers the best mix of flexibility, choice of services and the basic management environment needed. Most of the major cloud services providers are — or certainly will be — offering the availability of DBaaS systems, meaning users can have choices and can mix services together as required. 
Real-World DBaaS Challenges 
If we can agree that DBaaS represents a big potential step forward, we should still move forward with care. Like any enterprise technology, organizations will face different implementation challenges as they work to fit and shape new data tools into their own IT stacks and across their line of business operations.  
DBaaS is all about standardization. Through standardization, we are more easily able to run IT at scale when a business can replicate its implementation process to something representing a template or a reference architecture. But standardization has a cost — i.e., regulatory compliance rulings differ across different industries and world markets.  
Just because a business can store one type of data in location and process it through systems x, y and z is no guarantee that the same approach can be mapped to the next region. Specifically, in the area of customer data, an instance of DBaaS tracking U.S. customers may have more information than is permissible for a European customer base due to GDPR stipulations.  
Businesses using DBaaS in these cross-border scenarios may need to run a separate DBaaS instance for each set of operational data. When appropriately anonymized and obfuscated, there may be opportunities to coalesce all data sources to track wider customer trends. A one-size-fits-all approach is rarely applicable in the world of cloud, data or users. 
Further challenges may present themselves in terms of what happens to DBaaS implementations over time. Short-term data requirements are rarely the same shape as medium or long-term requirements, but knowing what scalability path an organization needs to prescribe for itself is not always straightforward. However, standardization, compliance and growth obstacles are not insurmountable and are easier to manage if customers go into DBaaS with an appreciation for the landscape ahead. 
An information-driven future 
Accepting the fact that not every technology will provide an instant one-click quick fix, we can bring the benefits of DBaaS to bear in productive and tangible ways if we do it diligently and strategically.  
As they say: With great power comes great responsibility. But, with great data power also comes great responsibility to ensure data integration and management within appropriate guidelines to ensure standards are established and regulatory compliance met.  
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Although data democracy has become an overused industry buzz-phrase, it is a term with real meaning and substance.

理事會帖子: 數據庫作為服務: 對數據民主的投票