Moving to the cloud isn't easy, so in the spirit of research, check out this article's succinct cost-risk analysis of using cloud services.
Like any new initiative, there are both challenges and benefits to weigh when deciding whether cloud computing is suitable for your company’s analytic environment. Let’s start by understanding the challenges:
IT Governance and Control
IT departments are still leery of letting go of their data. There are many reasons, but certainly job loss and the concerns about security and privacy over data rank high on the list. IT is generally responsible for corporate data assets being implemented and used according to agreed-upon corporate policies and procedures. This means that service level agreements between the company’s IT department and the cloud provider are critical to ensure acceptable standards, policies and procedures are upheld. IT personnel may also want insight into how the data is obtained, stored, and accessed by its business personnel. Finally, it is recommended that IT determine whether these cloud-deployed assets are supporting your organization’s strategy and business goals.
Changes to IT Workflows
IT workflows dealing with compliance and security become more complicated in hybrid environments (those consisting of both on-premises and cloud deployments). The workflows must take into consideration the need of advanced analysts and data scientists to combine data that is on-premises with data in various cloud computing sites. Keeping track of where the data resides can be quite difficult if good documentation and lineage reports are not available.
Managing Multiple Cloud Deployments
Often, companies have more than one cloud computing implementation; they may use a mix of both private and public deployments – maybe even multiple ones in each category. The company must determine if each cloud provider is in compliance with regulatory requirements. Also, when considering your cloud provider(s), determine how security breaches are prevented or detected. If data security concerns are great, it may make sense for the corporation to maintain highly sensitive data (like customer social security numbers, medical health records, etc.) within their premises rather than deploying them to cloud computing.
The on-demand and scalable nature of cloud computing services can make it difficult to determine and predict all the associated costs. Different cloud computing companies have different cost plans. Some charge by volume of data stored, others by the number of active users, and others still by cluster size. Some have a mixture of all three. Be sure to watch out for hidden costs like requested customizations, database changes, etc.
It is clear that if your provider is down, so are you. All you can do is wait for the provider to come back up. A second concern is your internet bandwidth. A slow internet means slow connectivity.
Now let’s turn to the many benefits of migrating to a cloud computing environment:
Lowered Operating Costs
This is perhaps the first benefit that companies realize when considering a move to the cloud. There is a significant difference between capital expenses and operating expenses. Basically, you are “renting” the infrastructure rather than bearing the costs up front of building your own environment. The cloud computing provider bears all the system and equipment costs, the costs of upgrades, new hardware and software, as well as the personnel and energy costs.
No Maintenance or Upgrade Hassles
These are again the headaches for the cloud computing provider. This frees up all resources to have a laser focus on obtaining, accessing, and using the data, not on managing the infrastructure.
Many customers say this is the most appealing attribute of cloud computing. You can quickly scale up and down based on real needs. There is no need to buy extra computing capacity “just in case” you may need it at a later date. Cloud data warehouses can increase or decrease storage, users, clusters with little or no disruption to the overall environment.
Ability to Handle the Vast Diversity of Data Available for Analytics
Cloud computing providers can handle both well-structured data (like from operational systems) as well as the “unusual” data so popular today (like social media, IoT, or sensor data). Cloud implementations can support both fixed schemas and dynamic ones, making it perfect for routine production analytics like Key Performance Indicators or financial analyses as well as unplanned, experimental, or exploratory analyses so popular with data scientists.
Taking the time to identify both the challenges and benefits associated with the cloud is the first step in evaluating whether a move to the cloud is right for your organization. In my next blog, I’ll dispel some of the common myths associated with moving your data infrastructure to the cloud. If you can’t wait, download the complete Moving Your Data Infrastructure to the Cloud – Things You Should Know white paper now or watch this recorded webcast from WhereScape, leading provider of data infrastructure automation software.