Business Intelligence Blog from arcplan

The 4 Drivers of Cloud BI


drivers-cloud-BIThese days, everyone's talking about business agility. Wikipedia defines it as the ability of a business to adapt rapidly and cost-efficiently in response to changes in the business environment. Leading organizations realize that in a volatile business environment, the capacity to be agile determines whether the company will be able to survive and thrive in the market. Cloud computing has become a major driver of business agility, enabling IT resources to be scaled up or down in an automated way at a moment’s notice in response to internal or external requirements and to save money when resources aren't in demand. Business intelligence is also a driver of business agility, giving decision-makers massive insight into company data and the ability to quickly make predictions and decisions that influence performance.

The combination of these technologies in the form of cloud BI is becoming quite popular. A survey from TechTarget in 2013 revealed that one-third of companies have cloud components in their BI program. The companies adopting cloud BI are driven by 4 things: reduced cost, flexibility, speed of implementation, and reduced maintenance of hardware/software. Let's examine these drivers in more detail:

1. Reduced Cost

While many hosted BI solutions offer cloud BI licensing as an option, many cloud BI solutions are SaaS (software as a service) solutions – applications that are hosted outside of your company and accessed by users via the internet. User licenses are paid for on a monthly or yearly basis and you don't truly own them; you simply pay for use of the software. Companies that don't want to lay out the cash for BI software licenses at one time may benefit from this model; however, after about 2 years, they'd break even on what they could have spent by purchasing software licenses up-front. So "reduced cost" is true when it comes to hardware costs but may be a little bit of a fallacy when it comes to software costs; it's more like "reduced cost up-front" or "quicker time to ROI." Reducing costs is a valid use case for departments that don't want to go through the approval process for a capital expenditure (CAPEX), and for companies that want to avoid hardware and upgrade costs, or don't want to reallocate staff to manage BI infrastructure.

2. Flexibility

Flexibility refers to the ability to match service capacity to the fluctuating demand from business users and the ability to choose from a wide variety of cloud BI deployment models. Cloud computing is based around the idea that resources are elastic and can be easily scaled up or down depending on a company's needs. When it comes to cloud BI, flexible resources include the data itself as well as the servers needed for the analysis.

With technologies like Amazon Redshift, a cloud data warehouse solution, managing vast amounts of data in the cloud is flexible, scalable and affordable. Users can provision any number of servers on demand and scale BI deployments up or down as needed. And at less than $1,000 per terabyte per year, Redshift is a tenth of the cost of most traditional data warehousing solutions. It can easily be deployed as part of a cloud BI solution where some or all of the BI stack is deployed in the cloud. For example, a company may choose to:

  • house their data in the cloud with Redshift and also choose a SaaS BI provider (full cloud environment)
  • use Redshift for data warehousing and use an on-premise BI solution (hybrid cloud environment)
  • keep their data warehouse on-premise but go with a SaaS BI provider (another kind of hybrid cloud environment)
  • use Redshift plus BI that's not SaaS but is hosted in the cloud (marrying cloud + a traditional BI license model that's simply deployed on cloud servers rather than in-house servers)

…not to mention the choice of cloud servers that are public, private or hybrid. This is what I mean by a wide variety of cloud BI deployment models. The decision to implement cloud BI is not an all-or-nothing approach. Some things, like very sensitive financial data, can be on-premise, while other things, like a dashboard application, can be in the cloud. Whatever a company's requirements are, the flexibility of the cloud means there is an appropriate cloud model somewhere out there that will fit.

3. Speed of Implementation

According to a white paper by Tata Consultancy Services, speed of implementation is one of the key factors in favor of cloud BI because it means "immediate availability of [the] environment without any dependence on the long periods associated with infrastructure procurement, application deployment, etc." – which drastically reduces the BI implementation time. Time saved is crucial for most businesses, as is time-to-decision. If cloud BI can be implemented much faster than a traditional on-premise solution, this can be a deciding factor for some organizations. But note that customization is more difficult with SaaS BI solutions that come pre-configured.

4. Reduced Maintenance of Hardware/Software

On-premise infrastructure for business intelligence includes data warehouse appliances, BI servers, and human resources to manage and maintain hardware. For some organizations it may be more cost-efficient to outsource these tasks to an IaaS (infrastructure-as-a-service) or PaaS (platform-as-a-service) cloud provider so they can run large-scale data analysis for a fraction of the cost it would take to house and maintain the necessary physical and human resources internally. Choosing a cloud BI model where infrastructure is the cloud provider's responsibility is more affordable (cost- and time-wise) since the need to configure, optimize and update hardware and software is handled externally.

As time goes on, trust in cloud computing grows and more businesses seek an agile infrastructure, the number of companies with cloud components in their BI stack is certain to rise. Cloud BI makes it possible for smaller organizations to get into the business intelligence game – companies that don't need all the bells and whistles of fully customizable platforms or don't have an IT staff that can maintain in-house BI. I for one am firmly in favor of anything that makes analytics more prevalent.

arcplan is poised to offer cloud BI on AWS this year, but for now you can deploy arcplan in the cloud through our global partner network. Contact us if you're interested in exploring this option!


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