Over the past eighteen months, both mainstream and start-up software vendors have been announcing a number of hosted business intelligence (BI) solutions. However is it possible to support a rich, fully functional Business intelligence experience for major corporations or will it remain the domain of the smaller company.
Technology and Availability
Cloud based solutions were initially targeted at the smaller company or organization
without the hardware and software infrastructure or major investment capital.
The first SaaS (Software as a Service) applications were aimed at retailers who
did not want or could not afford to purchase an in house (on premises)
application; an example would be Salesforce.com, which now delivers sales
solutions to over 1 million subscribers. However with the major BI players now
becoming more and more involved in the Cloud how does the current Cloud BI tool
set stack up against the on premises solutions available.
The cloud currently hosts four main types of services, SaaS, Platform as a
Service (PaaS), Infrastructure as a Service (IaaS) and Data as a Service
(DaaS). As stated above SaaS applications have been around since the inception
of the Cloud however PaaS, DaaS and IaaS are only recent additions to the Cloud
area brought into focus by the recent offerings in the IaaS area, which a
number of my associates in the administration areas of larger companies’ IT
Departments are using as development and test areas. PaaS is the most recent
addition, which allows developers to deploy their own custom developed
applications to the cloud. This broad spectrum of services allows the customer
a lot of choice, especially in the area of data warehousing, which can be
deployed in various forms throughout the any of the above "as a
Service" types dependant on your requirements.
I have developed utilizing Microsoft’s offering "Azure" and can
confirm that utilizing the Cloud is a pain free experience for the most part,
especially when incorporating virtualization and inbuilt Extract, Transform and
Load (ETL) tools. Some of the Cloud major players however are still not ready
to support the large data sets and complex analysis that is required for a
really useable BI solution to be deployed inside the Cloud. This includes
Google’s PaaS offering, which although it has a comprehensive set of apps and APIs,
does not have the open ended storage capacity of say Amazon’s EC2, which also
allows the user to bind their own front end analytics to the storage solution.
One of the major concerns that I have had voiced when talking to business
managers about BI from the Cloud is that of security. Local, on premises data centers
and data warehouses are closely guarded and strictly managed by your own IT
Security Department and moving that data outside the companies’ secure
firewalled confines promotes fear of data loss and breaches of security. However,
the use of Virtual Private Networks (VPN) and an inspection of the security of
the host machines and data center by your companies network security team will
provide reassurance – in these days of outsourcing of much of a company’s
sensitive data to third parties, this is just another extension.
Can the Cloud provide the processor intensive computing power and storage
facilities required by a major corporation looking to replace their manpower,
energy and space intensive current solution? The Cloud provides an unlimited
pool of computing power, memory and storage, which are delivered in affordable
discreet modules to the end user. This business model, which delivers unlimited
scalability with very little overhead is undoubtedly appealing to the corporate
finance departments of many major corporations and I believe from my experience
and with careful planning can be utilized by any company.
The following considerations must however be factored into the decision to
adopt BI in the enterprise for your company:
- Plan for the worst
- Perform due diligence for security, backup and disaster
- Do not overlook BI Cloud pricing and contract matters
- Evaluate the long term cost of ownership
- Investigate license requirements
- Consider your data transfer requirements
Many of the major vendors in the BI community are now actively seeking a
presence in the Cloud BI arena, SAP BusinessObjects BI OnDemand, Microsoft
Azure and IBM Blue Insight; whether they succeed or fail in their enterprises
will inevitably drive the use of the Cloud for mainstream BI solutions. I
believe however, that BI in the Cloud will primarily be utilized by the major
corporations as a development tool to reduce overhead costs. It represents a
way for a BI application to be developed, installed and adapted to need with
reduced costs and easier deployment, without the need for capital investment in
hardware and infrastructure space.
- Speed of Deployment
- Ease of Access especially for Power users and Analysts
- Data transfer rates – especially for data sets of a
terabyte or more.
- SaaS offerings especially need to be specially tailored
for the data they are linking into.
- The possibility that the vendor your company chooses in
this start-up stage may not survive to support your long term needs.
The fact that the Cloud can support BI is not at question here; the
requirement is that it supports major corporation’s BI needs. I believe that
the ability to provide a pay as you compute infrastructure will provide new
data warehouse storage options and provide the possibility of unlimited
scalability within your corporate environment. However, these major plus points
must be tempered with a realization that BI in the cloud is still in its
infancy. Major consideration must be given to security, data transfer rates and
the chosen vendor’s risk within the market place. If your company can perform
due diligence to satisfy themselves that these possible stumbling blocks can be
offset then there is the ability for the cloud to satisfy the most demanding of
companies. I believe that the main users of cloud BI as a main source of BI for
their companies will be SMEs and that larger corporations will utilize the
cloud as a sandbox for pre-deployment development and testing.