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Cloud computing has almost become a rage among IT industry and businesses today. It is transforming the way organizations create software, applications and the way they do business. The fundamental need of focusing on core business, controlling IT expenditures and adaptability to changing business ecosystem is driving companies to move to cloud.
Establishing a in-house data warehousing and business intelligence (BI) environment is not a trivial task, organizations have to spend millions of dollars to procure hardware, software and then spend months in installation, configuration and optimization before they could actually start using these systems. In addition to this, top it up with the investment in resources for continuous administration and the periodical hardware upgrades to manage growth and keep the momentum going.
All the above factors combined together make it very compelling for companies to make a radical shift of some of their on-premise analytical data warehouse environments to cloud. It simplifies and speeds up analytics without the need of deploying heavy weight infrastructure and teams. On-demand resource provisioning helps in accommodating real-time workload surges without much manual interference. Imagine having a plethora of compute capacity lying idle in server rooms for once or twice a week reporting vs. having it on cloud and only paying for the required usage.
However, irrespective of these innumerable benefits which a cloud can provide it still involves certain challenges which may make businesses wary of putting their data warehouses on cloud:
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Security:
- What type of data can be put on public cloud?
- How secure it is to put sensitive organizational data on public cloud?
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Data Volume:
- What volume of data can a cloud environment support? Loading huge amount of data which is very typical of a data warehouse requires high bandwidth, how efficiently can a cloud handle that?
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Performance:
- Performance of a virtual machine on cloud may not match that of a bare metal server.
- This may impact the complex analytics being performed on a data warehouse.
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Transaction Latency:
- What could be the impact on business due to loss in transaction latency arising out of communication over a network (large distance between datacenter and users and/or lower bandwidth), especially in financial world?
There are several vendors who now provide data warehouse and BI as a service but everyone may not be able to handle the complexity of a data warehouse and analytics ecosystem on cloud.
IBM’s BLU acceleration on cloud is an offering which provides a self-service BI and data warehousing on cloud using best in class security and other features to support even the most complex production environments. It is powered by IBM DB2 with BLU Acceleration a next generation in-memory technology. Columnar data processing and high compression rates combined with an enterprise class BI and DW tools like Data Architect, Cognos and compatibility with R help customers transform their data into insights at speed of thought. Through BLU Acceleration on Cloud now even small organizations who could not afford to establish data warehouses earlier can have access to one of the most advanced analytical environment and make the best out of their data at a very low cost.
BLU Acceleration on cloud is available on IBM Softlayer and Amazon Web Services (AWS). I am really excited to invite you to get hands on experience of the technology through a Free Trial (in Beta). Do let us know your feedback or any queries which you may have on this forum.
Although I work for IBM, the views expressed are my own and not necessarily those of IBM and its affiliates.
