Unfortunately, with new technological advances comes the mistaken idea that they must also be the long sought-after “silver bullet” that makes all problems go away. In this second of a three-part series on Moving Your Data Infrastructure to the Cloud – Things You Should Know, let’s discuss and dispel these myths associated with moving your data infrastructure to the cloud:

  1. Just throw all your data into the cloud and start analyzing it – no design or architecture is needed. Nope – sorry, not going to happen. Your previous on-premises data and access methods will not just magically be understood and usable in the cloud. You will just make a data dump or data swamp in your cloud implementation. And that is simply a big waste of money, time and effort. An analytics environment is planned and architected so that all users can understand and use it. The manipulation of the data and its lineage must be documented; its components and data schemas must be known so the analytical personnel can easily use the environment.
  1. Just forklift all your data warehouse into the cloud – there is no need to redesign it. Negative – just not so. Your multi-year-old data warehouse has grown some barnacles along the way or is in need of being updated with new requirements. This is your chance to blow the dust off, remove inefficient processes, wasted space from unused assets (old reports, visualizations, analyses no longer used), and excess workspace for users who no longer use the environment. This is a perfect opportunity to automate many processes to make them far more efficient. It is also a time to reassess the original requirements, perhaps bringing in new ones that are waiting in the wings.
  1. Just by changing to a cloud deployment, your implementers will be more productive. Again no – migrating to the cloud will most likely change your entire process and methodology. Infrastructure gains do not necessarily equate to productivity gains if the team continues to develop and operate using the same outdated means, methods or processes. Productivity gains may actually be negative at first if moving to the cloud invalidates current methodologies and/or productivity tools. The team will need time to retool and learn the new methodologies and processes. Then their productivity will improve.

It would be wonderful if moving your data infrastructure to the cloud was as easy as selecting and purchasing a cloud data platform. In my final installment in this three-part series, I’ll discuss how automation can help you bridge the gap and ensure you begin to reap the benefits of cloud data warehousing sooner. 

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. Alternatively, if you missed my first blog post, you can read it here.


Dr. Claudia Imhoff, Ph.D., is an internationally recognized expert on analytics, business intelligence, and the architectures to support these initiatives. She has co-authored five books and more than 150 articles on these subjects. Dr. Imhoff is the president of Intelligent Solutions, Inc. and Founder of the Boulder BI Brain Trust (BBBT), a consortium of internationally recognized independent analysts and experts.