Hybrid Data Warehousing – The Best of All Worlds

By Wendy Lucas, 

When it comes to data warehousing, organizations are progressing along the maturity curve at their own individual pace.  Today, most organizations have some form of warehouse and business intelligence in place, or recognize the need for it and the benefits it can drive.  But we all know that technology doesn’t stand still.  And so, you are now faced with a new step in your progression towards data warehouse maturity – the move to cloud.

Building Momentum

Cloud applications started with a fairly narrow focus.  A few years ago, you may have viewed the cloud as a viable platform for mobile applications or just a way to keep your contacts synchronized between your devices (by the way, that is still my favorite cloud use case).  IT organizations have begun looking to the cloud as a way to cut costs, but the strong momentum behind cloud adoption indicates there is more to it than that!

According to a recent IBM Tech Trend study, cloud adoption is up 92% since 2012.  The same study shows that organizations identified as pacesetters are 10x more likely to increase workforce efficiency with the cloud, 5x more likely to enhance communication and collaboration and report 4X better customer experience.   Pick your research outlet and you will find similar statistics.

One of Forrester’s top cloud computing predictions for 2015 is that “hybrid cloud management gets real” in terms of having the tools to allow you to manage across multiple on-premise and cloud platforms.

I believe that cloud use cases are the driving factor behind the growth and momentum of cloud technologies. Data warehousing on the cloud is no exception, where the general need is to deliver analytics to the organization faster.  Let’s explore specific data warehouse use cases.

Use case 1: development, testing, prototyping and sandboxing

A safe place to start might be establishing a cloud environment for warehouse development and testing.   Do you need the ability to test key functions like ETL processes or analytic applications without the need to setup more costly infrastructure on-premise?  Why not consider testing in the cloud? Perhaps you need an environment in which to do quick prototyping or sandboxing?   Whether it’s an environment that is a temporary or persistent, a cloud data warehouse instance can be quickly stood up and used for prototyping and sandboxing with very minimal cost.

Use case 2: Do more with less when when you are at capacity

Organizations are also considering cloud as a way to expand capacity of their existing data warehouse.  In the context of the logical data warehouse, data assets can reside on the cloud to serve up specific types of data to specific applications.

Use case 3: self-service analytics

Organizations can use the cloud as a data layer for self-service business intelligence and analytic capability, especially for applications that need data that’s already in the cloud, for example if your marketing organization need to analyze unstructured social media data.

Both IT and the line of business can benefits from these and other use cases.  IT organizations are able to reduce infrastructure costs and simplify budgets by shifting capital expense to an operational expense model.   Perhaps most importantly, the flexibility and agility of a cloud option provides faster time to insight for end users who need insight immediately.

What should I move to the cloud?

If cloud is so great, why not move everything to the cloud?  The reality is there are some applications that will remain on-premise for some time to come (or forever).  Systems that require large amounts of on-premise or sensitive data or that are generating large volumes of data may not be easily moved to the cloud.  It may make sense to leave these in the on-premise data warehouse systems that have matured over decades and are fulfilling the needs of those applications quite well.   But like discussed above, you may not want to incur capital expenditure or longer deployment times for things like data marts, development and test environments or analytics for data already in the cloud and these represent ideal opportunities to use a cloud data warehouse

There isn’t a one-size fits all answer, which is why hybrid environments make the most sense.  A hybrid environment can provides the best of all worlds – the ability to keep your large, on-premise warehouses in place, allow compliance with security and regulatory reporting, and fulfill the needs of traditional reporting and analysis.  , All of this is done while continuing to reduce costs and increase flexibility and speed of deployment for new applications in the cloud.  Just like most things, its best to pick the right tool for the job.

What tools can help me get there?

IBM data warehouse solutions offer the breadth and depth of capabilities required to effectively support a hybrid environment.   On cloud, IBM dashDB is our exciting new data warehouse and analytics as a service that concluded the beta program for Cloudant and enterprise plan on December 18th and is now generally available.  It pulls together the lightning fast performance of DB2 with BLU Acceleration with market leading in-database analytic capabilities from Netezza.  Think of it as the combination of the fastest data warehouse and analytic platform, combined with the flexibility and agility of the cloud.  dashDB will continue to evolve in a way that preserves analytic and application portability between the cloud and on-premise systems.  Most importantly, as you modernize with a hybrid cloud approach, the enterprise plan is available to support you at scale.

And of course on premises, IBM offers DB2 with BLU Acceleration as a software-only solution or the IBM PureData System for Analytics as a ready to go data warehouse appliance. Putting these pieces together, you can support your hybrid data warehousing needs with proven technologies that offer the best of all worlds.

For more information, please visit dashDB.com.

About Wendy,

Wendy Lucas is a Program Director for IBM Data Warehouse Marketing. Wendy has over 20 years of experience in data warehousing and business intelligence solutions, including 12 years at IBM. She has helped clients in a variety of roles, including application development, management consulting, project management, technical sales management and marketing. Wendy holds a Bachelor of Science in Computer Science from Capital University and you can follow her on Twitter at @wlucas001

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