Posted by: Dr. Werner Hopf
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added and updated.
SAP’s Tom Kurtz, VP Global Strategic Initiatives, SAP HANA Services, and collaborator, Robert Hernandez, SAP’s Director of In-Memory Services, North America, shared an insightful and helpful article on the SAP Community Network on October 18 about determining if and when SAP HANA is right for your organization. They called it “The HANA Journey,” and rightfully so!
The value of HANA is unsurpassed when it comes to faster analytics, modeling flexibility, near real-time data replication, faster reporting and data loading, and many new applications and enhancements. Most of all, it can help optimize the power of Big Data.
However, one area Kurtz and Hernandez didn’t address was managing and maintaining all of the data that is created, which is key to deriving a return on investment on HANA platforms. In their defense, the article was about determining when or if HANA is the right choice for an organization and how to approach the implementation; but, part of the ‘roadmap’ must also be analyzing infrastructure and looking at how to efficiently use and manage the HANA platform to maximize the investment. Thus, I’d like to offer an addendum to the roadmap laid out in their article.
With Data, Less can be More
While the value of HANA is faster processing, reporting and analytics – an advantage that can provide an important competitive edge – one downside which must be accounted for is escalating data growth. Let’s face it: “he who has the most data” is not guaranteed to succeed. In fact, the only guarantee when collecting data without a management strategy is rapidly increasing Total Cost of Ownership and slower processing speeds.
The key to ensuring optimal performance is to reduce and organize the data that populates your system. Accomplishing this objective requires the implementation of an archiving and complementary data management strategy. At the core of this approach is a robust data archiving plan, which will also help ensure predictable TCO for newer in-memory technologies that, while more capable, are already acknowledged as more costly.
With so much data, determining the starting point for tackling a data volume management project can be daunting. Start with recognizing that certain data is more valuable than other information, preferably prior to moving anything to HANA. Understanding the specific value that different data types have for your organization is a cornerstone of archiving and an important facilitator to more effectively harness and maintain a lean and effective HANA solution.
Benefits of Nearline Storage
Dolphin has seen a number of enterprises achieve success in moving large amounts of static data to a lower-cost, high-performance nearline storage (NLS) environment, complementing both the SAP NetWeaver Business Warehouse (SAP NetWeaver BW) environment and SAP HANA’s in-memory architecture. Even better: during a carefully planned implementation, NLS can be utilized before HANA on the current platform to achieve immediate benefits.
NLS is a cost-effective, scalable option for storing large volumes of data. It is a critical component of a data archiving strategy that supports compliance to further ensure the right balance between performance and storage costs. Many CIOs understand the value of the transparent access to data that NLS provides, and its ability to maintain predictable database size and growth through archiving processes.
A major energy provider running HANA stand-alone and BW on HANA found that although HANA offers compression, the payback would be 15 years, or never when considering maintenance costs and upgrades, without adding NLS infrastructure. However, with nearline and an archiving strategy in place, the payback on HANA is now calculated at an astonishing 2.4 years.
Harness the Full Potential of Big Data
With advances in the ways that Big Data is analyzed almost every day, businesses are at the threshold of incredible insight, but first must create a data environment which will allow the full potential of data to be harnessed. Whether six months or several years down the road from an implementation, for many companies this means formalizing better data volume management processes and adopting data governance capabilities as part of the roadmap for the HANA journey.