On the Road to SAP HANA: Paving the Way
Maximize the Potential Benefits of SAP Big Data with HANA
According to industry analysts, we have entered the age of “Big Data.” Generally, Big Data relates to the fact that today’s business intelligence (BI) systems – like SAP NetWeaver™ Business Warehouse (SAP NetWeaver BW) – are experiencing record levels of data growth from terabytes to petabytes and beyond. The challenge is in maximizing the opportunity for real-time business intelligence while minimizing the impact of exploding data volume on productivity and total cost of ownership (TCO).
SAP Big Data Archiving
The promise of big data applications, even combined with the seemingly endless performance capabilities of SAP HANA, does not negate the reality that turning massive amounts of data into insightful, real-time intelligence requires a sound data management infrastructure. As more data accumulates in BI and ERP systems, one major issue emerges: input/output performance degradation that slows data access. SAP HANA eliminates these bottlenecks by keeping data in memory, but the extra cost to add sufficient capacity can be higher than expected. From a data management perspective, making the most of the big data opportunity requires the adoption of two key strategies: 1) augmenting data archiving capabilities with nearline storage and 2) re-architecting the business warehouse (BW) data model for lean, flexible, organized “views” of information that serve up agile reporting without increasing administrative overhead. Dolphin offers a compelling strategy to help companies meet those goals, achieve significant savings, performance improvements and lay the foundation for leveraging SAP HANA – the vehicle for truly maximizing the potential benefits of big data – now and in the future. Dolphin is the leader in providing business performance improvement solutions for SAP environments. Our team has the expertise to help you enter the era of Big Data and build your bridge to SAP HANA.
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Maximize SAP HANA™ PerformanceMaximize SAP HANA™ Performance Cont.On The Road To HANA SAPBenefits of SAP Big Data Archiving StrategyCase Study: Large West Coast Energy Company
As we know, “big data” is everywhere. On one hand, Big Data relates to the fact that today’s business intelligence (BI) systems – like SAP NetWeaver® Business Warehouse (SAP NetWeaver BW) – are experiencing record levels of data growth from terabytes to petabytes and beyond. SAP® is reporting more than 2000 customers already going to or using HANA, the company’s in-memory, column-based appliance. The real challenge of big data is figuring out how to maximize the opportunity for never- before-realized real-time business intelligence while minimizing the impact that exploding data volume has on productivity and keeping the cost of performance down. Dolphin offers a compelling suite of solutions to help you achieve a lower total cost of ownership (TCO), significant savings and high performance for applications on HANA and even prior to its implementation. From a data management perspective, closing the gap from where most companies running SAP applications are today to their implementing HANA can be accelerated by the adoption of two key strategies. One is augmenting your data archiving capabilities with nearline storage. The other is re-architecting your BW data model for lean, flexible and organized “views” of information that serve up agile reporting without increasing administrative overhead.
The promise of big data applications and the seemingly endless performance of HANA do not negate the reality that turning massive amounts of data into insightful real-time intelligence requires a sound data management infrastructure. As more data accumulates in ERP and BW systems, one major issue emerges that bogs down data access: I/O performance bottlenecks within traditional storage technology. HANA eliminates the performance bottleneck by keeping data in memory; however the extra cost to add sufficient capacity can be excessive.
A cost-efficient approach to this challenge and a foundational piece to maximizing what SAP HANA offers is an archiving strategy that includes the ability to move large amounts of static data to a low-cost, high-performance nearline storage (NLS) environment that complements the in-memory SAP HANA architecture. NLS is an inexpensive, scalable option for storing large volumes of data. When adopting an archiving strategy with NLS, it is critical to segregate frequently used, “high-value” information from data that provides lower business value, regardless of environment or current (or planned) platform. Data archiving is an essential part of this data management process. A nearline solution ensures the right balance between performance and storage costs. It also provides the ability to maintain size and growth of production environments through archiving processes, while protecting data for business and audit requirements. The nearline environment optimized with analytics provides the foundation for a reliable and inexpensive information management strategy. It can also serve as an analytics and indexing engine for archiving in transaction-oriented systems, such as SAP ERP, CRM, SRM, etc. Dolphin’s nearline solution delivers the necessary throughput to effectively archive high transaction volumes in these systems.
Businesses are faced with determining how to best prepare for HANA regardless of when they plan to move in that direction. Whether your IT organization is considering this journey or the decision has been made, you may feel the need for a check list on how to proceed and what pitfalls to avoid on the road to SAP HANA. Dolphin has a “roadmap.” Most of us are aware that SAP HANA utilizes disk space on a “pay-as-you-grow” basis and because in-memory blades are rather expensive, cost becomes a consideration. Keeping databases as lean and mean as possible will be a major priority for businesses pursuing a HANA strategy. Even with commodity servers, the performance and scalability that SAP HANA offers can carry a considerable price tag. While it is inevitable that companies will pursue SAP HANA because of the clear performance advantages gained by keeping data in memory, it is important to understand that the process is more involved than flipping a switch, especially around the critical aspects of optimizing performance and database size. To begin, evaluate current needs for streamlining infrastructure and accessing data. This first step identifies key performance indicators (KPIs) for system performance, and specific areas for cost reduction, management and avoidance. It also allows organizations to more fully understand their environments and understand what could be. Another important consideration when migrating to SAP HANA is a comprehensive database assessment; albeit, a HealthCheck. Dolphin offers a SAP database HealthCheck which is a proactive audit that will help safeguard against costly system down time and ensure that the in-memory infrastructure remains lean and stable. It incorporates standard SAP reports and specifically designed utilities to identify areas that need attention. Based on assumptions and a series of non-intrusive transactions from the system, data focusing on opportunities in three KPI areas can be extracted. These include:
- System performance
- Size and growth of production environments
- Cost reduction/containment
The resulting report will provide an overview of the health of the database on a monthly basis.
- Increased Performance: including smaller database size, faster data load, queries, back up, refreshes and upgrades
- Sustainable & Predictive Growth: including reduced storage and server growth
- Reduced Total Cost of Ownership: including operational, system infrastructure and administrative savings
The strategy was to migrate the entire BW platform to SAP HANA for BW to achieve faster analytics and reporting of big data. One area of concern was the size of the current BW database, the volume of database growth and how to keep it in check going forward. They also wanted to contain costs to lower TCO. Solution
Dolphin provided a data archiving strategy and nearline storage infrastructure with PBS BW Nearline storage and analytics. Results
- Reduced database growth by 50% thereby keeping database size constant
- Stabilized cost of database growth
- Provided data for analysis at a lower cost without performance loss
- Savings from NLS is directly proportional to the memory reduction on BW HANA
- Easy to maintain and keep BW HANA objects up-to-date in the NLS system
- Lower Total Cost of Ownership
Download “A Strategic Approach to Data Archiving” White Paper