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Analytics is now mainstream, helping companies of every size in ever industry drive business, streamline processes and improve their customer relationships. To reach its full potential, however, requires working in real-time with a platform like SAP HANA.
Companies around the world are using analytics, and not solely larger enterprises. In IDG’s 2016 Enterprise Data & Analytics Research, 69% of the organizations surveyed had either implemented analytics projects or were planning to do so. SMB investment in analytics more than doubled between 2015 and 2016.
It doesn’t matter whether you’re involved in retail, construction, logistics, risk-management or IT; capturing and analysing data can help you optimise your operations, cut costs and push revenues up. Analytics can help you find the bottlenecks in your supply chain or opportunities for cross-selling and promotion. It can help you remove slack from business processes, prioritise investments or understand risks.
Analytics can help your business respond faster to market trends, and even predict changes in customer behaviour before they occur. These applications mean as much to smaller enterprises as to large ones.
Deploying analytics involves preparation; looking at the available technologies, their benefits and costs. However, not all analytics platforms work in the same way, with some best suited to mining vast data warehouses for insight and others focused on predictive modelling – spotting patterns in existing data to suggest what might happen should a similar pattern emerge.
Arguably, however, the real power of analytics emerges when you work in real-time, leveraging the structured and unstructured data moving through your systems to get minute-by-minute insights. As Irene Hopf, Global Thought Leader SAP Solutions at Lenovo says, ‘working in real-time enables enterprises to predict trends or shortages rather than react to them. It delivers the speed required to seize opportunities as they arise.’
This is where the advantages of SAP HANA as an analytics platform become compelling. An in-memory computing platform designed to work on large datasets in real-time, it can also dramatically reduce the pain and time involved when working with existing data. ‘Real-time analytics platforms like SAP HANA can deliver intelligence at the speed business moves’ says Irene Hopf. ‘That makes it an important platform for Lenovo, both as a key SAP partner and customer, as well as the leading manufacturer of optimised infrastructure.’
Why is SAP HANA so effective? Because the data can be operated on entirely in memory, without the need to move it back and forth between memory and storage, SAP HANA can mine useful insights from real-time data streams or answer sophisticated queries in a fraction of the time required by more conventional architecture – in seconds or minutes, not hours. In fact, an SAP BW edition for SAP HANA benchmark on Lenovo hardware  in February 2017 saw a SAP HANA system tackling over 71 complex queries per minute on a 1.3 billion record dataset for over an hour.
Building an infrastructure that supports and accelerates SAP HANA takes specific expertise. Not only does SAP HANA have rigorous requirements in terms of processor, storage, memory and network hardware, but balancing raw compute power with low latency RAM and high-speed storage is something of an art. That’s why Lenovo has spent years developing and tuning its X6 Series servers to run SAP HANA as it’s meant to be run, with the latest models deploying the full power of Intel’s latest Xeon E7 processors and Lenovo TruDDR4 RAM. This expertise has helped Lenovo become a leader in SAP HANA deployments worldwide, not to mention the provider of SAP HANA servers used internally at SAP.
Whatever your business, whatever your industry, investing in analytics can help enhance efficiency and the bottom line. By planning for real-time analytics now, using hardware built and tuned for the specific requirements, you’ll be even better equipped for future real-time and predictive intelligence applications; applications that could make all the difference in an increasingly competitive world.
 IDG Enterprise, 2016 Data & Analytics Research, July 2016, http://www.idgenterprise.com/resource/research/tech-2016-data-analytics-research/
 Database server: Lenovo System x3850 X6, SAP HANA 1.0, SuSE Linux Enterprise Server 11, 4 processor / 96 cores / 192 threads, Intel Xeon Processor E7-8894 v4, 2.40 GHz, 64 KB L1 cache and 256 KB L2 cache per core, 60 MB L3 cache per processor, 2048GB main memory. Total Runtime of Data Load/Transformation: 14,939 seconds; Number of Navigation Steps per Hour: 4,237 at 215,902,670, 995 records; Total Runtime of complex query phase: 154 seconds. Operating system: SuSE Linux Enterprise Server 11; database: SAP HANA 1.0; technology platform release: SAP NetWeaver 7.50
The SAP BW edition for SAP HANA Standard Application Benchmark performed on January 30, 2017, byLenovo in Morrisville, NC, USA, with a total of 1,300,000,000 initial records, was certified by SAP on behalf ofthe SAP Benchmark Council on February 7, 2017
For more details see http://www.sap.com/benchmark