How To Manage Data In A Business

Transcription

1 Improving Performance by Deploying Business Suite with Advanced In-Memory HANA Technology Leveraging New -based Capabilities to Optimize Costs, Performance, Data Availability, and User Satisfaction

2 Overview Businesses today are facing the challenge of coping with everincreasing levels of data while simultaneously needing to maximize the opportunity of leveraging that information to improve responsiveness to customers and to gain competitive advantage in their markets. For many companies, the combined pressure of effectively handling more data and meeting shorter action-timeframes is outstripping the capabilities of conventional hardware/software data management architectures. The traditional approach of maintaining large data repositories that are separated from the actual processing hardware is often becoming a primary chokepoint within the information flow. At the same time, companies need to preserve their existing investments in the myriad of userfacing processes for handling transactions, reporting, managing information, compliance, analysis, etc. Basically, companies need a solution that can speed the internal flow and real-time responsiveness of internal information processing while maintaining compatibility with all of the database structures and user-facing systems currently in place. Coming at the problem from long experience in both enterprise management and user-facing systems, has developed an innovative approach using the HANA architecture by moving the entire data set into processor memory space. This fundamental shift eliminates the traditional separation between where data is and where it is processed. The result is a dramatic increase in system responsiveness while maintaining transparent compatibility with existing database structures and userfacing systems. HANA enables virtually any database ( or non-) and associated applications, such as ERP, CRM, or other Business Suite functions, to be transparently migrated to in-memory mode, thereby significantly boosting performance without requiring changes to the existing user processes or business procedures. The immediate payoff is much higher performance for current applications with additional benefits over the mid to long term from improved hardware utilization and system migration options. This paper offers an overview of trending information management challenges and provides an indepth look at how the HANA inmemory architecture can be leveraged to improve performance within a variety of different implementation scenarios. ERP / CRM / PLM /SCM NetWeaver ERP / CRM / PLM /SCM NetWeaver Any Database Hana Page 01

3 Need to Manage Escalating Volumes of Big Data Most people have heard the term Big Data used as an opportunity area, and it is; but only if the challenges of managing it can be addressed. Big Data can be defined as data sets that are beyond the ability of commonly used software tools to capture, manage and process the data within acceptable elapsed timeframes. Mobile GPS Planning Tweets CRM Data Customer Transactions Sales Orders Demand Planning Velocity Things Instant Messages Opportunities Inventory COPA Data Speed Emalis The ability to process these large amounts of information is the main attraction of big data analytics, however it requires an architecture that can seamlessly scale both data storage and querying processes without compromising performance. Most companies already have accumulated large amounts of data but lack the capacity to process it in a unifying, comprehensive and timely manner. Page 02

4 Increasing Variety and Velocity of Data In today's world, data rarely presents itself in a form that is perfectly ordered and ready for processing. A common theme in big data systems is disparate data generated from a wide range of sources that is inherently diverse and doesn't fall into neat relational structures. In addition to internally created transactions where the company has some control over structure, other relevant data is also pouring in from sources such as social media, text messaging, SaaS services, images, videos, EDI partners, and many more. In addition, the velocity with which data flows into the organization and the criticality of real-time processing is escalating right along with higher volumes and more variety of data. Simply capturing the data and storing it for later analysis is no longer sufficient for maintaining a viable position. The speed of a system's outputs have become critical to success or failure in today's dynamically changing and interrelated global markets: The tighter the feedback loop, the greater the competitive advantage. Expectations for Immediate Access to Information At the same time that the volume, variety and velocity of data inputs are skyrocketing, the expectations for immediacy are growing within all user groups, from frontline users to management to executive level decision makers. Based on our universal online Cost-effective Management of Large Data Volumes Current and Complete Information??? Immediate Answer to any Question experiences of having virtually any type information at our fingertips, whenever we want it and wherever we are, today's users also expect the same level of responsiveness from their business systems. The proliferation of seamless mobile access on a variety of handheld devices is also fueling users' anticipation of information immediacy and availability without regard to geographic or platform constraints. User adoption and commitment are key factors for the success of any business system implementation process. Both internal and external users expect their experience with a company's systems to be as responsive and satisfying as the personal systems that pervade their lives and which have already set the bar at a very high level. The ability for an organization to meet all of the above challenges is fundamentally dependent on how tightly they are able to marry together vast amounts of data with the processing systems needed to turn that data into timely and actionable information. Page 03

5 Evolution of HANA In-Memory Architecture Basically, HANA has evolved from an innovative convergence of 's advanced business intelligence reporting tools and a new approach to inmemory data warehouse management. Over the past few years, the key enabling technologies have been developed, proven out in actual real-world successes and now have been brought together within a fundamentally game-changing, in-memory architecture. The first building block in the process was NetWeaver BW Accelerator (BWA) that delivered radical improvements in query performance through sophisticated in-memory data compression and horizontal and vertical data partitioning, with near zero administrative overhead. The second key element was the introduction of BusinessObjects Explorer in 2009, which provided an advanced a web-based search and exploration application to explore and search through business information. By selecting from various values, users can match the data set to specific KPIs and output formats to address particular business questions. As requirements evolve or change, users can easily switch chart formats, sort, rank and export the presented data depending on specific needs. Bringing It All Together for Unified, In-Memory High-Performance Operation Building on HANA's proven analytics capabilities, the next major leap forward was to bring all of the data storage, processing and exploration together within the unified HANA in-memory architecture. This opened new possibilities for dramatically improving system performance as well as streamlining the relationships between content, applications and real-time business analytics. BusinessObjects and other Applications ECC in-memory computing engine BWA Accelerate BWA BO Explorer Accelerated Version Self-Service BI rd 3 Party BW HANA BusinessObjects Data Services HANA In-memory platform Real-Time Analytics Content / Applications Accelerated BI Page 04

6 Performance Advantages of In-Memory Operation Combining both the live operational database and the processing resources within a unified, in-memory architecture eliminates the need for passing queries to external storage devices, thereby enabling core processing resources to directly access any needed data in real time. This ground-breaking in-memory database approach enables HANA to deliver results across all five dimensions of decision processing: Breadth (analyze big data from multiple sources) Depth (ask complex questions on granular data) Speed (receive fast, interactive responses) Simplicity (eliminate the need for data preparation) Real time (run real-time queries on real-time data) Some of the unique advantages of in-memory technology are the ability to store massive amounts of compressed information within main memory, to optimize use of multiple cores and parallel processing, and to move some data intensive calculations from the applications layer into the database layer for even faster processing. It also eliminates the need for and costs and delays associated with unnecessary data duplication. Since all of the detailed data is available in main memory and processed on the fly, there is no need for separately aggregated information and materialized views, thus fundamentally simplifying the architecture and reducing latency, complexity and cost. In-Memory Cache V S Transact Analyze Accelerate Transactions + Analysis directly in-memory Page 05

7 The HANA architecture is designed to maximize implementation flexibility and interoperability within existing software systems and to leverage optimal use of hardware investments. By building in a high level of agnostic capabilities with regard to databases, operating systems and data warehousing methods, HANA can be readily adapted to virtually any existing data strategy. As shown below, pre-defined HANA implementation models address scenarios ranging from no data warehouse to -based ERPs, non- ERPs and hybrid situations. NetWeaver Business Warehouse capabilities provide an agnostic unifying capability for implementing complex Type 5 and Type 6 scenarios. Enterprise Systems Datawarehouse Strategy Implementation Process and Interoperability No DWH Non- DWH Non- - ERP - ERP & Non- Type 1 Type 2 Type 3 Type 4 Netweaver BW Type 5 Netweaver BW & Non- DWH Type 6 To support a smooth and fast implementation, Idhasoft and have defined a structured three-step approach to updating any non-hana database as well as the target data system to a matching level of Netweaver and then seamlessly exporting/importing between the systems. ERP / CRM / PLM /SCM NetWeaver Any Database ERP / CRM / PLM /SCM NetWeaver Hana Page 06

8 Integrating HANA into Overall Business Objectives In addition to offering a high degree of implementation flexibility on the database and processing side, HANA is also designed to be highly agnostic with regard to user-side business intelligence capabilities. Some of the key HANA features include: In-Memory software for range of hardware platforms (HP, IBM, Fujitsu, Cisco, Dell) Data modeling and data management Real-time data replication BusinessObjects Data Services ETL capabilities from Business Suite NetWeaver Business Warehouse Support for 3rd party BI and other systems The combination of these HANAenabled capabilities results in the following major advantages: Analyze information in real time Unprecedented speeds for large volumes of non-aggregated data Ability to create flexible analytic models on the fly for real-time and historic data Minimize need for data duplication Optimize hardware resource usage Enable finer-gradient hardware performance tuning (e.g. memory vs. disk) Provide foundation for new categories of applications (e.g. real-time planning, simulation, etc.) that significantly outperform currently available alternatives. After migration, the HANA based target in-memory data system maintains full compatibility with all of the company's existing back-up policies, security and recovery strategies, whether synchronous, asynchronous, RAID, mirroring, etc. Businessobjects BI Solutions HANA Studio Applications By implementing a highperformance in-memory processing capability that is tightly integrated with hardware resources and highly interoperable with surrounding software systems, HANA completely changes the paradigm for making the best use of any data for any purpose within the overall business. Other Applications Information Composer HANA Database Calculation Engine Real-Time Data Replication HANA Row & Column In-Memory BusinessObjects Data Intergrator Non Data Sources Page 07

9 Key Considerations for Success Over the course of many system implementations, Idhasoft has become very aware that every company's specific requirements are unique. As with all of our solutions technologies, we've approached the HANA architecture with an objective of tailoring a variety of implementation scenarios and system options that serve as building blocks for adapting the right elements to meet current requirements as well as building in a growth path for future needs. At the same time, the conversion to HANA also lays a solid and extensible foundation for significantly enhancing business intelligence capabilities, real-time decision making and optimal usage of hardware resources going forward. In particular, as multi-core hardware processing capabilities and memory costs continue on very positive cost/performance curves, making the shift to a HANA-based, in-memory strategy today is expected to deliver considerable on-going ROI dividends over the mid to long term. Any successful ERP, data warehousing, business intelligence, or other software design project requires a disciplined approach with careful attention to the following areas. Up-Front Planning Top-down Design Roles & Responsibilities Definitions Detailed Process Improvement Definitions Establishment of Data Migration Path Pre-Live Testing & Training Step-by-Step Go-Live Process On-going Monitoring and Optimization By creating a forward-looking data strategy that ensures effective leverage of diverse data sets from all sources and the internal tools for real-time analysis and actionable decision processes, companies that master the emerging discipline of big data management can stake out a superior competitive position. The HANA in-memory architecture offers an excellent opportunity for reaping major performance results in the management of the big data challenges facing companies today. It also creates a solid foundation for effective scaling of data management resources and enablement of new applications to meet the impending big data challenges of tomorrow. The primary goal of any Idhasoft HANA implementation is to quickly deliver the very significant performance improvements and data exploration capabilities from inmemory data while providing maximum transparency between the current system and the new HANA based target system. About Idhasoft: Idhasoft Inc. is a global leader in strategic technical solutions, gold channel partner and 2010 Business All-in-One Partner of the Year-USA, providing innovative end-to-end business solutions to companies around the world. Idhasoft founding vision is to serve the SMB marketplace with a unique blend of business solutions and services. We help our clients drive efficiency, improve profitability and build a lasting competitive advantage. Idhasoft capabilities and services include the following: 100% commitment to solutions, services and technologies Gold All-in-One Solution Provider and Premier Implementation Partner Partner Center of Excellence Certified master VAR Certified Industry Specific Solutions Dedicated Practices- ERP, CRM, SRM, SCM, BI and Net Weaver/Portals Senior experienced consulting team with both industry and experience Invited expert each year at ASUG, PHIRE and other conferences State-of-art Solutions Center with Ramp-up Applications Idhasoft's pre-configured Industry and Solutions templates Our consultants work closely with COE and Product Development Page 08

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