SAP Standard for Data Volume Management

Transcription

1 SAP Standard for E2E Solution Operations Document Version: SAP Solution Manager 7.1

2 Typographic Conventions Type Style Example Description Words or characters quoted from the screen. These include field names, screen titles, pushbuttons labels, menu names, menu paths, and menu options. Textual cross-references to other documents. Example EXAMPLE Example Example <Example> EXAMPLE Emphasized words or expressions. Technical names of system objects. These include report names, program names, transaction codes, table names, and key concepts of a programming language when they are surrounded by body text, for example, SELECT and INCLUDE. Output on the screen. This includes file and directory names and their paths, messages, names of variables and parameters, source text, and names of installation, upgrade and database tools. Exact user entry. These are words or characters that you enter in the system exactly as they appear in the documentation. Variable user entry. Angle brackets indicate that you replace these words and characters with appropriate entries to make entries in the system. Keys on the keyboard, for example, F2 or ENTER SAP SE or an SAP affiliate company. All rights reserved. Typographic Conventions

3 Document History Version Date Change > First version created Document History 2014 SAP SE or an SAP affiliate company. All rights reserved. 3

4 Table of Contents 1 SAP Standards for E2E Solution Operations Control Center Approach Overview of the Standard for Data Volume Management Data Volume Management and Application Lifecycle Management Benefits Challenges Basic Architecture Technical Aspects Interfaces Information Lifecycle Management Data Volume Management Tools Lifecycle of Data Volume Management Plan Data Volume Management Strategy Organizational Preparation Assessment Scoping Build Blueprint Realization Functional and Integration Tests Go-Live Run Data Volume Management Operations Executing Jobs Maintaining Documentation Reorganizing Databases Troubleshooting Optimize Continuous Improvements Driving Continuous Improvement Quality Assurance Tasks Quality Targets and KPIs Training Expert Guided Implementation Sessions Continuous Quality Check (CQC) SAP Service for Data Volume Management More Information Enterprise Support: Value Map for Data Volume Management SAP SE or an SAP affiliate company. All rights reserved. Table of Contents

5 Table of Contents 2014 SAP SE or an SAP affiliate company. All rights reserved. 5

6 1 SAP Standards for E2E Solution Operations IT organizations face new challenges every day as they attempt to remain effective and future safe while also keeping costs for day-to-day operations as low as possible. They are also being challenged more than ever to demonstrate their value to businesses. Therefore, it is important to optimize the day-to-day tasks that have less obvious business value and to use KPI and benchmark-based reporting to make IT processes more visible, demonstrating the real value that IT can provide. In order to minimize the costs of IT, it is necessary to standardize and automate IT processes end-to-end (E2E) without reducing the SLAs required by the business, such as stability, availability, performance, process and data transparency, data consistency, IT process compliance, and so on. Based on the experience gained by SAP Active Global Support (AGS) while serving more than 36,000 customers, SAP has defined process standards and best practices to help customers set up and run E2E solution operations for their SAP-centric solutions. The Build phase of SAP best practices supports a Build SAP Like a Factory approach, consisting of the following processes: Custom code management Change, test, and release management Incident, problem, and request management Solution documentation Remote supportability During the Run phase of a solution, adapting your IT infrastructure to a Run SAP Like a Factory operation impacts both application operations and business process operations. Therefore, operations processes, such as technical monitoring, end-to-end root-cause analysis, technical administration, and data volume management need to be optimized to achieve state-of-the-art application operations. In business process operations, the same applies to business process and interface monitoring (including performance optimization), data consistency management, and job scheduling management. Quality management processes and tasks need to be established throughout the lifecycle to guarantee continuous improvement of the end-to-end operations processes while simultaneously ensuring the flexibility needed to react to changing requirements SAP SE or an SAP affiliate company. All rights reserved. SAP Standards for E2E Solution Operations

7 Figure 1: Organizational model for solution operations This figure shows an organizational model for solution operations that aligns SAP best practice topics and E2E standards with SAP's control center approach. The Operations Control Center executes and controls the Run SAP Like a Factory processes, while the Innovation Control Center ensures optimal custom code management and a smooth transition to production with integration validation procedures. SAP connects to these control centers from the Mission Control Center to ensure that professional support is available to the customer. The following Application Lifecycle Management (ALM) functions are not provided directly in one of the control centers because they must be handled across different areas: Change, test, and release management Incident, problem, and request management Solution documentation Remote supportability The quality management methodologies are an essential part of SAP's Advanced Customer Center of Expertise (CoE) concept and ensure that the KPI-driven processes are continuously improved across all processes and teams. In addition, the quality manager roles ensure consistent and value-centric reporting to the business and management. This unified reporting platform is known as the Single Source of Truth. 1.1 Control Center Approach The Operations Control Center (OCC) is the physical manifestation of the Run SAP Like a Factory philosophy. The OCC allows for automated, proactive operations, which simultaneously reduces operational costs while increasing the quality of IT services, leading to improved business satisfaction. The OCC also drives continuous improvement of business processes and IT support. To achieve these goals, it relies on a close interaction with both the Innovation Control Center (ICC) and the SAP Mission Control Center (MCC). SAP Standards for E2E Solution Operations 2014 SAP SE or an SAP affiliate company. All rights reserved. 7

8 Figure 2: Interaction Between ICC, OCC, and MCC The OCC is a central IT support entity at the customer site, which monitors the productive SAP environment as well as important non-sap applications. During operation, the OCC requires a workforce of 2 full-time equivalent (FTE) per shift to ensure that incidents are detected and resolved as quickly as possible. The OCC is equipped with large screens that display the status of business processes, IT landscape components, as well as exceptions and alerts. If problems occur, you use a video link to get live support from SAP and partners. The customer usually sets up the room with assistance from SAP Active Global Support (AGS). The customer is responsible for managing the OCC and the team of technical and functional IT operators who act on the alerts. The OCC is most effective when closely integrated with other IT processes, such as IT Service Management (ITSM) and Change Management. Central monitors and dashboards based on application and business process operations display the current status of business and IT-related processes. This data can also be used to drive continuous improvement. An effective system monitoring and alerting infrastructure is fundamental to the success of an OCC SAP SE or an SAP affiliate company. All rights reserved. SAP Standards for E2E Solution Operations

9 Figure 3: OCC Concept The OCC is most effective when closely integrated with other IT processes, such as IT Service Management (ITSM) and Change Management. Central monitors and dashboards based on application and business process operations display the current status of business and IT-related processes. This data can also be used to drive continuous improvement. An effective system monitoring and alerting infrastructure is fundamental to the success of an OCC. For Job Scheduling Management, the OCC supervises all background monitoring processes, SAP controls and legacy background operations. It reacts to job monitoring alerts according to predefined error-resolution activities, and triggers follow-up activities for error handling if the relevant task are not completed within a certain timeframe. SAP Standards for E2E Solution Operations 2014 SAP SE or an SAP affiliate company. All rights reserved. 9

10 2 Overview of the Standard for Data Volume Management 2.1 Data Volume Management and Application Lifecycle Management In SAP Solution Manager, Application Lifecycle Management (ALM) processes are supported by control centers. The Innovation Control Center provides transparency on possible improvements to business processes. The Operations Control Centers are focused on optimizing the system and application management of your system landscape. Figure 4: Operations Control Center: General Concept In SAP Solution Manager, the Data Volume Management work center acts as the operations control center for Data Volume Management (DVM). The work center serves as the central point of access for all features related to monitoring and analyzing the data volume in your landscape. These processes are called Data Discovery and Data Profiling. DVM focuses on performing the following tasks: Notifying and managing alerts Performing individual trend analyses for allocation statistics, utilization, and time-based distribution Reporting of continuous improvements Generating best-practice documents (guided self-service) Calculating potential savings Gathering information about executed archiving activities in your system landscape Generating graphical representations of your system and application size and archiving potential SAP SE or an SAP affiliate company. All rights reserved. Overview of the Standard for Data Volume Management

11 Figure 5: Data Volume Management Process 2.2 Benefits The data volume in your landscape grows continuously due to the increasing need for easy access to larger and larger amounts of data. But simply installing additional disks to storage area networks (SANs) and storage subsystems can make the situation worse, for example, by reducing performance or increasing the cost and effort of system management. To manage and reduce this growth, you need to define and implement an effective DVM strategy. The provides an overview of how to set up such a strategy, including how to manage data growth by summarizing, deleting, or archiving data and even how to avoid creating unnecessary data altogether. Implementing this kind of strategy helps you to make improvements for both IT services and business stakeholders in the following areas: Area Improvements IT services Overall better system performance Shorter response times in dialog/batch mode for all employees Reduce downtime, for example, during conversions, migrations, and upgrades Fewer hardware requirements and faster point-in-time recovery Improved system availability Faster and easier upgrades to higher software releases Overview of the Standard for Data Volume Management 2014 SAP SE or an SAP affiliate company. All rights reserved. 11

12 Area Improvements Shorter runtime for backup and recovery Increased transparency Proactive monitoring of data distribution, growth rates, and saving potential Simple presentation of statistical and analytical issues Better supportability Reduced effort for database maintenance Fast and easy implementation of applicable reduction methods Green IT Lower energy costs by reducing hardware resources Business stakeholders Reduced risk Fewer unplanned downtimes due to point-in-time recovery Reduced impact of backups on dialog transactions Fewer resources required Reduced hardware costs for disk, CPU, and memory as well as administration costs (for example, for SAP HANA-based solutions) Increased process efficiency due to better system response times Reduced storage costs due to optimal data lifecycle Increased transparency regarding business growth rate compared to technical landscape growth Basis for decision making and planning of follow up activities Increased data quality Legal compliance Simplified process of meeting data retention requirements and setting up end-of-life scenarios 2.3 Challenges Managing the data volume of your companies presents a number of challenges. In particular, you need to consider the following challenges when deciding on your Data Volume Management strategy: Financial audits and tax requirements are country-specific and so each country poses its own challenges. It is extremely important to take this into account as these requirements can heavily influence a DVM strategy. Example Financial auditing may require you to retain historical data for a certain number of years. Although archiving this data might be an effective way of reducing your data volume, archived data can differ from the original data and can only be accessed by a limited set of transactions. Therefore, you have to determine whether archived data will still meet the requirements for auditing. Any process of destroying data must be legally compliant SAP SE or an SAP affiliate company. All rights reserved. Overview of the Standard for Data Volume Management

13 Size and complexity of system landscapes and exponential data volume growth can lead to an increased total cost of ownership (TCO) and reduced green IT. In large systems it can be difficult to process archiving and deletion jobs without impacting other business-critical processes. To ensure that these challenges do not become critical, SAP recommends creating a thorough DVM roadmap or a project plan, which defines all necessary steps to successfully implement your DVM strategy. 2.4 Basic Architecture Technical Aspects Technical tasks in Data Volume Management require a well-designed DVM infrastructure. This mainly applies to monitoring and archiving tasks. Monitoring DVM monitoring and reporting should be based on a centralized concept for information collection. This means that you must ensure all systems are technically connected to SAP Solution Manager. DVM-related data is collected from each system in the DVM landscape and stored centrally in SAP Solution Manager for evaluation using the DVM work center. Archiving Data archiving involves moving information from the database to the archive files. These archive files can be maintained on any file storage system but SAP recommends storing them on an external content server. Content servers are standalone components that you use to store large quantities of electronic documents in any format. Relevant SAP applications must support the use of the SAP Content Server. You can run a content server with or without Information Lifecycle Management (ILM) enablement. Archiving for SAP Business Warehouse (BW) systems is supported by Nearline Storage (NLS) systems. To find SAP-approved partners for the different technologies, go the SAP Application Development Partner Directory at and search for the following key words to find corresponding partners: BC-AL for storage partners certified for the ArchiveLink interface. These are generally considered the normal content servers. BC-HCS for storage partners supporting the HTTP Interface (HCS = HTTP Content Server) BC-ILM for ILM-enabled storage and NLS for Nearline storage partners for BW systems As part of the Data Volume Management process, you need to perform other technical tasks, such as reorganizing tables and indexes after extensive archiving or deleting, as well as troubleshooting any read or write jobs that failed. Effective housekeeping is also an important part of the process, especially for SAP tables. For more information, see SAP Notes and The DVM work center is mainly used for monitoring and does not initiate archiving activities. Overview of the Standard for Data Volume Management 2014 SAP SE or an SAP affiliate company. All rights reserved. 13

14 2.4.2 Interfaces In the context of Data Volume Management, interfaces exist both on a technical level (between technical systems) and on a business-process level (between applications). The technical level is important for DVM monitoring. Therefore, each system in the scope must be connected to SAP Solution Manager and the data collection must be active. The business-process level is related to functional correctness. On this level, it is important that all interfaces between applications are listed and you need to check whether and how they are impacted by DVM measures (avoidance, summarization, deletion, archiving). It is important to identify whether you have any systems that try to access archived data and whether you have any source systems that deliver data from time frames that were already archived. For example, a BW system might try to upload data that has already been archived in the ERP system or archiving in CRM might send BDocs to update the corresponding documents in ERP. You need to make sure that the various responsibilities on both sides of interfaces are clearly defined, including which teams are involved Information Lifecycle Management Information Lifecycle Management (ILM) is a software package that you implement on top of SAP NetWeaver, which includes features such as retention management and system decommissioning. Data archiving can be used independently of the ILM add-on. You use data archiving to move unnecessary business data from your databases to cheaper long-term storage in an easily accessible archive. Data archiving is one of the prerequisites for retention management implementation. Therefore, data archiving is always included in ILM retention management projects. This means that, although it can sometimes be difficult to see the difference between the two processes, ILM is an expansion of data archiving. SAP ILM supports your DVM processes by providing software, tools, and functions for the following processes: Data archiving and data management Retention management, which involves destroying data after a defined retention period System decommissioning, which ensures compliance with legal and regulatory requirements SAP SE or an SAP affiliate company. All rights reserved. Overview of the Standard for Data Volume Management

15 Figure 6: Overview of ILM As a bare minimum, your DVM strategy should cover data archiving and data management, but you can also include retention management. When considering how long you intend to keep your data before archiving it (usually 1-3 years), you should also consider the length of time you will retain the data in that archive before it is destroyed. This length of time depends on legislative and industry requirements, but is usually between 7 and 15 years. SAP Retention Management provides tools and functions to support the following tasks: Note These tasks apply to both structured and unstructured data. Determining the location of stored data Determining the retention period of data Determining when data can be destroyed Defining policies based on external legal requirements or internal SLAs SAP System Decommissioning provides tools to help decommission legacy systems and move data from both SAP and non-sap solutions into a central ILM retention warehouse. If required, DVM can provide retention management, data destruction, and data archiving functions, but does not provide any system decommissioning functionality Data Volume Management Tools SAP Solution Manager provides some, but not all, of the tools required for Data Volume Management (DVM) processes. Overview of the Standard for Data Volume Management 2014 SAP SE or an SAP affiliate company. All rights reserved. 15

16 Data Volume Management Work Center The most important platform for analyzing and monitoring data is the Data Volume Management work center in SAP Solution Manager. The work center serves as the central point of access for different functionalities and applications related to DVM. It provides the following tools to support a variety of processes: Tools Decision Maker Description Helps you to determine the following key points: Which tables to process first Which objects best fit your defined strategy Which objects show high saving potential Which objects are not yet part of your archiving strategy The Decision Maker analyzes your system based on leading application areas and weighted key figures, for example, archiving activities, data growth, size, and complexity. Only tables of the specified application areas will be considered. Reorganization and Compression Analysis Helps you to determine the following key points: How much space you released during recent archiving activities Whether data compression is a good option in your environment Whether reorganizing your tables or indexes is necessary or beneficial How much space you could save by migrating to SAP HANA The analysis uses key figures related to compressing and reorganizing indexes and tables to simulate potential savings. Impact and References Helps you to determine the following key points: Impact of planned archiving measures on business processes Which processes and steps require testing Which tables and indexes are connected to which business scenarios Affected transactions and reports DVM Planning Dashboard Enables you to perform the following tasks: Visualize archiving potential Determine whether you can configure your own residence times for individual systems and application areas Provide a graphical representation for greater detail regarding annual and monthly data Forecast and Simulation Cockpit Enables you to perform the following tasks: Simulate cost savings after implementing proposed DVM measures Project impact of planned business changes Simulate HAHA migration and determine required space on HANA Service Documents Enables you to investigate your system in more detail. This tool is a Guided Self- Service and can be used without assistance. For more information, see the SAP Help Portal at Application Help SAP Library Application Operations Work Centers in Application Operations Data Volume Management Work Center SAP SE or an SAP affiliate company. All rights reserved. Overview of the Standard for Data Volume Management

17 You perform data archiving and ILM activities locally on each system with the appropriate NetWeaver tools. For example, Archive Administration (transaction SARA) or the Data Archiving Cockpit, which is available from SAP NetWeaver 7.40 Support Package 04 and which consists of the ILM Archiving work center and the ILM Reporting work center. For more information, see the SAP Help Portal at These tools are available with all NetWeaver installations regardless of whether you have an existing ILM add-on license. EarlyWatch Alert From Solution Manager 7.10 SP12 onwards, you can make specific DVM content available in EarlyWatch Alert (EWA). For more information, see SAP Note Recommendation SAP recommends that you focus DVM activities on a maximum of 5 objects. You select these objects based on their complexity. Simple objects, such as those found in cross-application areas, are suggested first, along with the expected saving potential; for example, tables that include older data and could be deleted or archived. In SAP Solution Manager systems with a lower support package, DVM alerts occur if a database experiences significant growth or reaches a predefined size. For more information on the relevant thresholds, see SAP Note Guided Self-Service for DVM To help implement your data management and data archiving strategy, SAP offers a guided self-service for Data Volume Management, which is a tool-based approach powered by SAP Solution Manager 7.1. The self-service generates a best practice document that describes how to handle your largest data objects according to the methodologies of data avoidance, summarization, archiving, and deletion. NetWeaver Tools In addition to the DVM-specific tools, you can use some SAP NetWeaver tools during a DVM project. The following NetWeaver tools can be used for Data Volume Management: Table Analysis (transaction TAANA) Archive Administration (transaction SARA) Document Relationship Browser for an integrated display of archived documents DART (Data Retention Tool), which extracts business documents required for tax audits. The Data Retention Tool is based on IRS Revenue Processes in the US but was enhanced and adjusted to also meet German tax legislation (GDPdU) Overview of the Standard for Data Volume Management 2014 SAP SE or an SAP affiliate company. All rights reserved. 17

18 3 Lifecycle of Data Volume Management The following chapter describes the general methodology that you need to apply in order to implement and operate a Data Volume Management strategy. Figure 7: Lifecycle of Data Volume Management The first step of implementing a DVM strategy is to assess your landscape. Even you already have an existing strategy, reviewing your current strategy is important. You then need to define the scope for your DVM strategy and estimate the benefits you hope to achieve. In the following Planning step business processes and legal requirements on data are checked against the technical need for data reduction. You furthermore prepare all steps you finally want to implement with a project. Besides all the technical issues aspects like timeline and project funding have to be considered as well. The result of all these steps is the initial implementation of a DVM strategy. The implementation triggers finally an ongoing monitor and improvement process. During operations the archiving and delete jobs are scheduled regularly. The success of the implementation has to be monitored continuously by DVM Work Center to detect new or additional potential for improvement that may be caused by changed business processes. Potential findings will trigger a new entry into planning step for making sure your DVM strategy will be adapted to changed requirements, SAP SE or an SAP affiliate company. All rights reserved. Lifecycle of Data Volume Management

19 3.1 Plan When beginning a new DVM implementation or if DVM monitoring indicates that you need to consider reduction measures, you start with the Plan (assessment and scoping) phase of the DVM standard implementation. To begin this phase, you need to evaluate your current system. You need to perform an initial implementation as you would a project. Project organization will help to integrate all required teams and roles. The following chapters explain the approach you should take during your implementation Data Volume Management Strategy Ensuring optimal Data Volume Management is a critical task and should always be run as a centralized IT service. If you do not already have a holistic strategy for managing your data, SAP highly recommends that you to think about implementing DVM processes or reviewing your current strategy. A comprehensive Data Volume Management strategy should describe the following points in detail: Responsibilities o Who is responsible for DVM issues o How the responsible person deals with DVM issues o How often the responsible person addresses issues that occur Concepts for proper data monitoring, which form the basis for alerting and following improvements. Concepts for data management and data archiving A guided self service in DVM Work Center supports this step by helping you to define a data management and archiving strategy. Concepts for efficient data storage utilization, For example, database compression and reorganization The Reorganization and Compression application in the DVM work center allows you to simulate certain scenarios to optimize data storage. The key goals of your DVM implementation Budget and personnel requirements Your strategy should define key roles, such as the project lead (DVM Champion) and functional experts. For more information, see the Organizational Readiness chapter. Technical requirements, including setting up DVM Work Center in SAP Solution Manager to efficiently analyze and monitor the growing systems and setting up an external content server to store created archive files Strategic goals Organizational Preparation A DVM project is executed by a project team. Once you have defined responsibilities in your DVM strategy and you have ensured sufficient resources, you can start to plan your project. The project team executes all project tasks and is responsible for the success of your implementation. The project requires a high degree of cooperation between teams and business departments, such as functional or business Lifecycle of Data Volume Management 2014 SAP SE or an SAP affiliate company. All rights reserved. 19

20 experts, process owners of relevant applications, and IT, for example, infrastructure experts and database or system administrators, and so on. You might also need to define additional roles, such as external or internal auditors, IT consultants, and service providers. A project team lead takes responsibility for the project, managing tasks such as budget planning, team coordination, decision making, and reporting. An important task assigned to the project team is to implement the strategy and establish a DVM team responsible for the Run and Optimize phases. This team must have at least 1 DVM lead, who is responsible for checking that all DVM projects are compliant with the DVM strategy. Ensuring that your strategy is followed properly required close cooperation between business process operations and IT departments Assessment You need to identify the systems in your landscape for which you want to implement Data Volume Management and which specific DVM measures are appropriate. Consider which of the following aims apply to you: Minimize storage costs and capacity growth Identify and check which resources in your landscape are most used Monitor and minimize database size and growth Improve performance (dialog, batches) according to database size and growth Optimize and review your existing archiving concept Reduce the data volume and TCO You can also make a decision by considering pain points. You should use the following tools to collect all available technical information about DVM-related issues, such as system, landscape, technical, and application-related information: DVM work center EarlyWatch Alert (EWA) Enterprise Support Report (ESR) Database Administration Cockpit (transaction DB02) Self-assessment Based on this information, you can define thresholds to be monitored by EWA. For example, if the size and growth is larger than the defined thresholds, an alert is raised. From SAP Solution Manager 7.1 SP12 onwards, you can also create an EarlyWatch report that contains DVM information, which gives you an idea of the potential savings you could make. The data volume size and the monthly data growth are the most-used criteria, but in specific situations other criteria may be used. As soon as one or more thresholds are reached, you should begin scoping your DVM requirements for that specific system or object. This assessment process determines whether the data growth and volume is best managed by implementing a DVM strategy or whether you also need to review your business processes Scoping While the assessment process looks at a system and a database as one entity, scoping describes a more detailed look at database objects. You examine for which business areas and business objects you can reduce the data SAP SE or an SAP affiliate company. All rights reserved. Lifecycle of Data Volume Management

21 volume and data growth by applying DVM standard reduction methodologies, such as data avoidance, data summarization, data deletion, and data archiving. You evaluate the reduction possibilities according to a business process analysis. that is, you generate a report about how your situation looks if no DVM reduction possibilities are available for a business object or the data for this business object cannot be deleted or archived because of its assigned residence time. Note Business process analyses are outside of the scope of the. When scoping, you determine the possible effects of DVM activities on your system's largest tables and related archiving objects. You also evaluate the prospects of success, especially reachable saving potentials. You use this step to decide whether it is worthwhile to continue with planning and implementing your DVM solution. You may find that the predicted benefits are not large enough and that the expected savings do not justify the effort required to run a DVM project. You can find potential areas for improvement by using one of the following services: Guided Self Service for DVM Continuous Quality Check (CQC) SAP Service for DVM. Both services provide an overview of database resources and expected sizes of the analyzed database tables. If you don t use the guided self-service, collecting the following information can help provide a basis for your DVM implementation decision: Type of Information Examples General system information Date of production start Systems older than 2 years present the best data archiving opportunities. Productive clients (multi-client system) You must perform all DVM activities on each client. Monthly data growth (default: last 12 months) Table size and growth information Categorization of tables Relevant business area and business object This includes estimating the expected complexity of the implementation. Basis objects are usually easy to implement when compared to, for example, accounting documents, which require your teams to consider the appropriate legal requirements. Possible ways of reducing this business object Annual distribution of business-object data You can use this to estimate the technical requirements of archiving the data. Historical archiving information Archived objects with completed archiving runs Execution period (first run date and last run date) This includes identifying whether they run regularly. Archive objects with a date of last archive run older than 2 years are not considered active. Number of archived objects and the size of the archive files. This indicates whether you have already archived a significant portion of your data. Lifecycle of Data Volume Management 2014 SAP SE or an SAP affiliate company. All rights reserved. 21

22 The outcome of the DVM scoping process is a clear description of what is required to implement or adjust your DVM strategy, and a rough idea how successful this will be. If you do not identify a significant enough benefit to your company, for example, if the saving potential is minimal, and you decide that conducting an archiving implementation project is not reasonable, you could consider implementing regular data growth monitoring processes to identify an appropriate time to begin certain DVM processes. SAP recommends using the DVM work center in SAP Solution Manager as central monitoring tool. To ensure the success of your DVM implementation, you should estimate the time and effort required and define the scope of your service in the form of a proposal. You must ensure that all management related (project) requirements have been met. 3.2 Build It is important to keep your business process champion involved at every step of your implementation, especially when including business objects that are required for internal or external reporting purposes (legal compliance) in the scope of your data archiving strategy. Usually, the implementation is driven by the business process operations team. The following key factors are vital to ensuring the success of any DVM implementation: Support of the management team, for example, sufficient sponsoring Established IT and business unit teams Committed business unit that understands the need for DVM Proper scoping by performing a qualified data analysis to focus your goals. These might be quick-wins during the first implementation phase Archive administrator know-how Test system for mass and performance tests In this phase you start to reduce the system volume by implementing the recommendations given in the Self- Service or SAP service report and following your project plan. In this implementation step, you can also cover the setup and configuration of the DVM work center in SAP Solution Manager. You can also perform post processing during this phase, such as database reorganization. In general, the implementation follows the stages shown in the following figure: SAP SE or an SAP affiliate company. All rights reserved. Lifecycle of Data Volume Management

23 Figure 8: Phases of a DVM Implementation Project Blueprint In this step, you match the technical requirements for Data Volume Management with business requirements for data. To successfully complete this step, you need to involve business units. The following chapter describes all of the processes and consideration necessary to properly blueprint your DVM implementation. Workshops The business process champion and the key users conduct workshops to discuss options with the application team. Each workshop usually focuses on a specific application or document type and aims to fully inform the team These workshops need to be carefully planned and conducted by the business process operations team. Data Analysis Application management teams should perform an in-depth and detailed data analysis, for example, using the Table Analysis function (transaction TAANA). This identifies which business objects will benefit from the Data Volume Management process. It also helps to clearly present the expected effect of any measures you take and allows you to clearly see the effects of defining a certain residence time. In addition, it may help when specific data Lifecycle of Data Volume Management 2014 SAP SE or an SAP affiliate company. All rights reserved. 23

24 has to be excluded, for example, from data-archiving for business reasons. In addition, it helps you to identify the following: Appropriate archiving object or deletion report. In some cases, more than one archiving object can be applied for the same table and you need to find out which archiving object is the most appropriate. Possible critical errors that might prevent you from implementing Data Volume Management. For example, incomplete documents will not pass the checks for data archiving and will remain on the database. Test Archiving Test archiving performed before the workshop allows you to demo how to display archived data and helps to reassure key users that their data will not be lost. For this test, you can use the following sources of data: DVM CQC service DVM Guided-Self-Service This provides in-depth data analysis, explanations, and know-how on the individual data archiving objects. Tables and Archiving Objects (transaction DB15) This shows the linkage between an archiving object and its related tables. You can use SAP Notes to find additional technical information. For more information including the data management guide, reports, and a list of transactions for accessing archived data, see the following SAP knowledge sources: Role of Business Process Champion The business process champion must answer the following questions: Is the data required at all or is it possible to avoid future postings? Is the data required at the current level of detail or is it possible to summarize the data? Is the data required for a limited timeframe only and can it be deleted afterwards? How long should the data to remain in the database before it is archived? How long do the archive files have to be stored for retrieval for business and audit purposes? Where should the archive files be stored? (external content server or directly on file system) Is the available standard functionality on archived data sufficient for business and audit purposes? Which minimum search criteria should be available for archived data? Is fast indexed access (for dialog accesses on archived data) required or is a non-indexed sequential read of archived data in a batch process sufficient? Do you need to take action before data archiving to ensure legal compliance? For example, creating a Data Retention Tool (DART) extract for tax audits in the US and Germany. What dependencies between archiving and deletion have to be considered? In some cases, the business process defines the sequence of the archiving objects, in other cases the archiving objects follow a predefined sequence that is achieved by implemented existing checks. For example, CO total records can only be archived when all corresponding CO line items have been archived. What are the effects of DVM measures on the system landscape? Are there any other systems connected via an interface that will be negatively impacted? For example, it is important to consider the interface between a transactional system (for example, R/3, CRM) and an attached BI system. Uploading to BI that already has been archived in R/3 or CRM is possible, but it is also difficult and time consuming SAP SE or an SAP affiliate company. All rights reserved. Lifecycle of Data Volume Management

25 Storage and Project Costs A successful implementation will have a short but manageable residence time. This is to minimize storage costs while reducing impact to business processes. In some cases, very short residence times mean that you have to define and develop customer-specific workarounds, which can increase the implementation costs. For example, if you have to implement Z-reports for accessing archived data. Figure 9: Storage Costs vs. Project Costs If data from different countries with different legal aspects is included in the project, planning and testing data may take several months. If you are archiving data, the application management team needs to provide information about features available for displaying and reporting archived data so that the business process champion fully understands the effects and consequences of data archiving. The result of this process is a preliminary definition of the data volume management strategy. This preliminary definition has to be confirmed by the business process champion after an intensive test phase with the involvement of the key users Realization In this step, you transfer the specified business requirements into the Customizing and variant definitions. In addition, you must define the technical setup of data-archiving, for example, where to store the archive files or the retention time of an archived file before its destruction. Example If you are summarizing, you need to set up the Customizing Lifecycle of Data Volume Management 2014 SAP SE or an SAP affiliate company. All rights reserved. 25

26 If you are archiving, you need to customize residence times for an archiving object and define the selected variables for the archive write job. There is no single way to avoid creating data or to begin and schedule deletion tasks. How to proceed and which report or Customizing option to use depends strongly on the business object or technical table. For data archiving, the central place for customizing and variant definition is the NetWeaver Archive Administration (SAP transaction SARA). A full and detailed understanding of Customizing parameters and the variant definition report is required. After this step, the system is ready for functional and integration tests Functional and Integration Tests After you have transformed the business requirements of the preliminary DVM strategy to the Customizing, the effects and results have to be tested. Before starting the tests, make sure that the latest SAP Notes are implemented. The following table describes the aspects that the tests should cover and provides some specific questions that you need to answer: Aspect Functional correctness and business acceptance Questions Is the result as expected? Is the data after avoidance still sufficient for reporting and retrieval needs? Does the deleted data match the data selected in the deletion report? Is the display method (which may differ from the display of online data) acceptable and does it include all required details? Is the performance of accessing archived data sufficient? Is the search criteria offered on archived data sufficient? Is the display of linked data sufficient (for example, business objects in document flow, PDF documents, attachments, documents)? Effects on interfaces and other systems in system landscape Are there any systems that try to access archived data? For example, a BW system may try to upload data that has already been archived in the ERP system Archiving in CRM may send out BDocs to update the corresponding documents in ERP. Performance Test This mass test is important to estimate the runtime in the production system. Based on the result, the data volume processed in each job may have to be adjusted to ensure a reasonable runtime that should not exceed 6-8 hours. If possible, this mass test should best be performed on a system of comparable size to the production system. A test case with all detailed steps is prepared by the application management team. The functional test is then performed by the key users of the business unit based on the test case. As a result the business process champion signs off and confirms the planned activities and you set up job variants and Customizing that can be used in the production environment SAP SE or an SAP affiliate company. All rights reserved. Lifecycle of Data Volume Management

27 3.2.4 Go-Live You need to implement the activities and measures defined in the DVM strategy carefully. You need to closely monitor the effects on the overall system performance, as archiving and deletion processes will put additional load on the system. Begin by running a small number of jobs at the same time. After gaining some experience, you can increase this number if necessary. You do not need to start a lot of different archiving objects or deletion jobs at the same time. Instead, archive and delete the backlog of archiving objects or deletion jobs for 2-3 business objects before scheduling the next jobs. Removing the backlog (catchup phase) may take some time; depending on the overall system loads and the resulting limitations in scheduling the jobs, this phase may take several months. In contrast the standard operations phase, the catchup phase requires manual job scheduling and monitoring. Usually, no automated or dynamic variant definitions can be used. Different variant definitions may be required for every job. You need to ensure intensive monitoring to discover how much more work the DVM jobs can cause without any negative effect on standard operation. You should create a predefined list of jobs to be scheduled as result of the test phase, as well as a troubleshooting guide explaining the most common errors and their fixes or workarounds. It is especially important to distinguish between errors that can be handled by the IT unit and errors that need to be fixed with the help of the business unit. After the go-live and catchup phase, the DVM jobs can be moved to standard operation mode. During the catchup phase, the business process operation team aims to gain experience scheduling the jobs, their runtime and their side-effects on other processes. This means they are well prepared and able to define automated jobs that will run without manual interaction. 3.3 Run Once you have planned and built your solution you can begin to run your Data Volume Management processes. This chapter discusses the key considerations when operating your solution Data Volume Management Operations How to operate a DVM strategy is handled differently by different SAP customers and largely depends on the number of jobs and the frequency defined for scheduling them. SAP recommends implementing regular jobs automatically. This enables you to include these jobs in the general monitoring concept and reduces manual effort. To achieve this, your teams need to rely on information about archiving time based on experience gained during the go-live and the initial mass archiving phases. In addition, optimal technical customizing is required to support this automated approach. This ensures that you create a set of well-defined jobs that run on a regular basis in the defined job windows with as little manual interaction as possible. Some customers schedule all their archiving and deletion jobs manually, for example, once a year after the fiscal year closes. This approach is only feasible for systems with a medium level of data volume. Using this method can lead to the following disadvantages: Manual scheduling increases the risk of human error, for example, teams forgetting to run jobs or new members of staff being unaware of requirements. Lifecycle of Data Volume Management 2014 SAP SE or an SAP affiliate company. All rights reserved. 27