Successful SAP BI Project which went live and includes SAP Business Objects ...

Successful SAP BI Project which went live and includes SAP Business Objects 4 over SAP BW 7.1

via Content in SCN by Adir Oren on 4/14/12

BICS present a successful SAP BI Project which went live and includes SAP Business Objects 4 over SAP BW 7.1

Hi All,
In this article we will share with you a success story of one of our SAP BI project using SAP Business Objects 4 over SAP BW 7.1
Customer: SAP Customer running SAP Best Practice
Users: Over 50 Business Intelligence users

Project scope:

1. Implementation of the SAP BI Best Practice with COPA,PP,MM,FI,SD,PUR,IV,PS
2. Enchantment of Info Objects Material, Customer , SD & COPA BI modules
3. Implementation of Organizational KPI's for 6 business  areas 

Architecture:
The Data warehouse is SAP BW, Front end tools is SAP Business Objects 4 web intelligence for management /analysis reports + crystal reports 2011 for transactional reports
BW-We have 2 SAP BW 7.1 landscapes: BW Dev acting also as BW QA and BW Production
BO-We have 2 SAP Business Objects landscapes – BO Dev , BO Prod

Authorization concept:
The authorization module includes 3 tiers
Tier1- Data level security coming from SAP BW
Tier2-SAP Business Objects web intelligence technical tool functionality (authorization over what kind of buttons and functionality the BO Webi will present for each user)
Tier3- SAP Business Objects control on the list of folders available for each user
Training:
Training method  was" train the trainer"- we have trained the Customer IT personal , they are responsible for User training.

Challenges:
1.We are the first service companies in the local market who went live with a full SAP BI project using SAP BW & SAP Business Objects 4, we had couple of problems with query performance, which eventually was stable after enhancement of SAP Notes , BO system tuning and last but not least we have established several of key development procedures for Business Object reporting over SAP BW Query as semantic layer.
2.There was several of Web intelligence functionality that wasn't working over BW, some of them we have developed workaround, some of them reported to SAP and will be fixed in FP3 and future development 

Summary:
Project went live as scheduled, SAP Business Objects reporting went live and kicking, good SAP support from SAP locally and globally
For more information
www.bics.co.il | coe@bics.co.il |visit their site SAP BI Center of expertise

Are You Hiding Your Data Sins?

Are You Hiding Your Data Sins?

via Content in SCN by Randy Garrison on 7/31/12

A single source of the truth. A great mantra – but hard to achieve as data types, volumes, and frequency continue to explode. A company that embarks on a campaign to create one source for all its reporting and analysis needs must traditionally undertake a massive enterprise data warehouse project, relying heavily on "extraction" of multiple layers of data from underlying ERP solutions. Business logic is then applied to the data, cleaning it and enhancing its usefulness, in a process referred to as ETL – extract, transform, and load.

The Promises and Perils of ETL
ETL works well in traditional environments where reporting solutions are outside the transaction system – those designed so reporting and analysis functions didn't impair or slow transactional systems. In such systems, users would simply extract the data and then use tools to report and analyze.
Many companies, however, use the ETL "cleansing" process to hide the sins of bad transactional system data. Such an after-the-fact approach creates multiple problems. Data that has been cleansed and changed can be difficult to reconcile with underlying sources. And when you pull together data from multiple sources, cleanse, and report it, it can look fine at a summarized level – but unsummarized, it is still full of outliers or anomalies... useful, but definitely not the same. In addition, ETL-based changes to data rely on predefined (often IT-driven) extraction configurations not visible to the report user. Because the quality of underlying transactional data is hidden, business processes remain less than optimized. Cleaning up such an environment requires costly data management projects.

Finding and Correcting Bad Data
Powerful computing tools can now work with transactional data directly in the data sources, making it possible to quickly spot bad data and trends. The SAP® HANA^TM platform, for example, is an in-memory computing appliance that runs analysis on big data directly from transactional systems. Its speed and power make it possible to analyze data where it resides, without exporting it.

Taking Action with SAP HANA
Using SAP HANA, employees can use information and analysis within the context of business processes – then take immediate corrective action. Users can continually monitor and refine a process in real time, identify backlogs and opportunities, and affect performance as it happens – for example, adjusting inventory levels on the fly or authorizing limited-time promotions for in-store customers.

Learn More
Business Analytics Services from SAP can help you right your data sins while crafting an overall information strategy. Our consultants can also speed analysis across your organization using in-memory computing advancements such as SAP HANA.
For more information on how Business Analytics Services from SAP can help unlock the value of your data and support better, faster, data-driven business decisions, visit us online.

Making Business Intelligence Work for You

Making Business Intelligence Work for You

via Content in SCN by Tom Kurtz on 7/26/12

Making Business Intelligence Work for You

Business Intelligence (BI) is a top priority for many companies. Used effectively, it can drive insights into customer behavior, pinpoint new market opportunities, optimize marketing spend, leverage competitive intelligence, and more. Because of the obvious benefits, most companies have evolved from an attitude of "Should I utilize business intelligence?" to "How do I get the most out of business intelligence?"

Yes, choosing BI is a wise move. But once you've made the decision to invest, how should you proceed? How can you ensure that you get the most from your investment? How do you make BI work for you?

Three Approaches for Successful BI Strategies

Over the past decade working with hundreds of customers to enhance their business value, SAP has seen three successful approaches to getting companies started with BI:

1) Holistic BI Strategy

In this approach, you take a step back and evaluate your entire BI strategy in the context of your business. You'll need to identify your business vision, strategies, and related growth initiatives and ensure alignment between your vision and your infrastructure needs. Execute by creating a long-term project roadmap and prioritizing your BI spending.

2) Focused Analytic Solution

If you have a high-value business use case already identified, consider developing an initial analytic solution targeting it. This approach addresses immediate business needs, while creating an opportunity to showcase your success to other parts of the business.

For this focused approach – for example, with a visualization quick start – you'll need to analyze four key areas:

• Metric framework. There are literally hundreds of metrics a company could calculate, monitor, and view. However, certain metrics are relevant to specific strategic initiatives. Identify which metrics are the most applicable to the issue you're addressing, and why. You'll also need to become familiar with how your metrics decompose and who in your organization views that information. For example, if a VP of operations at a retailer cares about COGS, and sees that it is tracking high for a given period, he will probably want to understand why. You may need to investigate a series of submetrics – product cost, landed cost, shrinkage – to fully understand the root causes of the increase in COGS.
• Visualization design patterns. Identifying your metrics framework and who in your organization is viewing the information allows you to understand how that information needs to be presented. Do you have executives who need aggregate information in the form of dashboards or scorecards? Do you have analysts that require drill-down reporting capability? Do you have mobile users that require information displayed on devices?
• Data design patterns. Once you know what you want to see and how to display it, you'll need to determine the data required. This is one of the most important aspects to strong BI; if you don't have a sound data strategy, your BI results will be compromised. What data is available? Where might you have data gaps? And what is the cost of acquiring new data vs. the benefit to the business?
• Solution architecture. Finally, what technical infrastructure is required to support your analytic solution? What are the various server considerations?

3) Architecture Framework

For some IT executives, this is the logical place to start. Begin by determining your infrastructure requirements and gaining an initial technical understanding of the tools you will be deploying. Such a framework will help you better support the business as you get into the planning and implementation stages. You'll need to systematically assess:

• The size of your enterprise deployment
• Security and authentication
• Positioning of BI tools
• Server configuration
• Installation requirements
• Current number of users, types of users, number of concurrent users, forecasted user growth
• Disaster recovery plans, strategies, and backup
• Content integration needs

Any of these three options can be an effective starting point; the choice comes down to where your business is now, and what is required for it to be successful. Regardless of where you start, though, you can – and should – expand to take advantage of one or both of the other options as your BI footprint matures. Perhaps you want to start with an analytic solution to show success, then once that succeeds, drive more sponsorship into a full BI strategy. Or maybe you want to begin by developing your architecture framework as you get your IT story in place, then embark on an analytic solution that solves a specific use case. There are many approaches to BI – ultimately, it's your business, and your decision.

Every day, SAP Services helps companies work through critical business decisions like these. Watch our latest World Tour presentation Decide Better: Best Practices with Business Intelligence given by Tom Kurtz, Global Practice Director HANA Services at SAP Consulting at http://tinyurl.com/3za6kmw.

To learn more about how we can help ensure that BI delivers maximum benefits for your business, visit us at www.sap.com/services.

What approach to BI has worked for your organization?

Snapshot Scenario on Stock Data with APD

Snapshot Scenario on Stock Data with APD

via Content in SCN by Volker Schottdorf on 8/1/12

Hi to all!

I recently was asked to share my knowledge of how to implement a snapshot scenario on stock data out of 0IC_C03 with Analysis Process Designer (APD) and here are the steps to take with screen shots of how the objects are implemented in our BW system (7.0) since 2009. All general information about the different approaches for analyzing stock data with cumulative and non-cumulative key figures are perfectly explained in the document "How to Handle Inventory Management Scenarios in BW (NW2004)" and therefore will not be mentioned in this blog of mine here.

Snapshot Scenario with APD on Stock Data of 0IC_C03

1. Create Query for selecting the data out of 0IC_C03 that you want to have in snapshot Cube
2. Implement a DSO (type: direct update) for the data of your snapshot query
3. Implement an analysis process with APD (transaction RSANWB) and include an ABAP routine and transformation for mapping source and target fields:
4. Execute the analysis process to insert data to your DSO; Result log:
5. Implement a standard InfoCube and a dataflow from DSO to InfoCube
6. You can update your DSO and InfoCube by Process Chain

ProcessChain: Program to start APD:

ProcessChain: InfoPackage to load data from DSO to InfoCube with OLAP variable for selection of current week: