QM RAPIDVIEWS WHITE PAPER
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QM RAPIDVIEWS WHITE PAPER
Sommaire
1. Transforming your analytics .................................................................................................. 3
1.1. Facing decision-making challenges ......................................................................................... 3
1.2. Implementing a high-performing BI ........................................................................................ 3
1.3. SAP QM Context ...................................................................................................................... 4
2. Explore the decision analytics with RapidViews ..................................................................... 6
2.1. A platform for IT and business users ....................................................................................... 6
2.1. Functional content .................................................................................................................. 7
2.1.1. QM RapidViews in figures ............................................................................................... 8
2.1.2. QM RapidViews Semantic Layer ...................................................................................... 9
3. QM RapidViews : report example ........................................................................................ 15
4. Technical content ................................................................................................................ 16
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1. Transforming your analytics
1.1. Facing decision-making challenges
“Business Intelligence” which includes decision analytics activities, presents for organizations major
challenges which need to address a set of multiple and complex solutions. SAP publisher offers
innovative tools which boost the potential of decision making analytics solutions. This is the case with
its In-memory HANA solution which answers the problematics of delays and data loading.
Beyond the challenges which BI needs to address, the implementation of an effective and qualitative
decision analytics system faces many difficulties. It can be difficult to implement because of the
number of stakeholders (publisher, implementation partner, user organization, service providers. Thus
the coordination between key users must demonstrate great expectations, and clearly defined
requirements gathering. This strategy would avoid the pyramidal construction which would consist in
overlapping data as new requirements appear, transforming the data base in a nebula. This
phenomenon would worsen the complexity of the environment, making it more difficult to maintain.
The course of each data point, firstly within the ERP, then in the data processing phase, and finally in
its restitution showcases the complexity of the environment.
To be competitive, organizations must now be able to react in a very limited timeframe, while facing
market trends and other variations on the supply channel. For this they must possess reliable, relevant
and accessible real time analytical tools. The reliability is based on high quality, centralized, and
appropriately consolidated data. As for the relevancy, it is based on the reading of coherent and
significant indicators.
1.2. Implementing a high-performing BI
In order to have successful decision analytics, the organization must ensure it follows a number of
principles:
- Organizational and documentation rigor: the data sources an data processing layers must be
identified and centralized.
- Data quality: the processes within the ERP must be respected to return uniform and reliable
databases. The BI post-project acceptance test must also be scripted and prepared.
- Relevancy of analysis: the data aggregation and visuals must supply precise and explicit
numbers. A BI report should gather data according to perimeters and axis of analysis to meet
the expectations of the target users
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1.3. SAP QM Context
The QM (Quality Management) module is a transverse module in SAP, it is very often linked to
the other modules (SD, MM, etc.) and concerns quality control. There are 4 main components
related to quality:
- Quality planning
- Quality control
- Usage decision
- Quality Reviews
In this module, we have integrated the main SAP dimensions below to analyze the different KPIs of
the QM module:
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2. Explore the decision analytics with RapidViews
2.1. A platform for IT and business users
The RapidViews platform allows you to accelerate, centralize and control your SAP Analytics projects.
It offers “BI Accelerator” functionalities, with notably predefined business content on the SAP QM
scope, and “BI Governance” features.
It offers many benefits:
• Accelerate your Analytics project: save time in the deployment and day-to-day of your
business intelligence project
• Centralize your Analytics referential: your Analytics knowledge in one single location
• Reconcile the IT and functional teams: a tool which allows BI managers, BI developers and
business users to work better together
• Efficiently manage your SAP BI: data is growing exponentially, it is ubiquitous, the governance
of its analytics contents is fundamental
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2.1. Functional content
RapidViews provides dashboards and KPIs to track quality activities. All of this functional content is
available in a platform and represented by SAP process.
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2.1.1. QM RapidViews in figures
QM RapidViews includes 40 HANA Views, 40 KPI, 7 pre-defined reports and 10 datamarts.
It covers the following sub-modules:
› Quality Planning
› Quality Inspection
› Quality Notification
40 40
HANA VIEWS KPI
QM
SUB
MODULE 7
Quality
Inspection & MODULE PRE-DEFINED
REPORTS
Notification
SUB
MODULE
Quality
10
Planning DATAMARTS
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2.1.2. QM RapidViews Semantic Layer
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3. QM RapidViews : report example
Inspection Message Overview
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4. Technical content
In practice, the Business Content RapidViews QM takes the form of pre-modeled data cubes that are
installed in client environments (development, testing, production). A reporting layer is then added for
KPI visualization.
Several technologies support the Business Content RapidViews QM data cubes, including SAP
Datasphere, SAP HANA, S/4HANA, ECC on HANA, and SAP HANA Cloud.
Furthermore, the primary reporting tools in the market are compatible with RapidViews QM, including
SAP Analytics Cloud, Power BI, SAP BO, Tableau, Qlik Sense, DigDash, and more.
RapidViews products thus complement the entire chain of decision data processing within an
organization:
• RapidViews Cubes
Data Reading, Targeting,
and Organization
• RapidViews Cubes
Data Processing: Scope,
Calculations, Aggregations
• Visualization Interfaces (Power BI, Tableau,
Real-time Data Qlik...) Catalog of Pre-designed RapidViews
Presentation Reports
• BI Governance features
Maintenance and Control
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