Closer to the customer with insights
Stories engage the brain on all levels: intuitive, optional, rational, and physically. When we hear stories, our brains respond by better understanding the information. The limbic system (the emotional part of the brain) releases chemicals that stimulate our sense of connection and our reward centre.
When you put your audience at the centre of your story, you make them feel like heroes. Stories move us to action. The reactions our brains trigger may evoke a sense of empathy, urgency, or great concern.In one study, participants’ neural responses were measured while listening to a story about a father’s relationship with his young, dying son. Two emotions, in particular, were prominent: distress and empathy. Study leaders assessed participants both before and after listening to the story. They found increased levels of cortisol, which makes a person more focused and attentive, and oxytocin, which triggers well-being and empathy. The most startling finding was: Narratives change the chemistry in our brains and get us to act. Captivating stories cause us to become emotionally attached to others and feel motivated to begin a particular action.
Lead with data
- Understand context
- Choose an appropriate visual representation
- Remove clutter
- Direct attention in the desired direction
- Think like a designer
- Tell a story
Four Megatrends for the Future
The platform ideaCompanies and people are under pressure to act. Changing framework conditions force rapid changes. The business analytics platform is the starting point for coping with new data types and combinations. We are constantly gaining new insights; proactively preparing options for the unknown.
Why the data warehouse is the core of the platformSingle Source of Truth (SSOT) is a concept that ensures that every business decision made in an organization is based on the same data. To set up an SSOT, relevant employees are equipped with a source that stores the data points they need. Data-driven decision-making took on unprecedented importance with the collection and analysis of data. Acting on data-driven business intelligence is essential for competitive brands today. Companies often spend far too much time debating which numbers (invariably coming from different sources) are the correct numbers.
SAP Reference: Business Technology PlatformReference architecture for a digital transformation
- Development of a fully integrated self-service and advanced analytics platform for all interactions and user groups.
- This serves as a framework with application and infrastructure services for converting different types of data and integrating different interfaces, source and target systems.
- Agility through coupling of different information systems in a logical data warehouse with Realtime Data Warehouse & Analytics Lab.
- Agile real-time data management with structured business data and unstructured Big Data from the Data Lake. Users leverage agile data from multiple sources. SAP HANA connects operational and analytical systems on one platform.
Building Blocks of the Business Analytics PlatformThe concept of cheap blocks is used in the Enterprise Architecture Framework TOGAF. The following solution components have a more general application character, i.e., they can be used as templates to solve similar problems. Building blocks have the following generic properties:
- Build an end-to-end integrated self-service and advanced analytics platform for all interactions and user groups.
- This serves as a framework with application and infrastructure services for the conversion of various data types and the integration of diverse interfaces, source and target systems.
- Agility through coupling of diverse information systems in a logical data warehouse with Realtime Data Warehouse & Analytics Lab.
- Agile real-time data management with structured business data and unstructured Big Data from the Data Lake. Users use agile data from different sources. SAP HANA combines operational and analytical systems into one platform.
- SAP S/4HANA forms the “digital core” for embedded operational reporting.
- SAP BW/4HANA as “central DWH” for descriptive and predictive analysis -with data types from IoT and Data Lakes. SAP Data Warehouse Cloud complements the core system as a “digital framework”..
- Raw Data from Processes
- Data acquisition layer-raw data
- Single Source of Truth
- Multiple Versions of Truth
- Service Layer
- Process Layer
- Interaction Layer
- Multi Channel Delivery
Virtually Connect Databases and SAP Systems Based on SAP HANAA wide variety of technologies are combined on SAP HANA for data storage. It is recommended for regular use within the SAP HANA stack to model the data that the transfer to SAP HANA is reduced to a minimum. This is different for exploratory access; here longer processing times are acceptable due to infrequent access. For the integration of the various other technologies, Smart Data Access (SDA) and Smart Data Integration (SDI) in particular are available at the SAP HANA level. With SDA or SDI, data can be merged into heterogeneous enterprise data warehouse landscapes (data federation) and combined for analysis. In previous SAP tools, all data were pre-classified by storing them in a database. In contrast, SDA lets you access data remotely without first replicating the data in the SAP HANA database. SDA is used for Teradata databases, SAP Sybase ASE, SAP IQ, Intel Distribution for Apache Hadoop and SAP HANA instances, among others. SAP HANA processes the data like local tables in the database. Thanks to automatic data type conversion, it is possible to map data types from databases that are connected to SAP HANA data types via SDA. With SDA, data from other sources remains in virtual tables. Virtual tables created within SAP HANA reference remote tables in the designated data sources. These connections provide real-time access to the data, regardless of where it is stored. At the same time, they do not affect the SAP HANA database. Authorized users can subsequently write SQL queries to SAP HANA that operate on virtual tables. The SAP HANA query processor optimizes the queries and executes the relevant part of the queries in the connected database, returns the result to SAP HANA and completes the operation. Query execution is optimized with SDI or SDA by working with SQL queries on virtual tables in SAP HANA. To create relationships and links, connect facts and master data from the source via associations in Open ODS View. These facts and master data, as well as operations on navigation attributes, are linked directly at the database level at query runtime. For Open ODS Views, SDA lets you use data sources not managed by the SAP BW system, but without much effort: extend modelling in the SAP BW system, use persistent data stored in SAP HANA tables, and create an open ETL connection between external systems and your virtual tables. Through this, with raw data from the processes, the first layer can be modelled. Not all data can be accessed virtually. Thus, we need a place in the business analytics platform where such data is stored: Data Acquisition Layer Raw Data.
The governance concept sets the following technical and functional guidelines and is decisive for a successful implementation:
- Establish BI organization
- KPI definitions: Develop a catalog of responsibilities and acceptances
- Modeling guidelines: Specifications and regulations in the context of data modeling
- Requirements elicitation: template with must-have content
- Development standards: Definition of guidelines for development/programming, including transport system
- Naming conventions: Establish specifications when naming objects. Goal is to build a framework for defining questions and solutions.
- Test concept with definition of quality checkpoints
- Authorization concept: Establish a concept that is compatible with the surrounding systems.
Added Value:Thanks to pattern recognition, customer-specific value propositions are created. This is how we strengthen customer loyalty and set ourselves apart from the competition. Potential & Benefit: Fast and well-founded identification of promising customers through access to valid and up-to-date data. We have better control of the results of the individual customer segments.
- Part 1: How to make business analytics successful?
- Part 2: Business Analytics vs. Business Intelligence
- Part 3: What is SAP Analytics? The SAP Data Warehouse Portfolio
- Part 4: SAP Analytics – The Front End Products
- Part 5: Data Platform – An Important Pillar of Digital Transformation
- Part 6: On the Way to AWS
- Part 7: Cloud – Curse of Blessing?
- Part 8: Leading wit Data – Why Power BI is Often a Choice