- Tableau Desktop Intelligent data analysis and visualization intuitively via drag & drop
- Tableau Prep Combine, format and prepare data for analysis
- Tableau Server Controlled self-service analytics for the entire organization
- Tableau Mobile Data availability from anywhere
- Embedded Analytics Powerful analytics embedded in your own portal
- Creator (can fully work with the tool and create new data sources)
- Explorer (is limited to the existing data sources; can work with them fully)
- Viewer (data consumer: sees the dashboards and analyses)
Tableau complements the business analytics toolsetFor a long time, IT departments have tried to satisfy as many needs as possible with just one tool. This approach failed to achieve high user acceptance. What is almost universally unthinkable for the company vehicle is just as bad an idea for the analytics toolset. The tool-zoo should be avoided and still different strengths should be used. With a framework (business analytics platform) the framework is set and the strengths of the products are used specifically: high integration (SAP) and flexibility for the analyst (Tableau). This is how we succeed in providing real added value to our users. We achieve this through the following points:
- Silos in the data warehouse and the data lake are broken down.
- Metadata contains important information to enrich the data and detect inconsistencies.
- Modernize data integration to support hybrid multicloud environments.
- Combine agility and pay attention to scalable solutions through optimized unified data integration.
Why is Tableau so often added to the existing SAP portfolio?Data analysis with Tableau is simply fun for many users. Tableau has placed great emphasis on the design of the user experience. Because of its high flexibility to combine data, derive data, etc., Tableau offers its own approach to data exploration. The source data is not modified by Tableau during the live connection, but it is cached locally. Thus, response times after the initial load are excellent. At SAP, the focus is on integration with existing software suites such as S/4HANA. SAP keeps the data in the original location. The reuse of metadata (for example, hierarchies, currency conversions, texts, etc.) is rightly expected by users, but limits independence in analysis. Business analytics takes a data-driven approach to business, using statistics and data modeling to develop new business insights. This includes analyzing historical data as well as predicting what trends will shape the future, all things being equal, and what business decisions should result. Data-driven decision making is defined as the use of facts, metrics and data to drive strategic business decisions that align with business goals and initiatives. When companies realize the full value of their data, it means that everyone – whether a business analyst, sales manager or human resources specialist – is empowered to make better decisions every day based on data. This isn’t achieved by simply picking the right analytics technology to identify the next strategic opportunity. Your organization must make data-driven decision making the norm and create a culture that encourages critical thinking and curiosity. Every meeting should start with data. You develop your data skills through practice and application. This requires a self-service offering where employees can access the data they need, balanced with security and governance. Additionally, the example of leaders supporting data-driven decisions and making them that way themselves is needed. This encourages employees to do the same. In an effort to be data-driven, many organizations are developing three core capabilities: Data Literacy, Analytics Agility, and Community. NewVantage Partners recently reported that 98.6 percent of executives say their organization is striving to achieve a data-driven culture, while only 32.4 percent report success in doing so. A 2018 IDC study also found that companies have invested trillions of dollars in modernizing their business, but 70 percent of those initiatives failed because they prioritized technology investments without building a data culture to support them.
Storytelling with dataWhen you present your insights in visually compelling ways, you have a better chance of influencing the decisions of senior leadership and other employees. With many visual elements such as charts, graphs, and maps, data visualization is a viable way to see and understand trends, outliers, and patterns in data. There are many popular visualization types to effectively display information: a bar chart for comparisons, a map for spatial data, a line chart for temporal data, a scatter plot to compare two measurements, and more. Develop insights: Thinking critically with data means finding insights and communicating them in a useful, engaging way. Visual analytics is an intuitive approach to asking and answering questions of your data. Discover opportunities or risks that impact success or problem solving. Act on your insights and share this way of working (analyze first, then conclude and move into action): once you discover an insight, you need to take action or share it with others for collaboration. One way to do this is to share dashboards. Highlighting key insights through informative text and interactive visualizations can influence your audience’s decisions and help them take more informed action in their daily work. Combine Tableau with graphomate Extensions. It’s so easy to create consistent and understandable charts.
Further development of the Enterprise Data ModelBefore I get to the communication standards and a way to present this similarly across tools, I want to talk about the evolution of the Enterprise Data Model. In my eyes, Tableau has its strengths in the independent preparation, analysis and playful development of dashboards. Therefore, to ensure sustainable use of the data, it is important that stable insights are fed back into the Enterprise Data Model. This ensures that there is a single source of truth for the enterprise data model. In my view, the extra effort is absolutely worth it. As far as possible, the data sources in the enterprise data model should be used directly (live data connection) and this very model should be expanded and maintained as new insights are gained. The single source of truth and a common understanding of definitions and data quality is the basis for a data-driven enterprise. Presenting insights in a user-friendly way with storytelling makes it very easy for users to understand and integrate the insights into their daily actions. A consistent understanding to visualize dashboards, graphs, and tables helps users quickly navigate and avoid misinterpretation.
IBCS – A Notation Concept for Comprehensible CommunicationRolf Hichert reached many controlling departments with his notation proposal. These were introduced into the International Business Communication Standards (IBCS®) and are today significantly developed further by the IBCS Institute. The SUCCESS formula of the IBCS® includes rules for the following three areas:
- Conceptual rules help convey a clear message by building an appropriate storyline. These are the SAY and STRUCTURE sections of the SUCCESS formula, based on work by authors such as Barbara Minto.
- Perceptual rules help convey the message by using an appropriate visual representation. These are EXPRESS, SIMPLIFY, CONDENSE and CHECK of the SUCCESS formula.
- Semantic rules help to convey an unambiguous message by using a consistent notation. This is the UNIFY part of the SUCCESS formula, originally developed by Rolf Hichert.
- The message should be the answer to the questions posed by those reading or listening. Therefore, those reporting need to know what the readers or listeners are burning to know.
- Each chart is given not only a title but also a message in the form of a declarative sentence. A picture is there to explain the message, but not the other way around.
- Each text passage begins with a summary of the message, namely the most important statement or finding.
- Every report begins with a summary of recommendations, decision statements, or key findings.
- Even a more comprehensive presentation should be able to be summarized in one sentence(!).
- Messages are always complete sentences, they can be findings, statements or recommendations.