Providing a platform for business decisions is not a question of tools and technologies, but a joint effort of different disciplines. To achieve this, we rely on workshops to record both the technical and business requirements, find the right technology and design a Business Intelligence solution tailored to your individual needs.
Workshops for the individual Business Intelligence solution
In the workshops, we first focus on the business requirements, then we derive the fundamentally necessary capabilities of a solution. In parallel, we consider the technical requirements and restrictions of each customer.
Our experience in various technologies and aspects helps us to identify the appropriate standard software from one or more manufacturers, to weigh advantages and disadvantages, and to estimate customization and development efforts.
As a result, we receive a possible solution architecture as a combination of standard software from the leading manufacturers as well as a rough cost estimate for the realization including the procedure.
Topics we address in the workshops:
Data: Origin, format, quality, quantity
Analytics: reports, dashboards, analyses, DataScience
Infrastructure: Present vs. Strategy / Cloud vs. On-premises
Governance, Security, Development
Analytics Workshop
- Actual recording
- Technical requirements
- Strategic objective
- Analysis of strengths and weaknesses
- Technical framework
- Documentation of the obtained information
- Development of a customized solution proposal
- Selection of suitable solution components
Optional: Planning and implementation of a business analytics and data project
Technology Workshop
- Actual recording of the technology and the challenges
- Objective regarding technology
- Technical framework
- Documentation of the obtained information
- Development of a customized solution proposal
- Selection of suitable solution components
Optional: Recommendation for implementation
Design Workshop
- Actual recording of the technical requirements
- Actual recording of the existing technology and the challenges
- Technical framework
- Documentation of the obtained information
- Development of a customized solution proposal
- Selection of suitable solution components
Optional: Recommendation for implementation
Big Data Workshop
- Actual recording
- Technical requirements
- Strategic objective
- Analysis of strengths and weaknesses
- Technical framework
- Documentation of the obtained information
- Development of a customized solution proposal
- Selection of suitable solution components
Optional: Planning and implementation of a Business Analytics and Data Project
Proof-of-Value Workshop
Content:
- Presentation / General procedure
- Evaluation of the collected use cases
- Analysis of existing data sources, quantities and quality
- Selection:
- Use cases to be presented
- analytical platform to be used
- other analytical tools
- Definition of expected results
- Data Preparation
- Load of data
- Test of data quality and documentation
- Application of statistical methods to analyze the data (Data Science) in terms of the defined use cases
- Conceptual design:
- Implementation recommendation "Big Data"
- Platform and operation recommendation
- Documentation
Objectives: The workshop is aimed at companies that would like to use Data Science to determine currently unknown information from their data with a rough objective. However, the value of the information, quality and quantity is still vague, which is why the initial investments should be limited.
Minimum Viable Product (MVP)
Objective: Development of a Minimum Viable Product (MVP). This is particularly interesting for companies that want to gain concrete initial experience with Data Science in the project based on their data. The MVP can later go live with little additional effort, but this is not the main focus during creation.
Content:
- Analysis of existing data sources, quantities and quality
- Selection:
- Procedure, analytical platform to be used
- further analysis tools
- Definition of the expected results
- Data Preparation:
- Load of the data
- Test of data quality and documentation
- Application of statistical methods to analyze the data (Data Science) in terms of the defined use cases
- Integration into the target system
- Conceptual design:
- Recommendation for further expansion Platform and operation documentation