Business intelligence

Increase your competitiveness with modern business analytics:

  • Quick and cost-saving access to current reporting
  • Efficient extraction of knowledge
  • Detailed & target group-specific evaluations
  • Automated reporting processes
  • Stable data quality & governance

Business intelligence

Increase your competitiveness with modern business analytics:

  • Quick and cost-saving access to current reporting
  • Efficient extraction of knowledge
  • Detailed & target group-specific evaluations
  • Automated reporting processes
  • Stable data quality & governance


More precise,
timely decisions

cost reduction

Sound basis for future-oriented topics such as workflow automation, big data and advanced analytics


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What is Business Intelligence ?

Business Intelligence (BI) is the collection, analysis, and visualization of business-relevant information that helps managers and decision-makers, in particular, to make well-founded business decisions. At the same time, the use of BI in the company can support a range of operational activities. Modern BI is divided into 3 types of implementation, which enable the necessary flexibility of data
evaluation for the respective use case and determine the implementation responsibilities:

  • Corporate BI – this implementation approach is centrally controlled by IT. The scope of use
    for departments is determined by the pure use of reports.
  • Self-service BI – this implementation approach involves the free use of data sources by the
    departments themselves, which take responsibility for the implementation of reports, quality
    assurance, data governance and lifecycle management.
  • The hybrid approach is a hybrid of the two approaches mentioned above. Here, the
    responsibility for data centration, maintenance and governance of the data models is
    assigned to the IT department (or a dedicated data team), while the business department(s)
    use the data models and predefined report templates for their reporting needs in self-service

Are you interested in implementing BI in your company? Explore our consulting services.

Areas of application

Sales management

Data: CRM-Systems

Product improvement

Data: Usage data, production metrics


Data: ERP-Systems


Data: internal data sources, surveys


Data: internal data sources, event logs

IT-Security & Testing

Data: Log files, Enterprise Service Bus

Challenges in the use of Business Intelligence

In today’s world, there are numerous options available for data analysis. Providers of business analytics software promise enormous flexibility in the choice of connectors as well as self-service evaluation tools and offer very attractive pricing models.
However, with flexibility comes the great danger of making wrong decisions based on incorrect, out-of-date, inconsistent or inaccurate data. In particular, heterogeneous data sources often ensure that the quality and truthfulness of analysis results suffer. On top of that, staff are often not adept at using modern self-service tools. This, in turn, negates efforts to reduce IT involvement in meeting day-to-day reporting needs. While staff competence can be sustainably strengthened by setting up a central or several selective competence centres for BI adoption, a number of technological and process challenges need to be overcome to ensure that data is always accurate and widely usable.
These are:


With many different sources, the technological basis of data consolidation must be designed.

Access rights

(Raw data)
Efficient collaboration on data models requires both organisational planning and technical premises.

Quantity structure

The data delivery infrastructure as well as the data extraction architecture can vary greatly depending on the data volume.


The decision on the granularity of the data to be stored must be made in advance in the cross-section of costs/benefits.

Data extraction

In some cases, data collection requires complex and/or elaborate automation steps.

Data extraction

In some cases, data collection requires complex and/or elaborate automation steps.

Access control

Granular access control at data point level ("row level security") requires specific technological support.


Correctness, completeness and up-to-dateness of the data must be ensured as automatically as possible

Complexity of the data models

Especially in self-service BI scenarios, conventions for naming and documentation standards are necessary.


In addition to internal governance, compliance with regulatory guidelines, especially for personal data, must be ensured.

TME Approach - our Consulting Services

Enterprise BI Enablement

There are many hurdles on the way to the data driven organisation. For efficient Self-Service BI, it is
crucial to institute an internal competence centre ensuring enterprise level discipline and wide
spread of BI adoption. We will guide you through all steps of organisational transformation including
both strategic and operational process change as well as technical development and resource skill building. 

We’ll help you to achieve an effective organisation-wide Business Intelligence enable-ment through establishing a modern technological stack, strong and flexible gover-nance concept as well as high velocity in operational routines.

  • Development of the adaptation strategy
  • Identification of use cases
  • Sourcing
  • Technical architecture
  • Governance concept
  • Setting up the work processes
  • Staff empowerment
  • Competence Centre

Power BI Implementation

Smart decisions require reliable data and actionable visualisation. Our favourite disci-pline is to equip
decision makers with in-sightful and user-friendly Power BI reports serving their daily reporting

To achieve this goal, we engage relevant cli-ent stakeholders in our proven co-creation workshops resulting in accurate report visualization, data modelling and governance requirements, which we implement through our expertise in Power Platform as well as capabilities in data modeling, report building, UX design, performance optimization and development of custom visuals for MS Power BI.

  • Requirements Management
  • Use Case Workshops
  • Corporate UX Design
  • Data modelling
  • Report development
  • Implementation of the Governance Guidelines
  • Performance optimisation
  • Development of custom visualisations

Daten- & Software Integration

Creating a big picture often implies strapping many edges of the data jungle in a single source of truth.

Our mission is the employment of organisational digital twin for advantages arising through data driven decision making and product development. We create a concept for reliable and cost-effective data pipeline and implement its architecture, deploying secure and highly scalable, cutting-edge PaaS/SaaS cloud services and/or on-premise technologies fitting your demands, budget and strategic vision.

  • Designing data collection pipelines
  •  Implementation of the technical architecture with a focus on efficiency and costs
  • Interface development (APIs, connectors)
  • Use of self-developed architectures and SaaS and PaaS solutions

TME is a certified Implementation Partner

TME AG is a certified implementation partner of Microsoft and Process.Science.
Our expertise includes business intelligence implementation, data and software integration,
Cloud application development and process mining.

Logo MS und TME-01
Process.Science - TME Partnerschaft

TME Workshops

BI Together Co-Creation Workshop

Start your Business Intelligence experience with TME AG

Are you interested in Business Intelligence and want to pilot a BI project? We would be happy to support you in crystallising the objectives for your use case, working out the requirements basis in a structured manner and developing a prototype based on synthetic data. In a 2-day workshop, we achieve the following goals together:

  • Documented common understanding about the challenges and the target picture
  • Informing participants about the state of modern BI incl. participant training for evaluating ready-made BI reports using Microsoft Power BI
  • Documented requirements basis for the database and evaluations
  • Implemented dashboard prototype using synthetic data as a template for further development phases

Bring Your Own Data – Proof Of Concept

Try out the advantages of data-driven decision-making!

With our “Bring Your Own Data” offer, we offer you the opportunity to create a proof of concept for the BI capability of your data free of charge and without obligation. Your advantages are:

  • Documented common understanding about the challenges and the target picture
  • Dashboard prototype developed in the shortest possible time based on your operational data
  • Optional: Data anonymisation

Project references Business Intelligence

Implementation of a business intelligence-based solution for liquidity monitoring

lnitial Situation

  • A clearing bank needs liquidity monitoring as an early warning system for intraday liquidity shortages based on the BCBS 248 ratios
  • The transaction data intended for import into the core banking system are available as a dynamic source data component
  • The source data are only accessible in the form of files in the company’s internal infrastructure
  • The Bank has no internal IT resources for the operation and maintenance of IT solutions

Approach & addes value of the TME

  • Elaboration of the technical and non-functional requirements
  • Design of the process chain to map the specified requirements and definition of the process responsibilities
  • Sourcing of the SaaS and PaaS solutions possible for the implementation
  • Creation of the technical architecture design
  • Implementation of the backend architecture for the data integration pipeline and the data pool
  • Implementation or set-up of the interfaces and data integration routines
  • Implementation of the data model and reports with the help of Microsoft Power BI
  • Operationalisation of automation processes for the software life cycle
  • Ensuring the maintenance-free operation of the solution
  • Enablement of the customer’s staff to use and administer the solution

Methodology used

  • Ideation workshops were held to identify problems and develop solutions
  • Bootstrapping method was used to conceptualise the report designs and validate against the defined requirements
  • The API architecture developed in the TME was used to introduce the data integration pipeline in a cost- and time-efficient way using modern technologies
  • Continuous Integration & Development (CI/CD) practices have been applied to automate the software lifecycle processes, especially in the testing and deployment sections.

Outcomes achieved

Liquidity Monitoring Tool

Public cloud-based liquidity monitoring tool in the form of a BI application

Process Automation

Process automation in the provision, import and aggregation of transaction data into liquidity ratios

Maintenance-Free Operation

Further Project References

only available in german

Implementation of a reporting solution for programme and project management
of a software development

Development of Custom Visuals
for Microsoft Power BI



Alexander Rezun TME Einstiegsmöglichkeiten Consulting Manager

Alexander Rezun

Consulting Manager

Together with Thomas Deibert, Partner TME, Alexander Rezun will be available to answer your questions about Business Intelligence and Power BI.