Intelligent Data Management

    Data management: one number every department can rely on

    Data management is the work of bringing together data from different systems, defining its meaning and organising its maintenance. datadice has been building data foundations like these in Coburg since 2019. For Thomann, Europe's largest music retailer, datadice built and ran a data platform with more than 100 dashboards over five years; today Thomann's own data team continues to develop it.

    Goal:Use data reliably

    ThomannCase studyOver five years we built a data platform with more than 100 dashboards for Thomann.
    Book an initial consultationRead the Thomann case

    Last reviewed: · reviewed by Thomas Knorr, Managing Director datadice

    One number for every departmentReconciling data

    Revenue Q3

    ERP
    €4.31m
    CRM
    €3.96m
    Excel
    €4.18m
    Definition: net revenue by invoice date

    Revenue Q3

    €4.24m

    Valid for sales, controlling and purchasing

    Example with fictitious figures

    At a glance

    What
    datadice brings together data from your systems, cleanses it and agrees with your departments what each number means.
    For whom
    Companies where sales, controlling and purchasing walk into the same meeting with different numbers.
    Outcome
    A documented data model, agreed system connections and regulated maintenance; built on top: reports, forecasts or data for AI applications.
    Getting started
    Initial consultation, then a strategy workshop with data foundation check

    Funding:Small companies in Bavaria receive a grant of up to 50% from the Digitalbonus for the introduction. We prepare the application with you free of charge.

    Go to the Digitalbonus

    Typical starting point

    You want to steer your company's development on a sound basis, automate processes or use AI. The information you need for this is created in different systems and maintained according to the rules of the respective departments. To be used together, this data has to be brought together both in business terms and technically.

    Our answer

    You understand your data and take responsibility for it yourself

    A reliable data foundation makes this information usable for decisions. It is the prerequisite for using new technologies effectively.

    What we stand for
    We are convinced: a company must understand its data and take responsibility for it. It holds information about customers, services and operational relationships. A reliable data foundation makes this knowledge accessible for decisions and creates the conditions for using new technologies effectively.

    For your finance department

    Why do sales and controlling show different revenue figures?

    Usually each system calculates “revenue” by its own rule: the ERP by invoice date, for example, the CRM by order intake and the controlling team's Excel list after credit notes.

    Each of the three figures is correct according to its rule. What is open is which rule applies in the Monday meeting. datadice solves this in two steps.

    First, the departments agree on a definition, for example “net by invoice date, after credit notes”, and name a person responsible for it. Then the data platform calculates every key figure by exactly this rule and, where needed, shows the path down to the individual invoice. Your finance department then sees where a number comes from and who approved it.

    For your IT department

    How do we prevent yet another isolated solution?

    datadice builds on the platforms you have already set and asks exactly this in the first meeting: which standards apply, which systems lead, who runs what.

    Only then do we map the data flows with your IT: which source delivers which field, where it is changed and who may read it. Every new connection gets a place in this picture before it is built.

    We document the data model, processing rules and responsibilities so that your IT or another partner can carry them on without us. Your CIO thus has an architecture sketch, a reasoned technology decision and an access concept in hand before the first invoice arrives. At Thomann, the platform is now in the hands of an in-house data team.

    Architecture

    How datadice builds your data foundation

    We start with your business goals, so we open up exactly the sources your project needs.

    Step 1 of 4

    01

    Goals

    We start with your business goals and the specific project, such as a cross-departmental analysis.

    Example: an agreed sales reportStep 1 of 4

    Goals

    Project: Sales report by product group

    Involved: Sales, controlling

    Outcome

    What you receive

    You receive a documented data model (the map of your terms, rules and responsibilities) with regulated maintenance, so you steer the quality and expansion of your data foundation yourself.

    • Agreed system connections
    • Documented data model
    • Regulated data maintenance with clear responsibilities
    • A data warehouse, where your needs call for one
    • Built on top: reports and forecasts
    • Data for processes and AI applications

    Building blocks

    Four building blocks, depending on the project

    Business Intelligence

    Business intelligence, meaning data-based reports and analyses, connects the information from your departments through jointly defined key figures and traceable calculation rules. This lets you assess business development on an agreed basis.

    You receive a key figure system with reports, graphical overviews and detailed views. In BI consulting, datadice starts with the management question, then defines the key figure and only then builds the dashboard.

    Data Warehouse

    A data warehouse (a central, structured data store) connects the data from your existing systems in an agreed data model. Further analyses and applications build on it.

    We document source connections, the data model and the processing and quality rules. More on this on the new page “Building a data warehouse”.

    Building a data warehouse

    Data Organisation

    Responsibility for data lies with the people who understand its business context. That is why we define terms, responsibilities, quality criteria and maintenance processes together with your departments.

    The datadice Academy supports applying the agreed rules in everyday work.

    Forecasting Systems

    Forecasting systems support sales, inventory and sales capacity planning. We test every forecast on held-back historical data against an agreed baseline, so the people responsible can judge what it contributes to planning.

    Responsibility for the measures derived from it remains with your company. Thomann uses such models in purchasing.

    The first step

    What does the datadice data foundation check examine?

    The datadice data foundation check examines whether your existing data is sufficient for a planned project. The review is limited to the sources this project needs.

    You receive findings on the state of your data, a business data model for the area examined, the definitions of terms and a prioritised list of preparatory work. It shows what needs to be cleansed, added or connected.

    Comparison

    Standard software, custom development or datadice?

    The table compares standard software, custom development and datadice against the same criteria, so you decide on a transparent basis.

    Starting point

    Standard software
    Features of the product
    Custom development
    Project specification
    datadice
    Your business goals and a specific project

    Connecting existing systems

    Standard software
    via the vendor's existing interfaces
    Custom development
    depending on the contract
    datadice
    Built on your existing systems, connections checked in advance

    Your own business rules

    Standard software
    within the configuration options
    Custom development
    freely implementable
    datadice
    Terms and rules defined together with your departments

    Quality assurance

    Standard software
    by the vendor
    Custom development
    as agreed in the project
    datadice
    Quality criteria and responsibilities for maintenance

    Operation and further development

    Standard software
    with the vendor's releases
    Custom development
    by separate agreement
    datadice
    Expansion according to your business priorities

    Enabling your team

    Standard software
    Product training
    Custom development
    as needed
    datadice
    Training in data maintenance through the datadice Academy

    Application

    We start with a specific project

    For example a cross-departmental analysis or the introduction of an AI application. This shows early on which information is available and how it can be used.

    Quality criteria and checks show where action is needed. Changes to definitions and data sources are documented, so statements remain understandable as your systems evolve.

    Knowledge

    Articles on this topic

    Google Cloud for AI Projects: Vertex AI, BigQuery & Co.Which Google Cloud service fits which AI use case? A guide from practice.16 min read(opens in a new tab)SAP ECC end of maintenance 2027: What mid-sized companies need to decide nowMainstream maintenance for SAP ECC ends on 31 Dec 2027. We show your options and move custom developments out of the ERP. Clean core makes your migration smaller.7 min read(opens in a new tab)

    Frequently asked questions

    An objection we often hear

    „Our system partner already takes care of the data.“
    Then datadice coordinates with them and adds the integration wherever a project needs data from several systems.
    What is data management?

    Data management brings together data from your existing systems, refines it and clarifies its business meaning. Your employees and applications then work from a shared foundation whose quality you control.

    What is a data warehouse?

    A data warehouse is a central, structured data store for analyses and applications across systems. It connects the information from your existing systems in an agreed data model.

    Do we have to rebuild our running systems for this?

    We plan the build on the basis of your existing systems and check their connection options. You know the impact on ongoing operations before implementation begins.

    Our data is still too disorganised.

    That is the normal case, and the data foundation check starts exactly there. It narrows the review down to the information your project needs and prioritises the preparatory work.

    Getting started

    For which decision do you need a number everyone trusts?

    In the free initial consultation we talk about your project and the data it needs. You then receive a short playbook with our assessment.

    Starting point:Strategy workshop with data foundation check

    Book an initial consultationSee the strategy workshop