Information & Data Management
Data is a boardroom matter. Not a tooling matter.
Articles on data preparation, modeling, real-time analytics, and the question of who owns a number.
Data quality is a symptom, not a cause. Treating it as a project means cleaning tables while leaving the condition that produced them untouched: nobody in the business owns the number that matters. The articles here run from data preparation through statistical modeling to real-time analytics, and at every stop they show that the bottleneck is rarely the technology.
A data strategy answers three questions before any system is chosen: which decision is supposed to improve, which number carries it, and who in the company owns that number by name. Only then does architecture become a sensible question. That order is the difference between a data strategy and a data project, and it belongs on the executive agenda, not in a department.
From the number to the name behind it: that is the work.
See our advisory workArticles in this topic 20 articles
- Information & Data Management
Data preparation: where most of AI success is decided
Data Preparation determines AI success or failure. Learn why 80 percent of the effort lies in data preparation and how midsize companies can master it.
- Information & Data Management
Data management best practices from the US, Asia, and Europe
How midsize companies in the USA, Asia, and Europe implement data management. Best practices, comparison of approaches, and transferable strategies for Germany’s Mittelstand.
- Information & Data Management
Information theory for business: from Shannon to data
From Shannon to today: how information theory shapes modern data management and supports midsize companies in evaluating and using their data assets.
- Information & Data Management
Data discovery: finding the hidden value in company data
Data discovery helps midsize companies find hidden data treasures and use them for better decisions. Methods, tools, and practical guide for the Mittelstand.
- Information & Data Management
Data governance for midsize companies: order from chaos
Pragmatically implementing Data Governance in the Mittelstand. Guide for midsize companies with framework, GDPR reference, and concrete measures for better data quality.
- Information & Data Management
The 10 costliest data management mistakes worldwide
The ten costliest data management mistakes in midsize companies worldwide and how to avoid them. With case studies, cost analysis, and concrete countermeasures.
- Information & Data Management
Breaking down data silos with integrated data management
Data silos cost midsize companies time and money. How to build integrated data management with concrete tools and strategies.
- Information & Data Management
Dimensionality reduction and feature engineering
Dimensionality reduction and feature engineering explained clearly. How midsize companies master data complexity and optimally prepare data for AI projects.
- Information & Data Management
Master data management: the foundation for AI
Master Data Management in the Mittelstand: why master data quality is the decisive AI enabler and how midsize companies can implement MDM pragmatically.
- Information & Data Management
Real-time analytics: live data for business decisions
Real-time analytics enables midsize companies to make faster and better decisions. A practical guide with tools, use cases, and implementation steps for midsize companies.
- Information & Data Management
Statistical modeling: from regression to time series
Statistical modeling from regression to time series analysis: How midsize companies use these methods for sales forecasts, cost models, and better decisions.
- Information & Data Management
Variational methods for business decisions
Variational methods and mathematical optimization explained clearly. How midsize companies use these methods for better data-driven business decisions.
- Information & Data Management
Data cleansing: the foundation for AI projects
Data cleaning is the foundation of successful AI projects in the Mittelstand. Practical guide with methods, tools, and a concrete case study for midsize companies.
- Information & Data Management
Data literacy as a competitive factor
Data Literacy is the decisive competitive factor for companies. How midsize companies systematically build data competency and use data for better decisions.
- Information & Data Management
Data storytelling: communicating data insights
Data Storytelling transforms data into compelling stories. How midsize companies communicate data insights effectively and drive data-based decisions.
- Information & Data Management
Bayesian methods for business decisions in practice
Bayesian methods explained clearly: How midsize companies make probability-based business decisions with concrete ROI and less risk.
- Information & Data Management
ETL and ELT: building and automating data pipelines
ETL and ELT explained simply: how midsize companies build automated data pipelines. Comparison of the best tools and step-by-step guide for midsize companies.
- Information & Data Management
Data analytics without a data science team
How midsize companies use data analytics for better business decisions—without their own data science team. Practical guide with tools, methods, and ROI examples.
- Information & Data Management
Data mesh vs. data warehouse for midsize companies
Data Mesh, Data Warehouse, or Data Lakehouse? Which data architecture fits the Mittelstand? Comparison, decision guide, and practical roadmap for midsize companies.
- Information & Data Management
Self-service BI: insights without a data department
Self-service BI enables midsize companies to make data-driven decisions without a dedicated IT department. Comparison of the best tools and a practical guide for getting started.
Next step
Business data strategy for your company
From the target state to supervised delivery. We advise you and enable your organization.
45 minutes, by video, free of charge.
How ready is your decision? Check it in 3 minutes.
Call +49 6021 625 63 40