Was sind Data Driven Solutions bei doubleSlash?

Data Driven Solutions ist das Angebot von doubleSlash für nachhaltige Datenqualität und datengetriebene Entscheidungen. Kernbausteine sind Data Lakehouse und Data Intelligence , ergänzt um planbare Einstiege wie den Data Readiness Check , das Data Assessment , die Data Discovery und den Data Hub .

Warum scheitern KI-Projekte oft an den Daten?

Weil die Ergebnisse von KI-Modellen von Datenqualität abhängen. Um Datenqualität sicherzustellen, setzen wir auf Ownership, klare Prozesse und Automatisierung. Mehr dazu unter Data Quality und Skalierung für KI .

Was ist der Unterschied zwischen Data Assessment und Data Readiness Check?

Der Data Readiness Check zielt auf KI-Readiness und Datenqualität. Das Data Assessment geht breiter auf Use Cases und Potenziale ein.

Was ist der Unterschied zwischen Data Lakehouse und Data Intelligence?

Data Lakehouse und Data Intelligence lösen unterschiedliche Aufgaben: Das Lakehouse schafft die verlässliche Datenbasis, Data Intelligence macht diese Daten für Entscheidungen nutzbar. Wenn Daten verteilt oder Kennzahlen widersprüchlich sind, starten Sie mit dem Lakehouse. Ist die Basis vorhanden, führt Data Intelligence zu Dashboards, Analytics und datenbasierter KI. Details: Data Lakehouse Data Intelligence

Brauchen wir eine bestimmte Cloud-Plattform?

Nein. Wir sind technologieoffen. Wir setzen unter anderem Azure und AWS ein. Die Auswahl der Technologie folgt Ihren Anforderungen.

Wie lange dauert ein Proof of Value, und was kostet der Einstieg?

Bei klarem Scope rechnen wir mit etwa 4 bis 6 Wochen. Viele starten mit dem kostenlosen Data Readiness Check, einem Data Assessment ab 1.500 € und einem Proof of Value ab 9.900 €. Eine Übersicht der Orientierungspreise finden Sie unter &bdquo; Ihr Direkteinstieg “.

What Are Data-Driven Solutions at doubleSlash?

Data Driven Solutions is doubleSlash’s offering for sustainable data quality and data-driven decision-making. Its core components are Data Lakehouse and Data Intelligence , supplemented by structured entry points such as the Data Readiness Check , the Data Assessment , Data Discovery , and the Data Hub .

Why Do AI Projects Often Fail Because of Data?

Because the results of AI models depend on data quality. To ensure data quality, we rely on ownership, clear processes, and automation. Learn more at Data Quality and Scaling for AI .

What is the difference between a data assessment and a data readiness check?

The Data Readiness Check focuses on AI readiness and data quality. The Data Assessment takes a broader look at use cases and potential.

What is the difference between a data lakehouse and data intelligence?

Data Lakehouse and Data Intelligence address different tasks: The Lakehouse creates a reliable data foundation, while Data Intelligence makes that data usable for decision-making. If data is scattered or metrics are inconsistent, start with the Lakehouse. Once the foundation is in place, Data Intelligence leads to dashboards, analytics, and data-driven AI. Details: Data Lakehouse Data Intelligence

Do we need a specific cloud platform?

No. We are open to all technologies. We use Azure and AWS , among others. The choice of technology depends on your requirements.

How long does a Proof of Value take, and what does it cost to get started?

If the scope is clear, we estimate it will take about 4 to 6 weeks. Many clients start with the free Data Readiness Check, a Data Assessment starting at €1,500, and a Proof of Value starting at €9,900. You can find an overview of the estimated prices under “Your Quick Start .”

Data Driven Solutions

From Data Silos to a Single Source of Truth

Start the Data Readiness Check

Request a consultation

Data quality, informed decision-making, and AI in day-to-day operations go hand in hand.

When data is stored in silos and metrics contradict each other, reporting, analytics, and AI fail at the most fundamental level. Our data-driven solutions create a trustworthy single source of truth and insights built upon it: with a data lakehouse, data intelligence, and predictable entry points.

Our Offers

Entry Points and In-Depth Sections

You don't have to start with the entire platform. With these offerings, you can jump in at the point that best suits your current situation and delve deeper into specific topics in a targeted way.

A Selection of Our Clients

With doubleSlash, we successfully implemented our data analytics project on an equal footing. … in a spirit of partnership, with a straightforward approach, and focused on finding solutions. – Maximilian Tschochner, Ph.D. (Eng.), Data Analyst, BMW AG

When Data Silos and Poor Data Quality Slow Things Down

Data is intended to create transparency and competitive advantages. In practice, however, there is often a lack of a single source of truth and usable data products.

Typical scenarios:

Data silos between CRM, ERP, the online store, IoT, and Excel
Inconsistent metrics without common definitions
Data processing logic in Excel or in a BI tool outside of stable data pipelines

Manual reporting and significant data cleansing effort
AI and analytics pilots that fail due to poor data quality
Compliance pressures (GDPR, EU AI Act, CSRD/ESG) without traceable data flows

First, data quality; then, insights and AI

This is where our data-driven solutions come in. We create a robust data foundation (data lakehouse), enabling reporting, analytics, and data-driven AI (data intelligence), along with blueprints, infrastructure as code, and team enablement—so your teams can operate and further develop the solution themselves on a day-to-day basis.

Clean data products are essential for self-service and automation. In the long term, they enable new business models (monetization).

Other providers build dashboards or simply provide the platform. We start with data quality. We don't stop at the prototype. We stick with it until the solution delivers reliable value in day-to-day operations.

For Data Explorer & Data Champion