Was ist Ask your Data?

Ask your Data ist eine Form von Self-Service BI, bei der Nutzerinnen und Nutzer Daten in natürlicher Sprache abfragen. Statt nur durch vorbereitete Dashboards zu navigieren, stellen sie Fachfragen per Chat und erhalten Antworten, Drill-downs oder Visualisierungen.

Wie unterscheidet sich Ask your Data von klassischen BI-Dashboards?

Dashboards zeigen vordefinierte Sichten. Ask your Data ergänzt diese Sichten um dynamische Fragen. Das ist besonders hilfreich, wenn Fachbereiche im Meeting neue Hypothesen prüfen oder Kennzahlen aus einem anderen Blickwinkel verstehen wollen.

Wann lohnt sich Self-Service BI mit natürlicher Sprache?

Self-Service BI lohnt sich, wenn viele wiederkehrende Ad-hoc-Fragen entstehen, Fachbereiche schneller entscheiden wollen und IT oder Data Engineering durch Report-Anpassungen stark gebunden sind.

Welche Datenbasis brauche ich für Ask your Data?

Sie brauchen freigegebene, verständliche und qualitätsgesicherte Datenprodukte oder eine vergleichbare Datenbasis. Wichtig sind klare KPI-Definitionen, Rollenrechte und ein semantisches Modell, das Fachbegriffe mit Datenstrukturen verbindet.

Wie bleibt die Datenabfrage sicher und nachvollziehbar?

Sicherheit entsteht durch Rollen- und Rechtekonzepte, Governance, dokumentierte Datenherkunft und kontrollierte Zugriffspfade. Ask your Data sollte nicht direkt auf beliebige Rohdaten zugreifen, sondern auf geprüfte Datenprodukte und semantische Modelle.

Kann Ask your Data bestehende Power-BI-Dashboards ersetzen?

In vielen Fällen ergänzt Ask your Data bestehende BI-Dashboards. Standardisierte Management- oder Prozess-Cockpits bleiben sinnvoll. Dynamische Fachfragen, Varianten und Drill-downs lassen sich dagegen oft besser über Self-Service und Chat abdecken.

Wie starte ich einen Ask-your-Data-Piloten?

Ein sinnvoller Pilot beginnt mit einem klaren Fachbereich, wenigen priorisierten Fragen und einer geprüften Datenbasis. doubleSlash unterstützt von der Readiness-Prüfung über den Proof of Value bis zur skalierbaren Umsetzung.

What Is Ask Your Data?

Ask Your Data is a form of self-service BI in which users query data using natural language. Instead of simply navigating through pre-built dashboards, they ask specific questions via chat and receive answers, drill-downs, or visualizations.

How Does Ask Your Data Differ From Traditional Bi Dashboards?

Dashboards display predefined views. Ask your Data supplements these views with dynamic questions. This is particularly helpful when business units want to test new hypotheses during meetings or understand key metrics from a different perspective.

When Is Self-Service Bi With Natural Language Worth It?

Self-service BI is worthwhile when there are many recurring ad hoc queries, business units want to make decisions more quickly, and IT or data engineering teams are heavily tied up with report customizations.

What Kind of Data Set Do I Need for Ask Your Data?

You need approved, understandable, and quality-assured data products or a comparable database. It is important to have clear KPI definitions, role-based access rights, and a semantic model that links technical terms to data structures.

How Can Data Retrieval Remain Secure and Traceable?

Security is achieved through role- and permission-based models, governance, documented data provenance, and controlled access paths. Ask your Data should not access raw data directly, but rather verified data products and semantic models.

Can Ask Your Data Replace Existing Power Bi Dashboards?

In many cases, Ask your Data complements existing BI dashboards. Standardized management or process dashboards remain useful. Dynamic business questions, variations, and drill-downs, on the other hand, are often better addressed through self-service and chat.

How Do I Launch an Ask-Your-Data Pilot Program?

A successful pilot project starts with a clearly defined scope, a few prioritized questions, and a validated data set. doubleSlash provides support from the readiness assessment through the proof of value to scalable implementation.

Self-Service Bi With Ask Your Data

Business units ask questions in natural language, receive answers and visualizations in seconds, and take the load off IT and data teams.

Ask your Data makes self-service BI easier: Not every new reporting need turns into a dashboard project. Instead, business units query their approved corporate data via chat, drill down into the answers, and make data-driven decisions faster.

To achieve this, we combine data intelligence, semantic data models, data quality, and governance so that Ask your Data effectively complements traditional dashboards and turns fragmented data into actionable insights.

Why Traditional Dashboards Are No Longer Enough

Many companies use BI tools and dashboards. Nevertheless, business units remain dependent on data engineering or IT whenever new questions arise: an additional filter, a different view, a new time period, or an explanation of a KPI. The result is delays, Excel exports, and a constant stream of new dashboards that need to be maintained.

Typical Signs:

Business units wait for IT or data teams to answer ad hoc questions.
Dashboard landscapes are growing faster than they can be maintained.
KPIs exist, but definitions and data trust are lacking.
Decisions are postponed in meetings because the necessary visibility is lacking.
Data processing logic is embedded in the BI tool or in Excel rather than in stable data products.

Ask Your Data Turns This Process on Its Head:

Business units start with their question, not with a predefined dashboard path.

Ask Your Data

Data Intelligence in Dialogue

Ask your Data is self-service analytics powered by natural language. For example, users can ask about revenue trends, quality deviations, service cases, or sales data. The solution translates these questions into a structured data query, provides an answer, and can generate appropriate visualizations.

It’s not just the chat interface that matters. What’s crucial is the underlying data foundation: a semantic layer with clear KPI definitions, approved data products, role-based permissions, data lineage, and governance. This ensures that data queries remain traceable and secure.

We implement Ask your Data as part of the Data Intelligence Solution. We assess which data sources, KPIs, and business questions are appropriate, create the necessary semantic layer, and integrate the self-service feature into your existing BI and data architecture.

Data preparation illustrated as house construction: from unsorted building materials through the Raw, Trusted and Refined Zones to a finished house representing usable data products.

What You Gain With Self-Service BI

Faster Time to Insight

Departments answer new questions directly within their workflow. Instead of waiting for new reports, they can review answers, ask follow-up questions, and prepare for the next decisions.

Less Dashboard Clutter

Not every new KPI variant requires its own front end. A clean semantic layer makes data dynamically usable and reduces maintenance efforts in established BI environments.

More Focus for Data Teams

Data engineers and BI teams are relieved of routine queries. They can focus more on data quality, data products, the platform, governance, and more sophisticated analytics or AI use cases.

What We Provide for Ask Your Data

Refining Use Cases and KPIs:
We start with the business questions: Which decisions need to be made faster, which KPIs are relevant, and which departments will benefit first?
Semantic Layer and Data Model:
We structure metrics, terms, and access permissions so that data queries are answered in a way that is both business-friendly and technically controlled.
Self-Service Analytics and Conversational Analytics:
We implement the “Ask Your Data” feature in your database and integrate it with appropriate visualizations, dashboards, or BI tools.

Governance and Security:
Roles, data access, quality, and traceability are taken into account from the very beginning to ensure that self-service does not turn into shadow IT.
Enablement for Business Units and Data Teams:
We support adoption, query logic, KPI understanding, and the operating model to ensure that Ask your Data is used in everyday work.
Blueprints, Accelerators, and Technology Neutrality:
We leverage reusable patterns from data lakehouse and data intelligence projects, adopt a technology-neutral approach, and avoid unnecessary vendor lock-in.

Who Is Ask Your Data Designed For?

Ask your Data is particularly well-suited for organizations that already use reporting, BI, or data analytics and now want to become faster, more scalable, and more user-friendly. For Data Explorers, this can be the next step after creating their first dashboards. For Data Champions, it’s a tool for scaling existing analytics landscapes and empowering business units more effectively.

A Good Fit:

If the data foundation isn’t yet robust, we start with data readiness, data assessment, or data lakehouse components. “Ask Your Data” is only as good as the data, definitions, and governance behind it. That’s exactly why we consider the use case, data product, and operating model together.

The Head of Data, BI Lead, or CDO wants to reduce time-to-insight.
Business units need ad hoc answers to operational and strategic data questions.
Existing dashboards are important, but too rigid for new questions.
Data teams should handle fewer support tickets and deliver more value.
A data platform, a data lakehouse, or quality-assured data products are either already in place or under development.

Here’s How We Get Started

Clarify Readiness

A person examines a data trend in a chart using a large magnifying glass.

We review the data infrastructure, KPI definitions, common business questions, access permissions, and tool landscape. This results in a realistic starting point rather than an abstract AI promise.

Implement Proof Of Value

A person presents a laptop displaying a speech bubble and a bar chart.

For a prioritized use case, we build a working prototype: data integration, semantic model, sample questions, answers, and visualization.

Scale and Operate

Two people manage a dashboard with connected data modules; one holds a tablet.

Following successful validation, we expand our data products, roles, governance, monitoring, and enablement. This transforms the pilot into a usable self-service solution in regular operations.