Anlage Logo
Talk to Anlage
Home› Data & AI› Modern Data Foundations› Data Analytics
DATA ANALYTICS

Turn trusted data into decisions that move the business.

Transform enterprise data into clear, actionable insight through modern analytics, business intelligence and advanced analytical capabilities designed around the decisions that matter most.

DATA
↓
PREPARE
↓
MODEL
↓
ANALYZE
↓
VISUALIZE
↓
ACT
↓
BUSINESS OUTCOME
FROM DATA TO DECISION

More data does not automatically create better decisions.

Organizations often have large volumes of data, multiple reporting systems, fragmented KPIs, and inconsistent definitions. This leads to manual reporting, disconnected dashboards, and difficulty translating analysis into action.

The problem is not simply access to data. The challenge is turning data into a consistent understanding of what is happening, why it is happening and what the organization should do next.

THE ANLAGE APPROACH

Anlage helps organizations build analytics capabilities around business questions — not simply around available data.

Move analytics from reporting to intelligence.

01
DESCRIPTIVE
What happened?
02
DIAGNOSTIC
Why did it happen?
03
PREDICTIVE
What is likely to happen?
04
PRESCRIPTIVE
What should we do?
05
INTELLIGENT
How can decisions be adaptive?
ANALYTICS CAPABILITIES

Analytics across the enterprise decision lifecycle.

BUSINESS INTELLIGENCE

Enterprise reporting, dashboards and KPI visibility.

ADVANCED ANALYTICS

Statistical and analytical techniques for deeper business understanding.

PREDICTIVE ANALYTICS

Models and analytical approaches that help anticipate future outcomes.

DATA VISUALIZATION

Clear visual communication of complex information.

SELF-SERVICE ANALYTICS

Enable business teams to explore trusted data independently.

PERFORMANCE ANALYTICS

Connect operational and business data to understand performance.

LOCATION / CUSTOMER / PRODUCT

Use enterprise data to understand customers, products, markets and operations where relevant.

ANALYTICS MODERNISATION

Modernize legacy reporting environments and analytical workflows.

Start with the decision — then design the analytics.

BUSINESS QUESTION
↓
DATA REQUIRED
↓
ANALYTICAL METHOD
↓
INSIGHT
↓
DECISION
↓
ACTION
↓
OUTCOME
"What is driving changes in performance?"
"Which customers are most valuable?"
"Where are operational bottlenecks emerging?"
"Which products or services are performing differently?"
"What is likely to happen next?"
"Where should the business intervene?"

Analytics is not simply dashboard development. It is a system for answering business questions.

From raw data to actionable insight.

01
DEFINE
Identify the business question.
02
PREPARE
Identify, combine and prepare relevant data.
03
MODEL
Structure data for analytical use.
04
ANALYZE
Apply analytical methods and identify patterns.
05
VISUALIZE
Make insights accessible to decision makers.
06
ACTIVATE
Connect insight to business processes and decisions.
07
LEARN
Measure outcomes and continuously improve.
MODERN ANALYTICS ARCHITECTURE

Create an analytics foundation that connects data with decisions.

LAYER 1: DATA SOURCES
ERP CRM Applications Databases APIs External Data
↓
LAYER 2: DATA FOUNDATION
Lake Warehouse Lakehouse Data Products
↓
LAYER 3: ANALYTICS ENGINEERING
Transformations Semantic Models Metrics Business Logic
↓
LAYER 4: ANALYTICS
BI Reporting Dashboards Advanced Analytics
↓
LAYER 5: INTELLIGENCE
Predictive Models AI Decision Support
↓
LAYER 6: BUSINESS
Decisions | Actions | Outcomes
GOVERNANCE QUALITY SECURITY OBSERVABILITY

Make complex information easier to understand.

Effective BI requires more than attractive charts. It requires trusted data, consistent definitions, clear business logic, and usable visual communication.

  • Executive dashboards
  • Operational dashboards
  • KPI & performance reporting
  • Self-service analytics
  • Interactive visualization
  • Semantic models
  • Governed metrics

Go beyond reporting when the business question requires it.

PREDICTIVE ANALYTICS

Identify patterns and anticipate potential outcomes.

STATISTICAL ANALYSIS

Understand relationships, trends and drivers.

FORECASTING

Support planning and decision-making with forward-looking analysis.

SEGMENTATION

Understand differences across customers, products, markets or operations.

ANOMALY DETECTION

Identify unusual patterns that require attention.

Analytics creates the bridge from trusted data to intelligent applications.

Strong analytics foundations improve the ability to identify useful signals, define business context and prepare data for downstream AI initiatives.

TRUSTED DATA
↓
ANALYTICS
↓
ADVANCED ANALYTICS
↓
MACHINE LEARNING
↓
GENERATIVE AI
↓
INTELLIGENT DECISIONS
TECHNOLOGY ECOSYSTEM

Architecture first. Technology where it fits.

DATA PLATFORMS
BI & VISUALIZATION
  • Power BI
  • Enterprise BI
  • Dashboards
  • Reporting
ANALYTICS
  • SQL
  • Statistical Analysis
  • Advanced Analytics
  • Predictive Analytics
CLOUD
  • Azure
  • AWS
DATA ENGINEERING
  • Pipelines
  • Transformation
  • Orchestration
GOVERNANCE
  • Quality
  • Lineage
  • Security
  • Catalog
  • Observability

Analytics shaped around the decisions of each industry.

RETAIL & CONSUMER
Customer analytics, Product performance, Demand and operations, Commercial performance.
Explore Retail →
HEALTHCARE & LIFE SCIENCES
Operational analytics, Patient / member insights, Performance, Data-driven decision support.
Explore Healthcare →
BFSI
Risk, Customer analytics, Operations, Performance.
TECHNOLOGY
Product analytics, Customer behavior, Operational performance.
MANUFACTURING
Operations, Supply chain, Quality, Performance.

Analytics that changes how the organization sees and acts.

FASTER DECISIONS
Reduce the time between information and action.
SINGLE VIEW OF PERFORMANCE
Create consistent definitions and trusted KPIs.
BETTER BUSINESS VISIBILITY
Make important patterns and drivers easier to see.
PROACTIVE DECISION-MAKING
Use predictive and advanced analytics where appropriate.
ANALYTICS ADOPTION
Make trusted insight accessible to the people who need it.

Modernize analytics without disrupting the business.

Emphasize controlled modernization across legacy BI, dashboard rationalization, semantic models, cloud analytics, self-service adoption, data platform alignment, governance, and migration planning.

ASSESS
↓
PRIORITIZE
↓
MODERNIZE
↓
MIGRATE
↓
ADOPT
↓
OPTIMIZE

A practical path from reporting complexity to modern analytics.

01 — DISCOVER
Understand business questions
Understand users, reports and underlying data.
02 — ASSESS
Evaluate analytics maturity
Assess data quality and technology landscape.
03 — DESIGN
Define the target architecture
Establish the target analytics architecture and user experience.
04 — DELIVER
Build and modernize
Execute implementations in manageable increments.
05 — ADOPT & OPTIMIZE
Drive adoption
Measure usage and continuously improve the capability.
WHAT YOU WALK AWAY WITH

An analytics capability built around the decisions that matter.

Analytics Maturity Assessment
A view of the current analytics environment and improvement priorities.
Target Analytics Architecture
A practical target-state architecture aligned to business needs.
KPI & Metric Framework
A consistent approach to important business measures.
Dashboard / BI Blueprint
A structured approach to reporting and visualization.
Analytics Roadmap
Prioritized initiatives and a path forward.
Advanced Analytics Opportunities
Identification of where predictive or advanced analytics can add value.
Adoption & Operating Model
Guidance for sustaining and evolving the analytics capability.

Analytics designed around business outcomes.

BUSINESS-FIRST

Analytics starts with the decisions the business needs to make.

DATA-FOUNDATION AWARE

Analytics is built on trusted, governed data.

ENGINEERING-LED

Analytical solutions are designed to operate reliably at enterprise scale.

EXECUTION-ORIENTED

The goal is adoption and measurable business value, not simply another dashboard.

Analytics is part of a broader modern data foundation.

Modern Data Foundations Data Platform Strategy Cloud Data Modernisation Data Engineering Data Integration Data Governance Master Data Management

Frequently Asked Questions

What is enterprise data analytics?
It is the capability of transforming raw enterprise data into trusted, accessible insight to support decision-making, operational efficiency and strategic planning across the organization.
How is data analytics different from business intelligence?
Business Intelligence (BI) focuses on descriptive and diagnostic reporting—what happened and why. Data Analytics is a broader capability that encompasses BI, but also includes predictive and prescriptive analytics to anticipate future outcomes and suggest actions.
How can organizations modernize legacy reporting?
By assessing existing reports, prioritizing those with true business value, modernizing the underlying semantic models and data foundations, and migrating to modern cloud-based visualization tools while driving user adoption.
How do you ensure analytics is based on trusted data?
We tightly integrate the analytics capability with Data Engineering and Data Governance, ensuring that the pipelines feeding dashboards and models are built on high-quality, governed, and well-understood enterprise data.
What types of dashboards and analytics can you build?
We design executive dashboards, operational performance reporting, self-service analytical environments, specialized predictive models, and embedded analytics for internal or external applications.
When should an organization use advanced or predictive analytics?
When standard descriptive reporting is insufficient to answer the business question, and there is a need to understand complex relationships, forecast future trends, or detect anomalies within the data.
How does analytics support AI initiatives?
A mature analytics foundation provides the trusted, structured data, the established business context, and the semantic understanding required to build reliable and valuable machine learning or Generative AI applications.
How do you drive adoption of analytics across the enterprise?
By designing analytics around actual business workflows and decisions, providing targeted training, establishing an analytics operating model, and ensuring the data is trusted and accessible when users need it.

Turn enterprise data into decisions that move the business.

Build an analytics capability that gives leaders, teams and operations a clearer view of performance and a stronger foundation for what comes next.

Discuss Your Analytics Agenda Explore Modern Data Foundations