Data Analytics Services

Accelerate speed to insight with advanced analytics and AI-powered insights

Is your data foundation limiting the impact of your analytics initiatives?

Disconnected systems, inconsistent pipelines, and poor governance lead to unreliable insights and low trust in analytics outputs. Modern data engineering practices are critical to building scalable, analytics-ready foundations for high-performing workloads.

Are legacy architectures restricting access to real-time insights?

Many enterprises still rely on batch-based architectures that delay insight delivery and slow decision-making. Real-time analytics requires modern data pipelines, streaming capabilities, and low-latency processing built for continuous insight generation.

Are your AI-powered analytics initiatives struggling to scale beyond pilots?

Many AI analytics initiatives stall due to poor data quality, limited trust in model outputs, and infrastructure not designed for AI workloads. Scaling AI analytics successfully requires the right data foundation, governance, and operational alignment.

Accelerate speed to insight with advanced analytics and AI-powered insights

Modern enterprises need more than dashboards and historical reporting. They need real-time analytics, predictive insights, and decision intelligence that help teams respond faster, forecast accurately, and uncover new growth opportunities. Gartner predicts that by 2027, 50% of business decisions will be augmented or automated by AI agents for decision intelligence, accelerating the shift toward AI-driven analytics across the enterprise.

We help organizations modernize analytics capabilities with Microsoft Fabric, Azure Synapse, Databricks, and AI-powered data analytics solutions that enable advanced analytics, customer analytics, forecasting, and ML-powered insights at enterprise scale.

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Our Data Analytics Services

Data Analytics Services Illustration

Data Analytics Consulting Services

We assess your current analytics maturity, identify capability gaps, and define a roadmap aligned to business objectives. Our consulting services help organizations modernize analytics strategies, improve data quality, and establish scalable, AI-ready analytics foundations across Microsoft Fabric, Azure Synapse, and Databricks environments.

Analytics Modernization Services

We modernize legacy analytics ecosystems using Microsoft Fabric, Azure Synapse, Databricks, Power BI, and Azure Data Factory. Through lakehouse modernization, unified data management, and scalable analytics architectures, we enable real-time analytics, AI-driven insights, and enterprise-wide analytics transformation.

Implementation Services

We design and implement modern analytics platforms across Microsoft Fabric and Databricks ecosystems—from data ingestion and lakehouse structuring to semantic modeling and analytics delivery. Our implementations enable governed, scalable, and high-performing analytics workloads built for advanced and AI-powered analytics.

Real-Time & Predictive Analytics Services

We help organizations operationalize real-time and predictive analytics using streaming architectures, forecasting models, customer analytics, and ML-powered analytics solutions. Leveraging Databricks Structured Streaming, Delta Lake, Microsoft Fabric, and advanced analytics frameworks, we enable faster, proactive, and data-driven decision-making.

AI Analytics & Decision Intelligence Services

We build AI-driven analytics solutions that combine machine learning, predictive modeling, and intelligent recommendations to improve operational efficiency and business responsiveness. Using Azure AI, Microsoft Fabric, Databricks Mosaic AI, and MLflow, we help enterprises scale AI analytics and decision intelligence securely across the organization.

Analytics Governance & Managed Services

We provide governance and ongoing management services to maintain secure, reliable, and optimized analytics environments. Our services cover data quality, lineage, access controls, performance optimization, streaming pipeline monitoring, model monitoring, and continuous enhancement of analytics workloads across Microsoft and Databricks platforms.

Talk to our experts who build scalable, AI-ready analytics ecosystems.

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Kumar Vellore
Kumar Vellore

MD - Data, Analytics
and EI

Gourav Poddar
Gourav Poddar

AVP-Global Client Partner

Our Implementation Roadmap

1

Requirement Gathering and Data Assessment

2

Analytics Architecture and Tooling Design

3

Data Modeling and Pipeline Engineering

4

Dashboard and Report Development

5

Advanced Analytics and AI Integration

6

User Adoption, Training, and Analytics Governance

Customer Impact

Seamless SAP Data Integration for Real-Time Analytics with Fabric

A diversified Kuwaiti holding company operating across industrial, hospitality, education, and real estate sectors modernized its SAP data architecture to improve analytics readiness and reduce reliance on manual reporting processes. By implementing a secure SAP-to-Microsoft Fabric integration framework, we established a scalable foundation for real-time analytics, enhanced data models, and enabled Copilot-driven analytics to support faster, data-driven decision-making.

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100% Connectivity Enablement

Full connectivity enablement between SAP and Microsoft Fabric environments.

60% Faster Integration Readiness

Faster integration readiness for analytics workloads.

50–70% Reduction in Manual Data Dependency

Reduction in manual data dependency for reporting and analytics.

Why LevelShift

  • Microsoft Solutions Partner and Specialized Partner for Data Analytics and Warehouse Migration
  • 100+ Data Analytics and Business Intelligence projects delivered
  • Winner Top 10 Data and Analytics Team Awards
Microsoft Solutions Partner
Microsoft Solutions Partner
Microsoft Solutions Partner
Microsoft Solutions Partner
Microsoft Solutions Partner
Microsoft Solutions Partner
Microsoft Solutions Partner
Microsoft Solutions Partner

Where are you in your Data Transformation Journey?

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Data Modernization Your Path to Data Transformation

Our Perspectives

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FAQs

Azure Synapse Analytics is designed for enterprise-scale SQL analytics, data warehousing, and integrated reporting within the Microsoft ecosystem. Azure Databricks is optimized for large-scale data engineering, real-time analytics, AI/ML, and lakehouse architectures powered by Apache Spark. Many organizations use Synapse for governed analytics and Databricks for advanced analytics, streaming workloads, and AI-driven insights.
Yes. Many enterprises combine Microsoft Fabric, Azure Synapse, and Databricks to support different analytics workloads. Fabric delivers unified analytics and business intelligence experiences, Synapse supports enterprise-scale analytics and warehousing, while Databricks enables real-time processing, advanced analytics, lakehouse architectures, and AI/ML-driven analytics at scale.
Databricks is often preferred for large-scale big data processing, streaming analytics, and AI-driven workloads due to its native Spark architecture and lakehouse capabilities. Azure Synapse is well-suited for integrated analytics, SQL-based warehousing, and Microsoft-centric data environments. The right choice depends on scalability requirements, workload complexity, and analytics maturity. Explore our Data Analytics Consulting Services to identify the platform best aligned to your business goals.
Yes. Modern analytics platforms support streaming analytics, predictive modeling, anomaly detection, and AI-powered insights. Technologies such as Databricks Structured Streaming, Microsoft Fabric Real-Time Analytics, Azure Event Hubs, and ML frameworks help organizations process and analyze data continuously for faster, data-driven decision-making.
Data quality and governance are maintained through lineage tracking, metadata management, validation frameworks, role-based access controls, and governance policies. Solutions such as Microsoft Purview, Unity Catalog, and native governance capabilities across Microsoft and Databricks ecosystems help ensure analytics environments remain secure, compliant, and trusted.
Costs vary based on the scope and complexity of analytics initiatives, including modernization programs, predictive analytics, dashboard development, AI analytics, or managed services. Engagement models typically include project-based delivery, fixed-scope implementations, or ongoing managed analytics support.
  • Big Data Analytics: Process massive volumes of structured and unstructured data at scale. We uncover hidden patterns, correlations, and trends across petabytes of information, turning data complexity into clear business intelligence.
  • Predictive Analytics: Forecast future outcomes using advanced statistical models and machine learning. Anticipate customer behavior, market shifts, and business opportunities before they happen—moving your organization from reactive to proactive.
  • Real-time Analytics: Monitor and analyze data as it flows. Get instant visibility into operations, customer interactions, and market conditions. Detect anomalies immediately and respond to critical events in real-time with maximum agility.
  • Performance Analytics: Track the metrics that drive business success. We deliver dashboards and reports that measure operational efficiency, reveal revenue drivers, and align teams around data-driven goals and continuous improvement.
  • Diagnostic Analytics: Discover the “why” behind your data. We drill into root causes using correlation analysis and data mining to diagnose issues, validate hypotheses, and develop targeted solutions that address core challenges.

Ready to modernize your analytics ecosystem for the AI era?

Talk to our experts