Analytics

Amplifying Business Value with Data and AI

Empower your Workforce with Generative AI

Harness the power of Generative AI with our cross-industry solutions, to empower your organization to create dynamic, context-aware applications automate tasks, and revolutionize decision support systems.

Enterprise Data Warehousing

Equip your Enterprise Data Warehouse to meet the ever-growing demands of big data. We specialize in building a central data repository that unifies diverse data sources, upholds data quality, and ensures you have timely access to critical information.

Data Lakes and AI-Driven Analytics

We provide end-to-end solutions, including strategy, prototyping, data integration, and real-time processing, enabling real-time insights and informed decisions.

Maximize Data Value with Data Migration

Reduce data management costs and unlock the untapped value within your data. Our data migration expertise ensures a seamless transition, preserving data integrity while modernizing your data infrastructure.

Data Platform Modernization

Establish a trusted and reusable set of data products, paving the way for faster insights and smarter decision-making.

AI and Machine Learning

Leverage our ML frameworks to scale AI solutions that address your specific challenges. Activate the power of data to predict, decide, and act in ways that transform the way you work.

We construct your cutting-edge data platform and seamlessly integrate it with your existing systems, establishing the cornerstone for robust data analytics.

The Data Platform serves as the bedrock for managing business information and your organization’s data estates. It encompasses processes for ingesting data from diverse systems, transforming it with business rules, and implementing governance measures to facilitate the compilation of data that drives valuable business insights.

Our team of world-class data engineers is adept at guiding you through the design, construction, and maintenance of a dynamic Data Warehouse/Data Lake. This infrastructure is tailored to accommodate Big Data, manage large volumes, handle different data types, and execute massive data processing workloads.

Additionally, we offer expertise in legacy system retirement, enabling the replacement of traditional Data Warehouses with modern counterparts optimized for contemporary requirements in big data, analytics, real-time operation, high-performance, and cost control.

Recognizing that traditional Data Warehouses were not originally designed to handle the expanding volume, variety, and velocity of Big Data, our services facilitate the modernization of your Data Warehouse. This ensures its competitiveness, growth, and alignment with new business and technology requirements, particularly as evolving business practices demand more extensive and up-to-date data.

Our Data Platform Services

Data Ingestion

Data Lake

Data Transformation

Data Warehousing

Data Modeling

Data Governance

Big Data Engineering

Data streaming

Microsoft Fabric

The data platform for the era of AI

Embark on your journey with Microsoft Fabric Architecture and ensure you have the right partner by your side. Fabric stands as an end-to-end analytics product designed to cater to every facet of an organization’s data analytics requirements.

With Fabric, customers can leverage a single product featuring a unified experience and architecture. This all-encompassing solution equips developers with the capabilities to extract insights from data and present them to business users seamlessly. Delivered as software as a service (SaaS), Fabric ensures automatic integration and optimization, allowing users to sign up in seconds and derive real business value within minutes.

Fabric empowers every team involved in the analytics process by providing role-specific experiences. This means that data engineers, data warehousing professionals, data scientists, data analysts, and business users can find a familiar and conducive environment within the platform.

For a comprehensive design and assessment workshop with our experts, feel free to reach out to us. Let Microsoft Fabric be your ally in navigating the complexities of data analytics in the AI era.

Azure Data Platform & Services

Data warehousing and analytics

Azure Data Platform & Services: Data Warehousing and Analytics Architecture

In your organization, data sources may span various platforms, including:

SQL Server on-premises
Oracle on-premises
Azure SQL Database
Azure table storage
Azure Cosmos DB
Other legacy applications and databases

To streamline the integration of data from these diverse sources, various Azure components are employed:

•Azure Data Lake Storage: This serves as the staging area for source data before its loading into Azure Synapse.

•Data Factory: Orchestrates the transformation of staged data into a standardized structure within Azure Synapse. When loading data into Azure Synapse, Data Factory utilizes PolyBase to optimize throughput.

•Azure Synapse: Functioning as a distributed system for storing and analyzing large datasets, Azure Synapse employs massive parallel processing (MPP) for high-performance analytics. PolyBase is employed to swiftly load data from Azure Data Lake Storage.

•Analysis Services: Provides a semantic model for your data, enhancing system performance during data analysis.

•Power BI: A suite of business analytics tools utilized for data analysis and insights sharing. Power BI can query a semantic model stored in Analysis Services or directly query Azure Synapse.

•Azure Active Directory (Azure AD): Authenticates users connecting to the Analysis Services server through Power BI. Data Factory also leverages Azure AD for authentication to Azure Synapse via a service principal or Managed Identity for Azure resources.

Microsoft Analytics Architecture

Single Source of Truth

Establishing a data warehouse as a single source of truth for your data, ensuring consistency and reliability across the organization.

Relational Data Integration

Integrating relational data sources seamlessly with other unstructured datasets, fostering a unified and comprehensive view of the data landscape.

Semantic Modeling

Leveraging semantic modeling capabilities to create a meaningful representation of data, facilitating easier understanding and interpretation.

Powerful Visualization

Utilizing powerful visualization tools, such as Power BI, to create compelling and insightful visual representations of data for more effective and user-friendly analysis.

These use cases highlight the versatility and capability of Microsoft Azure Data Warehousing and Analytics Architecture in addressing a range of data-related challenges and opportunities within an organization.