Azure Analytics Modernization 

Accelerate data-driven business growth by modernizing your analytics capabilities on the Azure cloud.

Adastra Named 2024 Data & AI Americas Partner of the Year

Adastra is proud to have won our 11th Impact Award this year—the Azure Data & AI 2024 Microsoft Americas Partner of the Year Award! We were also recognized as a finalist for three awards: Analytics Partner of the Year (Global), Business Applications (Americas), and Azure Infrastructure and App Innovation (Americas).

Azure analytics is a suite of services offered by Microsoft Azure for businesses to gather, process, store, and analyze data from various sources in real-time. It provides a range of tools and services that enable organizations to gain insights and make data-driven decisions, improving their decision-making processes, increasing productivity, and reducing costs. With Azure analytics, businesses can quickly adapt to changing business requirements and market conditions, innovate, and deliver new products and services faster.

Why Embrace Azure Analytics Modernization?

Performance

Take advantage of modern data processing technologies like Apache Spark and Apache Hadoop to accelerate data processing, perform complex analytics, and unlock insights faster than ever before.

Automation 

Leverage Azure Data Factory to build end-to-end data integration and transformation workflows that automate data movement and processing across on-premises and cloud sources.

Scalability

Scale your analytics to meet the demands of your business with Azure. Process massive amounts of data at scale, perform advanced analytics, and get real-time insights into your business operations.

Security

Get comprehensive security monitoring and threat protection for your Azure analytics workloads, helping you keep your data safe and your business compliant.

Collaboration

Manage your analytics projects and collaborate with your team in a single, integrated environment, from planning to deployment in Azure DevOps.

Innovate

Build, deploy, and manage machine learning models at scale, using a wide range of tools and frameworks to unlock new insights and innovation opportunities for your business.

Azure Analytics Modernization Services 

Azure Synapse Analytics

Accelerate time to insights across data warehouses and big data systems using an enterprise analytics service.

Azure Databricks 

Unlock insights from all your data and build artificial intelligence (AI) solutions with your Apache Spark environment in minutes.

Azure Advanced Analytics Enablement

Uncover hidden insights from disparate data, improve decision-making, optimize processes, enhance customer experiences, and drive innovation with advanced analytics on Azure.

Azure Analytics Modernization Framework

Begin by understanding your business objectives and goals. Identify the data sources and analytics tools that you are currently using and assess whether they are meeting your business needs.

Evaluate your existing data and analytics infrastructure, including data sources, storage, processing, analytics, and visualization tools. Identify the gaps and limitations in your current setup and determine the areas where you need to modernize.

Define your target state for analytics modernization, including your desired data architecture, analytics tools, data management, and governance processes. Determine the key performance indicators (KPIs) that you want to measure and improve.

Develop a migration plan that outlines the steps required to move from your current state to your target state. Determine the sequence of activities, timelines, and resource requirements for each step.

Select the Azure analytics services that best meet your business needs and target state. Consider services like Azure Synapse Analytics, Azure Data Factory, Azure Machine Learning, and Power BI. 

Set up your Azure environment by configuring your data sources, storage, processing, analytics, and visualization tools. Configure security and access controls to ensure data privacy and compliance. 

Migrate your data and applications to Azure by using Azure Data Factory to move data from your existing sources to Azure data storage. Use Azure Synapse Analytics to process and analyze the data and Power BI to create visualizations and dashboards.

Continuously optimize your Azure analytics environment by monitoring performance, identifying bottlenecks, and adjusting your infrastructure and processes accordingly. Implement best practices for data management, governance, and security to ensure that your analytics environment is scalable, reliable, and secure.

Azure Success Stories

Modernize Your Analytics on Azure

We will assess your current reporting and data platform and plan an Azure analytics modernization that gets insights to decision-makers faster.

Azure Analytics Modernization FAQ

What is Azure analytics modernization?

Azure analytics modernization means moving your reporting and data platform to Microsoft Azure services that gather, process, store and analyze data from many sources in real time. Organizations modernize to make faster, data-driven decisions, increase productivity and reduce costs, and to adapt quickly when business requirements or market conditions change.

Azure gives you faster processing with technologies such as Apache Spark and Hadoop, automated data movement with Azure Data Factory and the scale to process massive data volumes in real time. You also get security monitoring and threat protection for analytics workloads, collaboration in Azure DevOps and tools to build and deploy machine learning models.

Adastra follows an eight-step framework: define business objectives, assess the current state, design the target state with KPIs, plan the Azure migration, choose your Azure stack tools, configure the Azure environment with security and access controls, perform the migration, and then optimize and monitor the platform so it stays scalable, reliable and secure.

Azure Synapse Analytics is a Microsoft cloud service that combines big data and data warehousing in a single, end-to-end analytics solution. It processes and analyzes large data volumes in real time with tools such as Apache Spark, Azure Machine Learning and Power BI, and provides one workspace for data ingestion, preparation, management and governance.

Azure Data Factory is a cloud-based data integration service that creates, schedules and orchestrates data pipelines between on-premises and cloud sources. It offers a wide range of connectors and transformation capabilities, both graphical and code-based authoring, and monitoring with alerts, so you can track pipeline health and fix issues quickly.

Azure DevOps is a cloud-based suite of tools for software development, delivery and collaboration. It covers project planning, version control, continuous integration and delivery, testing and monitoring through Azure Boards, Repos, Pipelines, Test Plans and Artifacts. In analytics projects, it lets your team manage work from planning to deployment in one integrated environment.

UNIQA replaced three legacy data warehouses with a unified Azure and Databricks platform, improving data consistency, analytics speed and AI readiness. SCONTO Nábytek cut manual HR reporting work by 80% with Microsoft Fabric, and E.ON gained 70% higher sales potential for natural gas with an advanced analytics model that Adastra built in Databricks.

Adastra won the Azure Data & AI 2024 Microsoft Americas Partner of the Year Award, our 11th Impact Award, and was a finalist for Analytics Partner of the Year (Global), Business Applications and Azure Infrastructure and App Innovation in the Americas. We bring that Azure experience to every project, from assessment to optimization.