When to consider Azure Analytics Modernization
Azure Analytics is a comprehensive suite of services from Microsoft Azure that enables businesses to collect, process, store, and analyze data from diverse sources in real time. It empowers organizations to gain valuable insights, make informed decisions, boost productivity, and reduce costs. With its flexibility and scalability, Azure Analytics helps businesses quickly adapt to evolving needs, innovate faster, and accelerate the delivery of new products and services.
Why Embrace
Azure Analytics Modernization?
Moving workloads to Azure offers businesses a flexible, scalable, and cost-efficient infrastructure, while also enhancing security and integration capabilities.
Performance
Automation
Scalability
Leverage modern data processing technologies such as Apache Spark and Apache Hadoop to speed up data processing, perform advanced analytics, and uncover insights more quickly.
Use Azure Data Factory to create end-to-end data integration and transformation workflows that automate data movement and processing across both on-premises and cloud environments.
Scale your analytics with Azure to match your business needs. Handle large volumes of data, run advanced analytics, and gain real-time insights into your operations.
Develop, deploy, and scale machine learning models using a variety of tools and frameworks to uncover insights and drive innovation across your business.
Innovate
Streamline your analytics projects and collaborate seamlessly with your team using Azure DevOps—from planning through to deployment—all in one integrated environment.
Collaborate
Ensure your Azure analytics workloads are secure with robust security monitoring and threat protection, keeping your data safe and your business compliant.
Security
Analytics Modernization Framework
Migrating workloads to Azure can provide businesses with a more flexible, scalable, and cost-effective infrastructure, along with enhanced security and integration capabilities.
Azure
Synapse Analytics
Azure
Databricks
Azure
Advanced Analytics Enablement
Speed up insights across data warehouses and big data systems with a powerful enterprise analytics service.
Quickly gain insights from all your data and build AI solutions within your Apache Spark environment in just minutes.
Discover hidden insights from diverse data sources, make smarter decisions, streamline operations, and elevate customer experiences.
Azure Analytics
Modernization Services
Define Business
Objectives
Assess the
current state
Design the
target state
Plan the Azure
Migration
Start by clarifying your business objectives and goals. Evaluate your current data sources and analytics tools to determine if they align with and support your business needs.
Assess your current data and analytics infrastructure—including data sources, storage, processing, analytics, and visualization tools. Identify any gaps or limitations and pinpoint areas that require modernization.
Establish your vision for analytics modernization, outlining your ideal data architecture, analytics tools, data management, and governance practices. Identify the key performance indicators (KPIs) you aim to track and enhance.
Create a migration roadmap that details the steps needed to transition from your current state to the target state. Define the sequence of activities, set timelines, and identify the necessary resources for each phase.
Perform Azure
Migration
Choose your
Azure stack tools
Configure an
Azure Environment
Optimize and
monitor
Choose the Azure analytics services that align with your business goals and target architecture. Consider options such as Azure Synapse Analytics, Azure Data Factory, Azure Machine Learning, and Power BI.
Configure your Azure environment by setting up data sources, storage, processing, analytics, and visualization tools. Implement security measures and access controls to maintain data privacy and ensure compliance.
Migrate your data and applications to Azure by leveraging Azure Data Factory to transfer data from existing sources to Azure storage. Utilize Azure Synapse Analytics for data processing and analysis, and Power BI to build visualizations and dashboards.
Continuously enhance your Azure analytics environment by tracking performance, pinpointing bottlenecks, and refining infrastructure and processes as needed. Apply best practices for data management, governance, and security to maintain a scalable, reliable, and secure analytics setup.