As businesses grow, they generate massive amounts of data every day. They feel overwhelmed by the needs for bigger storage, faster processing, quicker insights, lower costs, higher security, and increasing regulations. Enterprises need to scale and modernize their data architecture and infrastructure to stay competitive and respond to the business and customer demands. They need to embrace the digital transformation journey with a modern data platform that can remove the feeling of being lost in the technology puzzle.
Why Embrace Azure Synapse Analytics?
Azure Synapse Analytics is a limitless end-to-end analytics service built on Azure cloud that combines data integration, enterprise data warehousing, big data analytics, visualizations, governance, and collaboration. With its SQL, Spark, and Data Explorer runtimes, it provides unique unified experience to ingest, explore, prepare, transform, manage and serve data at scale for business intelligence or machine learning needs.
Integrated Analytics Platform
Azure Synapse provides a single integrated platform that combines data integration, warehousing, processing, and visualization capabilities, eliminating the need for multiple tools and systems to perform these tasks. This provides a seamless end-to-end experience for data management and analytics.
Scalability, Performance, Cost
Azure Synapse is built on top of the Azure cloud platform, which provides the scalability and performance required to handle large volumes of data and support high-performance analytics. This allows organizations to handle growing data volumes, support business growth, and reduce costs.
Hybrid and Multi-Cloud Support
Designed to work seamlessly with both Azure and non-Azure data sources, Azure Synapse is a suitable solution for hybrid and multi-cloud scenarios. This provides organizations with the flexibility to choose the best infrastructure for their needs, while still benefiting from integrated analytics platform.
AI and Machine Learning
Azure Synapse provides built-in support for AI and machine learning, which allows organizations to gain insights and make data-driven decisions in a fast and reliable fashion. This includes the ability to perform real-time and batch data processing, and access to a wide range of analytics and visualization tools.
Data Visualization
Azure Synapse integrates fully with Power BI to provide interactive dashboards and reports, real-time data visualization, and ad-hoc data exploration. It also supports custom visualization using a variety of programming languages and tools, including R, Python, and JavaScript.
Governance and Security
Azure Synapse provides built-in governance and security features, such as in rest and in transit data encryption, data masking, access control, and auditing, which help organizations to comply with regulatory requirements and ensure data security and privacy. This reduces risk and increases trust in the data being used for analytics and decision-making.
Collaboration and Productivity
Azure Synapse provides a collaborative environment for data teams to work together on a single platform, which helps to improve collaboration and productivity. This includes features such as shared workspaces, comments, and versioning, which enable teams to work together more effectively.
Open and Extensible
Azure Synapse is built on open-source technologies, such as Apache Spark and Apache Kafka, and supports a wide range of programming languages and tools. This allows organizations to extend the platform to meet specific needs and enables developers to leverage existing skills and tools.
Azure Synapse Analytics Mastery at Scale
Discover current state infrastructure, challenges, and future state goals. With prioritized business requirements and processes, a high-level implementation design is defined, with sprint planning and training program.
Establish a Landing Zone that accounts for scale, network, security, governance, identity, and other technology solutions and integrations. Implement basic elements of business functionality to prove capability. Validate technology choices.
Gather detailed requirements to create detailed solution design and plan current sprint. Implement user stories and develop solution accordingly. Perform unit, system, integration, uat testing. Create training materials and assets.
Create and execute release management and deployment plans. Validate skill and service readiness, deliver trainings. Provide warranty and on-going support services to fix defects and performance issues. Evaluate solution and needs of other application support services.
What we do?
Adastra can help you plan and efficiently migrate your data to the Azure Cloud. As a Gold Microsoft Partner, you can tap into our vast expertise and rely on us to help you guide the way to creating a secure and cost-efficient cloud-based single shared repository of your data. Our Azure Synapse offerings are:
1
Assessment
Discover current solution landscape, define future state goals, and perform gap analysis. Define future architecture, TCO and create iterative roadmap.
2
Azure Synapse Modernization
Implement Centralized DaaS or Data Mesh using Adastra’s framework for fully integrated pipeline / sql / spark on Azure Synapse Analytics.
3
Azure Lakehouse Modernization
Implement Centralized DaaS or Data Mesh using Adastra’s framework for bronze / silver / gold data lake zones managed by Azure Synapse Analytics.
4
Data Warehouse Migration
Unleash new cloud analytics capability by migrating your premise data warehouse to Azure Synapse Analytics using Adastra’s accelerated migration.
FAQ
To effectively serve modern analytics, both data lake/spark engines (for advanced analytics) and SQL / data warehouse engines (for structured analytics) are required.
Adastra recommends Azure Synapse Analytics as the analytics foundation to seamlessly integrate both engines, to deliver a unified modern analytics platform.
Microsoft Azure Cloud provides you with multiple levels of security between the user and the analytics data at no additional cost.
Data protection:
- Data in transit
- Data encryption at rest
Access control:
- Object level security (tables/views)
- Row level security
- Column level security
- Dynamic data masking
Authentication:
- SQL login
- Azure Active Directory
- Multi-factor authentication
Network security:
- VNet
- Firewall
Threat protection:
- Threat detection
- Auditing
Data exploration is hugely simplified, irrespective of where it lives within Azure Synapse. Query the lake using T-SQL or explore your structured data using the big data processing power of Apache Spark, this flexibility provides persona-aligned access to all data.
Data engineers:
Simplify the steps to wrangle multiple data types from multiple sources, including streaming, transactional, and business data. Use a code-free visual environment to easily connect to data sources and ingest, transform, and place data in the data lake.
Data scientists:
Build a proof of concept in minutes and easily create or adjust end-to-end solutions. Provision resources as needed or simply query existing resources on-demand across massive amounts of data. Work with the language of your choice—T-SQL, Python, Scala, .Net, and Spark SQL.
Business Analysts:
Typically, a data professional can access and create datasets using Power BI and Analysis Services for ad-hoc and exploratory analysis within Azure Synapse.
Business Users:
Securely access datasets and use Power BI to build and consume dashboards available within Azure Synapse. Securely share data within and outside your organization through Azure Data Share.