The modern business world is fast progressing on the path of reaching 175 ZB of data by 2025. As incredible as it sounds, what defines a truly successful organization in today’s data-led world is the willingness and ability to build modern data estates, find meaning in an increasingly complex myriad of data sources and data silos, and incorporate agility, speed, and innovation into data-driven business decisions.
Indeed, data defines the modern-day business environment. But how C-suites and business executives approached data in the past has taken a 360-degree turn. Traditionally, unstructured and scattered data sources led to incomplete data and increased costs due to poor decision-making.
However, we now reside in an era where every business app and platform that an organization uses must be intelligent, agile, adaptable, and flexible to real-time data modeling. However, due to the scattered nature of today’s complex databases and the silos between fragmented databases and intelligent analytic solutions, organizations aren’t able to keep up with the speed and agility required in today’s fast-paced business landscape.
Today’s incredibly complex data estates and the need to unlock meaningful insights and drive innovation calls for data modernization and data migration to the cloud to incorporate scalability, flexibility, and agility in business operations. What data engineers need is a modernized, intelligent data platform that brings together data integration, data warehousing, big data analytics, machine learning, and data governance under a single roof.
Data estate modernization is a tough row to hoe. It requires a lot of heavy-lifting and the ability to address common challenges that enhance the complexity of the entire process.
Some of these obstacles include the inability to process large volumes of data, data discoverability, overflow (serverless data platforms, AI, machine learning, DevOps, data lakes, etc.) or the lack thereof of the right tools and technology, budgetary constraints, and the lack of specialized education and in-house skills sets and knowledge base.
Overcoming these challenges is crucial to successfully implementing a data estate modernization and migration project, and achieving the following:
- Enhanced innovation
- Improved decision-making and performance
- Lower costs
- Advanced security and reduced risk
- Powerful analytics ability
Introducing Azure Synapse Analytics for Data Estate Modernization
What organizations need is the resources and technology to democratize decision-making and foster a data culture that promotes insight-driven decision-making. Indeed, every organization, especially large and complex ones, needs an architectural approach to scale the adoption of analytics, what is commonly known as a Data Mesh.
Simply put, a Data Mesh helps implement enterprise data platforms in large organizations and scale adoption beyond a single platform and implementation team. Unlike many organizations that can combine modern architectural and analytics patterns with big data and warehousing technologies, enterprises, in general, implement monolithic solutions where a single team does all the data integration.
By allowing distributed teams to share and work with information in an agile, decentralized manner, a Data Mesh overcomes the biggest flaw of this system, i.e., one team cannot have experts for every kind of data.
And that’s where Microsoft’s Azure Synapse Analytics also comes into the picture. Azure Synapse Analytics, clubbed with Data Lake Storage Gen2 and SQL data, act as the essential components for implementing a data mesh. A modern-day cloud data warehouse platform, Azure Synapse Analytics facilitates data estate modernization by bringing together data from different sources to create a unified data environment that enables the three pillars of data estate modernization and warehousing, i.e., extract, transform, and load (ETL).
Putting data warehousing, enterprise data analytics, and data integration under a single roof, Azure Synapse Analytics serves immediate business analytics and machine learning needs, building an intelligent data platform to leverage cloud-related benefits such as lower costs, unmatched scalability, blazing speed, and unparalleled security.
A limitless analytics service, Azure Synapse Analytics delivers a unified data analytics experience by eliminating data barriers and discovering powerful insights from all operational and business apps data with no data movement needed. Azure Synapse Analytics Link allows organizations to converge enterprise-wide data loads, experience limitless scale, and query both relational and non-relational data using their chosen language.
Azure Synapse Analytics: Features that facilitate Data Estate Modernization
Native Integrations
Azure Synapse Analytics’ native integration with Delta Lake and Spark Pool makes it a wonderful choice for large businesses looking to leverage big data applications (AI and ML) to extract, transform, and process enormous volumes of data.
Cost-effectiveness
Compute cost is calculated hourly, so in an instance where your data warehouse was active for only 20 hours in a month, you will be billed for those 20 hours only.
Platform-as-a-service
A PaaS solution, Azure Synapse Analytics also offers a free Azure Workspace environment, consisting of functionalities like Power BI and Azure Active Directory, alongside cloud computing resources.
Scalability
A dedicated SQL pool with a pre-defined unit of scale and a serverless SQL pool that scales automatically make Azure Synapse an excellent option for huge data loads running in TBs.
No-code hybrid data integration
Easily ingest data from 95+ connectors by building ETL/ELT processes in a code-free visual interface.
Enterprise-grade security
Unparalleled data privacy and protection with robust security features, including data masking, always-on encryption, column and row-level security, and column-level encryption.
Case-in-review
Also learn why you should choose Azure Synapse Analytics and how it is in comparison with Snowflake
How can we help?
As a Microsoft Gold and Azure Analytics Advanced Certified Partner, Acuvate helps clients achieve seamless data migration and modernization by offering flexible deployment models for Azure Synapse Analytics.
Our Azure managed services help you modernize your data estate and uncover maximum value from cloud migration, making your business more agile, flexible, and cost-efficient. Our team of experts helps you with data estate modernization strategy, cloud-native development, application modernization, AI, ML, and IoT, helping you manage your data workloads and unlock valuable insights.
For more details, please feel free to schedule a personalized consultation with our experts.
