How to Plan to Migrate Azure Synapse Analytics
Data Analytics / April, 11 2022

Points To Consider While Migrating to Azure Synapse Analytics

Migrating your data warehouse is a critical decision that all organizations plan to implement. Among several options in the market, selecting the best one requires detailed research and competitive analysis. Many organizations found Azure Synapse Analytics to be one of the cost-effective and faster options to migrate their data warehouse. However, before migrating to Azure Synapse Analytics, organizations should have some considerations to ensure a smooth migration. These considerations will help you understand whether the Azure Synapse analysis is the best fit for your organization or not.

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Do you have datasets of more than 1TB?

Having more data is useful when you have an adequate data warehouse to process it. If you have more than 1TB database, Azure Synapse Analysis is the best option. According to Microsoft, you should consider Azure Synapse when your database is nearing or crossing the 1TB data size.

Is your data warehouse taking too much time to process your data requests?

Azure Synapse is the best solution if your data workloads are massive, such as OLAP and Bigdata workloads, causing a delay in processing the data requests. How does Azure Synapse solve this problem? It splits the workloads into multiple pieces and executes them parallelly, which helps execute the large data loads. This feature also enables queries to run faster in Azure Synapse.

Do you need a unified platform for your business?

Who would not love to have all the required services under one umbrella? If you need a unified platform, Azure Synapse is the best option offering you a unified experience that includes data analytics and data warehouses services under one roof. It enables you to avail yourself of a unified platform where you can ingest, manage, prepare, explore, and serve data for ML and BI needs with some vital services such as SQL pools, Power BI, Spark pools, mapping data flows, etc.

Azure Synapse Studio comes in handy for the users to create an end-to-end analytics solution in a few clicks. From Data exploration- to experimentation, creating pipelines, developing graphical representations, and finally operationalizing the solutions using a single web-based UI.

Does your business need both non-relational and relational data queries?

Unlike other data warehouse solution providers, Azure Synapse enables you to query relational and non-relational data using SQL.

PolyBase technology allows access to extend data to the database through SQL language. Azure Synapse supports PolyBase technology to support this function.

Do you need a scalable, on-demand, and cost-effective solution?

With Azure Synapse, you can run huge data workloads either on provisioned capacity or on-demand. The serverless option enables you to query the data stored in our storage account without touching the cluster or compute resources. This feature enables organizations to pay for what they use or need. It is a cost-effective solution for the organization.

Does your business need a cloud solution that supports multiple scripting languages?

Suppose you want to process your data sets in multiple scripting languages. In that case, Azure Synapse is the best solution as it supports several scripting languages such as Spark SQL, Java, R, .NET, Python, SQL, and more. The feature of supporting plenty of scripting languages makes Azure Synapse the best option for data analytics and data engineering tasks.

Are you having problems executing the complex query?

Organizations with large data loads usually face problems in executing some complex queries in real-time. Azure Synapse Resources’ classes help users allocate the resources for specific queries with some limitations on the queries’ volumes that run concurrently and set the rules for computing. Queries running under a large resource class will also be executed smoothly. Query performance for the large sorts and joins can be improved if the resource class is large to execute it in memory.

Do you need real-time analytics without impacting workloads?

Azure Synapse Link for Azure Cosmos DB enables you to execute near real-time analytics over the operational data. Organizations can have real-time analytics without impacting the transactional workload performances on Azure Cosmos DB.

How to plan your Azure Synapse Analytics migration?

When it comes to preparing the Azure Synapse Analytics Migration, several activities need to be considered beforehand.

  • Start with defining the scope of migrating on-premises data to Azure Synapse.
  • Ensure Azure Synapse Analytics is the suitable solution for your data needs and offers faster and cost-effective solutions compared to on-premises data systems.
  • Create an inventory of the data and processes that need to be migrated.
  • Learn more about the differences between the Azure Synapse and the current on-premises data warehouse database management system (DBMS).
  • Start allocating the resources, budget, and human capital for the migration task. Provide essential training to the team members regarding migration.
  • Once the migration strategy is defined, identify the bottlenecks, contingency plans, and checkpoints.

Steps involved in migrating On-premises to Azure Synapse Analytics?

Once you have decided on the strategies, let us move to the implementation phase. During the implementation phase, you need to take care of some points to ensure smooth data migration to Azure Synapse Analytics.

  • Create the metadata for the migration process by solving the compatibility problems.
  • Export the schema for the tables by automating the entire process.
  • Prepare a list of historical data for the migration process that might be used in Azure Analytics.

When everything is ready to be migrated, ensure that all files are in the right format to be transferred to Azure Synapse Analytics.

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