{"id":41966,"date":"2023-03-22T07:06:47","date_gmt":"2023-03-22T11:06:47","guid":{"rendered":"https:\/\/centricconsulting.com\/?p=41966"},"modified":"2023-03-21T12:09:24","modified_gmt":"2023-03-21T16:09:24","slug":"improving-your-modern-data-warehousing-with-azure-synapse-analytics","status":"publish","type":"post","link":"https:\/\/centricconsulting.com\/blog\/improving-your-modern-data-warehousing-with-azure-synapse-analytics\/","title":{"rendered":"Improving Your Modern Data Warehousing with Azure Synapse Analytics"},"content":{"rendered":"
When it comes to data, the future of data analytics and insight lies in cloud data warehouses.<\/p>\n
With a traditional on-premises data warehouse, integrating existing operational data with semi-structured and unstructured \u201cbig data\u201d is a major technical challenge.<\/p>\n
Traditional or enterprise data warehousing solutions simply aren\u2019t scalable enough or cost-effective to support the petabytes of data we generate. The need to mitigate the risks and issues in a traditional data warehouse inspired change that led to the birth of cloud or modern data warehousing.<\/strong><\/p>\n A modern data warehouse lets you bring together all your data at any scale easily. It allows access to insights through analytical dashboards, operational reports or advanced analytics for all your users. And, it combines all your structured, unstructured, semi-structured and streaming data.<\/p>\n In this blog, we\u2019ll dive into how a specific tool \u2013 Azure Synapse Analytics<\/a> \u2013 improves your modern data warehousing experience.<\/p>\n When it comes to cloud storage at an enterprise level<\/a>, we all think about a data lake, which is raw storage of all structured and unstructured data.<\/strong> Some companies use Delta Lake<\/a> on top of their data lake, which is like a software layer to implement the atomicity, consistency, isolation and durability (ACID) transactions and many more features to the Data Lake.<\/p>\n <\/a><\/p>\n The above diagram is a classic example of a modern data warehouse in the Microsoft Azure environment. In Microsoft Azure, we refer to a data lake as Azure Data Lake Storage Gen 2 (ADLS Gen 2).<\/p>\n Before Azure Synapse launched, we used multiple tools to manage our data warehouse<\/a>. For ingesting and processing the data in the data lake, we used Azure Data Factory (ADF) to transform the data and orchestrate the different activities involved in the extract, load and transform (ELT) process.<\/p>\n To prepare and transform the data, we used Azure Databricks. To store the processed data, we needed a warehouse so we used Azure SQL Data Warehouse (rebranded as Synapse Analytics in 2020).<\/strong><\/p>\n And finally, we need to integrate with reporting tools like Power BI to create reports on the facts and dimension tables.<\/p>\n We needed each of these separate tools to process our data from start to finish.<\/p>\n Azure Synapse brings all the platforms of a data engineering project like a data lake, ELT\/ETL, a warehouse and reporting under one roof.<\/p>\n <\/a><\/p>\n Azure Synapse Analytics is a unified platform for data engineering projects where the developers can:<\/strong><\/p>\n Now that you can do all of these tasks within one platform, what does that mean for your day-to-day?<\/p>\n Moving toward Synapse isn\u2019t without its learning curves. Our journey of exploring Azure Synapse was tremendous and full of experiences where we realized the power of Platform Integration that Azure Synapse offers.<\/strong> Here\u2019s what we learned during our transition. The key features that make Synapse lucrative are:<\/p>\n Synapse Analytics allows organizations working in a siloed infrastructure to manage and analyze their data from a single place. It offers centralized management of data lakes and data warehouses.<\/strong><\/p>\n This feature enables businesses across industries to use their data much more securely, accurately and efficiently by collating insights from diverse data sources, warehouses and analytical solutions.<\/p>\n Today, we have many available options for cloud computing<\/a> and storage like Snowflake<\/a>, AWS<\/a>, GCP and so on. But Azure Synapse Analytics offers a cutting-edge advantage because of the existing Microsoft services (SSIS, SQL Server) user base. It is more economical and feasible to integrate the current architecture with Azure Synapse Analytics.<\/strong><\/p>\n The tool is growing day by day with a lot of new updates. We recommend working with a partner to ensure your transition to Azure Synapse Analytics is smooth and you\u2019re able to take advantage of its latest features.<\/p>\n\n Modern Data Warehousing Before Azure Synapse Analytics<\/h2>\n
How Azure Synapse Analytics Changed the Game<\/h2>\n
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Adapting to Azure Synapse Analytics<\/h2>\n
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Where Azure Synapse Analytics Fits Into Your Industry<\/h2>\n
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Conclusion<\/h2>\n