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8 Reasons why you need Synapse Analytics
A single service providing limitless analytics
In a recent survey by Harvard Business Review, 80% of respondents said their organisations are struggling to become mature users of data and analytics. 55% of them named data silos and data management difficulties as the biggest challenges to their data and analytics strategies. And 60% said they were embarking on going to the cloud for their analytics platforms, data management and data lakes.
If you, like them, and are looking to refresh your approach to managing your data, then you need to look at Microsoft’s latest data offering: Azure Synapse Analytics. It’s a limitless analytics service with unmatched time to insight. It will give you insights from all your data, across data warehouses and big data analytics systems, with blazing speed. If you are familiar with Azure SQL Data Warehouse, this is the newer, superior version.
Here are eight reasons why you need it:
1. Data storage is becoming problematic
As businesses are becoming digital, the demands for data and insights is putting pressure on data systems. Azure Synapse Analytics Synapse solves this by utilising capabilities such as massively parallel processing (MPP), result-set caching and clustered columnstore indexes. Built on Azure, you have near-infinite scaling of storage. And you only pay for what you use.
2. You can’t consolidate disparate data into a single location
When Gartner surveyed the top organisational challenges in deploying data and analytics, challenges with technology, infrastructure and architecture came out top. Azure Synapse Analytics solves this by no longer requiring you to maintain a data warehouse AND a data lake. Instead, you can have one single service to process your business analytics AND your data science. Latency is eliminated and decision making is accelerated.
3. You can’t perform query analysis across large data sets
Azure Synapse Analytics allows you to query both relational and nonrelational data at the petabyte scale. You can do this using the language of your choice. For mission-critical workloads, you can easily optimise the performance of all queries with intelligent workload management, workload isolation, and limitless concurrency.
4. You can’t shape, model, or transform data in real-time
Azure Synapse Analytics provides a workspace for data prep, data management, data exploration, data warehousing, big data, and AI tasks – all in the same place. This means that data engineers can use a code-free visual environment for managing data pipelines. Database administrators can automate query optimisation and data scientists can build proofs of concept in minutes. Business analysts, securely access datasets and can use Power BI to build dashboards in minutes—all while using the same analytics service.
5. Your reporting across large data sets is ad hoc
Not so with Azure Synapse Analytics. With ASA, you can enable practitioners to easily apply machine learning models to all your intelligent apps without any data movement. This significantly reduces project development time for BI and machine learning projects. Additionally, you can apply intelligence over all your most important data—from Dynamics 365 and Office 365 to software-as-a-service (SaaS) services that support the Open Data Initiative — then share this data with just a few clicks.
6. You’re heavily invested in Power BI already
Power BI is the leading business intelligence app and because Azure Synapse Analytics is also built by Microsoft there’s a lot of collaboration between the two platforms. Power BI workspace integrates directly with Synapse. You can access reports and datasets within Synapse studio, but can easily create new datasets and reports from the data you’ve curated in Azure Synapse. You can significantly reduce development time to embed analytics into the BI and ML projects. Power BI has previously been focused on business users but this move now puts Power BI firmly in the hands of data professionals.
7. You want to use SQL workloads in the way that you choose
Synapse goes further than using SQL to query across a range of data sources and formats. By giving you the option to run these workloads either on-demand, via a serverless compute model, or via provisioned capacity known as SQL Pools, you have more power at your fingertips. The new SQL Serverless option allows you to query data stored in your storage account or a data lake without the need to spin up any clusters or compute resource. You simply point your query at your data and you are charged based on the amount of data you read. What’s more, almost any existing tool set that supports SQL Server will work straightaway. Currently, supported formats are CSV, Parquet and Json. It’s even possible to query Spark tables without a Spark cluster running.
8. Data security is important to you
Microsoft is known for its expertise in data security. With Azure Synapse Analytics you can keep your data really safe. Microsoft provides advanced security and privacy features like automated threat detection and always-on encryption. They also enable you to ensure fine-grained control. This is done with column-level and row-level security, column-level encryption, and dynamic data masking. This all ensures that you will automatically protect sensitive data in real-time.
Azure Synapse Analytics is the only unified platform for analytics. It blends big data, data warehousing, and data integration into a single cloud native service. Now you can have end-to-end analytics at cloud scale.
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