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Three Ways Azure is Managing Big Data

Posted in Azure

Big Data is commonly known as data that surpasses norms of traditional database analysis and is primarily seen as the byproduct of three factors: volume (quantity), variety (type), and velocity (frequency). With Big Data, an organization has the ability to capture insights needed to make better business decisions and strategic moves. However, even with all of that data, if an organization doesn’t know how to properly optimize the analysis of data and turn it into tangible results, then it is in essence, wasted.

In research conducted by IDC, it was surmised that Big Data and business analytics revenues will reach $150.8 billion by the end of this year. With an impact of that size, Big Data needs a solution that will allow companies to maximize data analysis and reap the benefits. Luckily, Microsoft answered the call with Azure and its three complimentary parts: Data Lake Store, Data Lake Analytics, and HDInsight.

Azure Data Lake Store

Azure Data Lake Store is a no-limit solution to empowering intelligent action. By running large scale analytic stems through spreader file parts over a variety of servers, the Store has the inherent capacity for native data storage with no transformations required. Schemas aren’t required either, as data in analytic framework form their own conclusions when the time arrives. Since files of all sizes and formats can be stored, the Store can work with data whether structured, unstructured, or somewhere in-between. With the Store’s scalability, parallel programs can be developed that correspond with already in place security and support measures.

The Azure Data Lake Store analyzes with no constraints; trillions of files can be held, with a single file able to exceed one petabyte. By extending security to the cloud, the Store ensures further security measures can be met through auditing of access/configuration changes to the system. Data encryption occurs continuously, whether via SSL or Azure Key Vault, and role-based access controls can be divvied out at will. The Store supports any app based in Apache Hadoop Distributed File System. As such, the migration of Hadoop data to the cloud can happen without the recreation of the file systems.

Data Lake Analytics

Data Lake Analytics pools together services to empower data reconfiguration among a number of programs. Due to its lack of infrastructure, Analytics can process and scale data instantaneously on a pay-per-job system. With Azure Data Lake Analytics, processing power can be scaled precisely to what is required for a job; furthermore, any code written in U-SQL is made parallel and scalable at its creation. Analytics’ environment continually reviews programs and doles out performance enhancement and cost reduction tips, simplifying the debugging and optimizing of Big Data programs.


HDInsight is the premier Cloud Hadoop source, enabling data processing in distributed IT settings and serving as a natural transition for those already using Hadoop. Through its optimization of open source analytic clusters, Big Data technologies and IV applications are deployed with increased security. Likewise, data assets receive optimal protection with the backing of the Cloud archetype, and the Azure Active Directory enables identification while still retaining single sign-ons. HDInsight renders pre-integrated clusters immediately compatible with Hadoop’s large market of ISVs, thanks to already ingrained edge nodes and script action. With HDInsight, Hadoop is deployed without initial payment or additional hardware expenditures, as everything is coordinated through Azure.

Making Azure and Big Data Possible 

With its three interworking solutions, Azure is ensuring that Big Data can be handled, no matter how it evolves in the future. The challenge is understanding the best way to move forward – to begin utilizing Big Data with Azure’s capabilities. With Unified Cloud Management for Azure, COMPAREX can help architect your Azure environment so that your organization can maximize the data flowing in. Using a pragmatic and methodical approach, our teams assist with the architecture and deployment of customized cloud-based solutions. Not to mention with our proprietary monitoring and reporting dashboard, you can always be in the know when it comes to your expenditures and usage.

Kick start your Big Data journey with Azure and we’ll be there every step of the way.

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