An introduction to Microsoft Azure Data Lake Analytics

2017-12-01T11:35:44+00:00 March 23rd, 2017|Azure|

If you’ve read our previous blog Saving the Banks: Is personal finance next for data driven transformation? we walked about how slow banks have been, in comparison to other industries, at indoctrinating digital transformation. It’s unusually due to the age of their legacy systems and the amount of critical data they hold, making updating them a challenge. Azure Data Lake and Azure Data Warehouse can help find a way around potential problems, as they can work with all your data, no matter how big or complex. This can help when it comes to shifting your legacy environment over to something much fresher.

 

What is Azure Data Lake?

Azure Data Lake is a highly scalable data storage and analytics service that includes the capabilities required to make it easy for developers, data scientists and analysts to store data of any size and shape and at any speed. Hosted on Azure, it removes the complexities of ingesting and storing all your data while making it faster to get up and running with batch, streaming and interactive analytics. It operates seamlessly with data warehouses, making it easier to shift your environment whilst minimizing the chances of losing any data.

What is Azure Data Lake Analytics?

Azure Data Lake Analytics is an on-demand analytical tool which can be used to simplify big data analytics. The data can be run through processing programs such as U-SQL, R, Python and .Net. Data Lake Analytics allows users to develop massively parallel programs with simplicity, by processing petabytes of data for diverse work categories. Instead of deploying, configuring, and tuning hardware, you write queries to transform your data and extract valuable insights.

Key benefits include:

  • Dynamic scaling – Data Lake Analytics dynamically provisions resources and let you do analytics on terabytes of data
  • Develop faster, debug and optimize smarter using familiar tools – due to the integration it has with Visual Studio, you can use familiar tools and resources to run, debut and tune your code.
  • Integrated seamlessly with other IT investments – Data Lake Analytics can use your existing IT investments for identity, management, security, and data warehousing, thus simplifying data governance.
  • Cost-effective – You pay on a per-job basis when data is processed. No hardware, licenses, or service-specific support agreements are required.
  • Works with ALL Azure data – optimized to work with Azure Data Lake; providing the highest level of performance, throughput, and parallelization for your big data workloads.