Azure Data Lake Storage

Azure Data Lake storage is well suited for applications/use cases within organizations where capturing and storing large amounts of data in any format is required, primarily for storing and processing purposes. It's an easy and cost-effective cloud solution for your application data. The ability to integrate with other Azure Services like Azure Databricks and Azure Data Factory is superb.

Azure Data Lake Storage is great if it's used in a company where once configured no one goes in and make changes, and there is little to no need for growth over time. If it's a business that will be modifying it daily and constantly expanding, other vendors may have a more feasible option available.

Having short videos allows me to go back and study precisely the topics I need without sifting through 30-minute videos to find the vignettes I need. Using the labs, I got Associate Developer and Cloud Practitioner authorization. study for the certifications also to have them as a reference for work when you have any questions about applying a configuration to the equipment.

Azure Data Lake is best suited for organizations looking to capture large amounts of data to process and store it. Azure Data Lake will make this process easy and cost-effective as it allows you to also report on this data. It provides tools to clean and present it into tables, charts, and graphs, and will easily integrate with any existing Azure environments.

You should use Azure Data Lake Storage if you need to store large amount of data for analytical purposes, especially if combined with analytical solutions that support its API, like Azure Databricks or Azure Synapse Analytics. You should not use it for transactional workload, of course.

For handling big data, it works very well, the interface is friendly also it provides a great feature and capability for adding security layers in working with data, so good security features.
The big data compute clusters are easy to set up and the learning curve is somehow easy but still Microsoft needs to provide more intractive instructions.

Azure Data Lake Storage is built to help with large data analytics and transformations. It can be used as a single data repository for any structured and unstructured data extracted from almost any source. As it is built on top of the Hadoop file system (HDFS), jobs' overall analytic performance and running is quite impressive.
As some features are still in development phase, there are some improvements required to make this a unified storage solution for the organizations.

ADL is great for structured and unstructured data backups: files, folders, disks, VMs, and databases. It does this better than any platform we ever vetted, and Microsoft is the industry standard typically.

It may not be feasible or cost effective if you don't have that much data to implement, or if you're a smaller organization with two or less VMs/production servers.

Azure data lake storage is best tool where you need to manage lot's of data. They provide so many good features and good customer support. It's easily integration with different services. Costing of Azure data lake store is very high and maintenance is also high for small companies.

While I did not think it was the most difficult to deploy, I did feel that there were some steps that took time when migrating from our data warehouse to data lakes. More documentation would have been helpful but I expect this to improve as the user base grows. I find that I need to be more careful in writing my queries for optimization when using a data lake. Can be a little more cavalier in a warehouse.

We have used Azure Data Lake Storage to analyze our large dataset to understand and visualize it thoroughly. It is highly encrypted and is highly scalable. It helps us to organize our data well and distribute it basis on its size.

Azure Data Lake Storage is great and affordable for anyone needing to process large data sets with better flexibility when it comes to file systems, looking for scalability and added file-level security, as well as other features like Hadoop integration amongst others.

Azure Data Lake Storage was our first project using a true data lake concept. In our experience it was a great product as it was easy to implement and matched our footprint quite well. After our initial work and the improvements Microsoft worked on, it became a better tool for us to run our reports and ingest our data.

Azure Data Lake is an absolutely essential piece of a modern data and analytics platform. Over the past 2 years, our usage of Azure Data Lake as a reporting source has continued to grow and far exceeds more traditional sources like MS SQL, Oracle, etc.