We use the Azure Data Lake to store raw customer files exported from their databases. Our pipelines then pick up this data and process it in various ways. For instance, we use Databricks to handle the data processing, transformation, and ETL tasks. The processed data is then stored in SQL Server or converted into other file formats.
The tool's most valuable feature is security access policies.
The solution needs to improve APIs and make them more accessible.
The tool is scalable. We currently manage around 200 GB of data, and recently, we've optimized and synchronized additional data, which is approximately 500 GB. My company has 1000-2000 users who use it weekly.
We've had to seek help several times, particularly with Power BI and Databricks integrations. However, the initial level of support hasn't always been as knowledgeable as we'd like. They usually gather information and then schedule follow-up appointments, which can take a few days. Improving the expertise and responsiveness of the first-level support team could speed up the resolution process.
We use templates for deployment and automate the process.
The tool's licensing model is pay-as-you-go. Regarding pricing, there's always competition between Azure Data Lake Storage and AWS. They're quite similar, but to attract more customers, Azure Data Lake Storage could consider adjusting its pricing to be more competitive with AWS. This might make Azure Data Lake Storage a more appealing option for users.
The tool is the best platform for storing all kinds of data; I've never experienced any downtime with it. Plus, it offers secure access and security features, which I appreciate. I rate the product a nine out of ten.
