Data Lake Analytics
For transforming raw data into insights that drive business.
Contrary to popular belief, a Data Lake is not merely a 'repository to store and process structured and unstructured data.' The lake is much more than that. Data Lake is the place where you put data that you have yet to prove the value of.
For instance, if you brainstorm a new external dataset that you have collected from scraping the web, you would want to land that data in the Data Lake. Then, you can merge that data with content from the enterprise data warehouse to prove out how valuable it is to different areas of the business.
Proving the value of data is a critical role of the Data Lake. Once proved, you can start with ETL operations to build a data pipeline for the valuable new dataset to land in your data warehouse, and with Data Lake analytics to extract valuable insights from the dataset.
Why Data Lake Analytics?
Intelligent Process Automation helps you with:
Data Lake analytics, combined with AI and ML, can be used to make accurate, profitable predictions.
Data Lake analytics helps R&D teams to test their innovative ideas by an evaluation of their hypothesis, refining their assumptions, and assessing the results.
Mozo’s Data Lake Analytics
MozoCloud helps you with:
Our experts help you choose the fitting technologies as well as vendors for your Data Lake analytics strategy. These choices will be based on your existing data warehousing systems, as well as investments.
After defining your schema, our experts will start querying - and deliver your required insights in seconds.
We continue working with you to build and manage more Data Lake solutions and help you talk to your data.