Examples of using Data lake in English and their translations into Vietnamese
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The data lake allows an organization to shift its focus to a shared model to respond to the changing dynamics of information management.
Application of technology solutions developed on the information platform Big Data, Data Lake, Data WareHouse, BI, Automation, AI,… to serve the requirements of customers management and administration.
The data lake allows an organization to shift its focus from centralized control to a shared model to respond to the changing dynamics of information management.
in the cloud or in a Hadoop data lake.
Support of Docker containerized workloads means that data scientists/data engineers can bring the deep learning frameworks to the Apache Hadoop data lake and there is no need to have a separate compute/GPU cluster.
in the cloud or in a Hadoop data lake.
the difference is the CDP has built-in features to do additional processing to make the data usable, while a data lake may not.
The idea of data lake is to have a single store of all data in the enterprise ranging from raw data(which implies exact copy of source system data)
The main purpose of data lake is to have a single store of all data in the enterprise ranging from raw data(which implies exact copy of source system data)
In the data lake, build the full data management lifecycle with that data source before you start with unstructured sources, sensor data, streaming data, etc. That way, you know your foundation is really solid
This may seem like a basic piece of information, but we include it here because there still exists a tendency for IT to turn their data lake into a science project; they want to play with it and experiment and build a dream data repository.
providing a data lake that stores all of Uber's transactional and logged data,
Data lakes are not a magical solution.
Data lakes keep data in its original state;
Data lakes aren't just a place for data science work, and they're not a
AWS Lake Formation makes it easy for customers to build secure data lakes in days instead of months.
Data lakes are designed to make it easier for users to access vast amounts of data when the need arises.
Data lakes are storage repositories that hold extremely large volumes of raw data in its native format until the data is needed by business users.
Data lakes are designed to make it easier for users to access vast amounts of data when the need arises.