If a data lake isn't well managed and governed, it can become more of a swamp than a lake. Data is dumped into the platform without suitable oversight and documentation, making it difficult for data management and governance teams to keep track of what's in the data lake. That c...
A data lake stores the raw data from various data sources in a standardized open format. However, use cases such as data exploration, Interactive Analytics, and Machine Learning require that the raw data be processed to create use-case-driven trusted datasets. For Data Exploration and Machine Le...
the data lake can become a messy dumping ground for data. Users might not find what they need, and data managers might lose track of data stored in the data lake, even as more pours in.
Use Case #1: Data Ingestion Thedata ingestionprocess involves moving data from a variety of sources to a storage location such as a data warehouse or data lake. Ingestion can be streamed in real time or in batches and typically includes cleaning and standardizing the data to be ready for a...
Examples of data ingestion include migrating your data to the cloud or building a data warehouse, data lake or data lakehouse. This diagram shows how managed data lakes automate the process of providing continuously updated, accurate, and trusted data sets for business analytics. Use Case #2:...
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From the data lake, the information is fed to a variety of sources – such as analytics or other business applications, or to machine learning tools for further analysis. A data lake use case Here are two examples of a data lake use case in retail. Long term sales data is stored in a...
Use case tutorials: Cloud Pak for Data v5.x Playlist (1h 47m) 5 videos IBM watsonx.governance service v2.x Playlist (32m) 2 videos Data connections: Cloud Pak for Data v5.x Playlist (8m) 4 videos Get started: Cloud Pak for Data v5.x ...
Dixon, the CTO of Pentaho and the creator of the term “data lake”, presents a challenge to the big data community in his blog “Union of the State - A Data Lake Use Case”. Dixon argues that it is time to start figuring out how to make the data lake a time machine for a ...
Ultimately, the choice between a cloud-based and on-premise data lake depends on factors such as organizational requirements, budget constraints, and the specific use case for the data lake. Many organizations opt for a hybrid approach, combining elements of both cloud and on-premise solutions to...