Reference no: EM134046231

Assignment:

Case: Data Warehouse or Data Lake?

A data lake is a vast pool of raw data, the purpose for which is not yet defined. A data warehouse is a repository for structured, filtered data that has already been processed for a specific purpose. Here are a few primary differences between data lakes and data warehouses:

. Data storage: During the development of a data warehouse, a considerable amount of time is spent analyzing data sources, understanding business processes, and profiling data. The result is a highly structured data model designed for reporting. Data lakes retain all data-not just data that is in use today but data that may be used and even data that may never be used but may one day have value.

. Data types: Data warehouses generally consist of data that is extracted from transactional or source systems and consist of quantitative metrics and the attributes that describe them. A data lake saves all data in raw form, regardless of source and structure.

. Data users: Data warehouses support operational and managerial users generating reports for KPIs and CSFs. These users favorite tool is the spreadsheet, and they create new reports that are often distributed throughout the organization. The data warehouse is their go-to source for data, but they often go beyond functional boundaries. The data lake supports all of these users equally well. The data scientists can go to the lake and work with the very large and varied datasets they need, while other users make use of more structured views of the data provided for their use.

. Data change: One of the chief complaints about data warehouses is how long it takes to change them. Considerable time is spent up front during development to get the warehouse structure right. A good warehouse design can adapt to change, but because of the complexity of the data loading process and the work done to make analysis and reporting easy, these changes will necessarily consume some developer resources and take some time. In the data lake, on the other hand, since all data is stored in its raw form and is always accessible to someone who needs to use it, users are empowered to go beyond the structure of the warehouse to explore data in novel ways and answer their questions at their pace.

Questions

1. In a group, explain the difference between a data warehouse and a data lake along with the advantages and disadvantages of each.

2. Provide a few business examples of when you would use a data warehouse and when you would use a data lake.