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              Home | Global Practice Lines | Data Analytics

              Data Analytics

              Supply Chain, Strategic Sourcing, IT, Infrastructure, Data Warehousing, Business Intelligence, Reporting
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              Your data is trying to tell you something, is your business built
              to hear it?

              Data Warehouse Components

              • Source Data: This can include PO/AP, Expense, and P-Card data and from among other sources. Data needs to be passed from these systems to the data warehouse either on a transaction-by-transaction basis for real-time data warehouses or on a regular cycle (e.g. daily or weekly) for offline data warehouses.
              • Data Transformation: The Data Transformation layer receives data from the data sources, cleans and standardizes it, and loads it into the data repository. This is the ETL process that will be built upon the new data classification.
              • Data Warehouse: The actual storage of the cleaned data. This can be a physical server, hosted service, or part of a larger eSourcing suite.
              • Metadata: Examples of data warehouse metadata include table and column names, their detailed descriptions, their connection to business meaningful names, the most recent data load date, the business meaning of a data item and the number of users that are logged in currently.
              • Operations: Data warehouse operations comprises of the processes of loading, manipulating and extracting data from the data warehouse.
              • Reporting Layer: The data in the data warehouse must be available to the organization's staff if the data warehouse is to be useful. This can be accomplished by many different software packages, but business needs and access levels must be defined ahead of time.

              Supply Chain, Strategic Sourcing, Data Warehouse, Components, Metadata, Operation

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