A data warehouse is a key component of business intelligence, and is the core of data reporting and analysis. Data is uploaded from systems such as marketing and sales, and is stored with recent data alongside historical. This allows for comparisons to be made, and trends to be observed in terms of a business’ success. A typical data warehouse uses an ‘ETL’ model, meaning that the data goes through a process of extraction, transforming and loading. The end result is an organized, retrievable set of data, often with extraneous data removed during the process through ‘data cleansing’.
Data is organized into hierarchical groups, and categorized as either facts or aggregate facts. Managers and business professionals are then able to use the data for market research and decision support.Contratar a Data Warehouse Experts
OWD -dimensions -facts -snowflake schema -star schema -ETL/SSIS Documents -Design & Architecture Document -Information Sourcing -Mapping-Document -ETL - Strategy Document Data Quality Services (DQS) -The discipline of Data Quality Assurance -SQL Server DQS capabilities and features -Creating DQS solutions -The SSIS DQS Cleansing component -Matching Policies and Projects -Administering DQS
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Help required in these topics 1. Data warehouse software for integrating data from disparate (dissimilar) sources and how to use these 2. Tools, platforms and architecture available for handling big data and how to access and apply these 3. Software tools for collating and cleaning data and how to use these 4. Objectives and scope of the analysis (basics of statistics) 5. Types of data analysis an...