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AWS Self-Service Reporting Infrastructure Tool Evaluation
Introduction
Ease of use of the AWS data warehouse is one of the key tenants of the AWS DW team. Currently AWS DW customers connect directly to data warehouse databases (RO & Primary) and use SQL to extract the data. Providing a general-purpose and self-service reporting infrastructure significantly reduces the effort spent by data warehouse customers to exact data and subsequently build metrics decks and dashboards. Oracle Business Intelligence (OBIEE) and Tableau are being evaluated for their suitability for our AWS data warehouse customers.
We are recommending Tableau. We have determined that it provides the best self-service experience for general purpose reporting needs and for more advanced data analytics and data visualization needs of the users of the AWS data warehouse.
Problem Statement
AWS data warehouse customers build and maintain SQL’s to extract data from the data warehouse. Once the raw data is extracted, it is often combined with custom data for individual services. Metrics on excel worksheets are then generated/updated. These excel worksheets are circulated to service team members and leadership for analyzing the usage and revenue of their products and also for identifying opportunities for operational improvements. Most tasks that involve creating the metric desks are manual, consuming significant effort of the data warehouse customers. The manual efforts are typically error prone and associated with the high overhead of maintaining the SQL portfolios.
Modern reporting tools overcome the barriers to easily consume the data in self-service fashion and present opportunities to automate the metrics deck building/updating. In addition, adopting a reporting tool flips the time spent in data extraction to analysis and decision making. OBIEE and Tableau were evaluated by the AWS DW

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