Data warehouse diagnostic

Pain points: Review of existing implementation Performance of Data warehouse is below expectation Data loading and transformation is below expectation ETL Process do not result in accurate data Business Analysts and Data Scientists are not able to leverage data for reports or Data Models Objective: To Identify the causes of slow or ineffective performance and give recommendations for better performance Deliverables: Analysis of current Data warehouse, ETL process and database parameters Identification of Gaps leading to performance degradation Recommendations for improving performance and potential technology choices High Level Execution Plan Requirements from Client: Data Architecture and Data Flow Documentation of data sources, targets, data transformations frequency of data and data quality Tooling related information and configurations Availability of Source SMEs and BI SMEs Scope: Databases in scope: Oracle, PostgreSQL, MySQL, MS SQL, Teradata, Amazon Redshift, BigQuery, Azure Synapse, Snowflake, Oracle Exadata Data warehouse + 1 Datamart (maximum of 100 tables and views and 50 procedures & functions) (for larger sizes, we can provide customised quote) Services to be provided through Remote Delivery Time Period: 4-5 weeks