Data warehouse audit

At any enterprise, data is generated during its operations, and there is a need to store these data effectively. It's essential to create a data storage system that operates securely, reliably, and is scalable.
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An audit of a corporate data warehouse (CDW) based on the GreenPlum DBMS (and others) is carried out in order to verify the compliance of the existing data warehouse architecture with the strategic goals and objectives of the company, compliance with the applied Business Intelligence (BI) task classes with generally accepted standards for building warehouses.
The audit may be:

The audit is carried out for different purposes:


when creating a new system, when radically changing the approach, when introducing new technologies
relevant for working with large data warehouses
Formation of a list of actions to improve the efficiency of the data warehouse.
Eliminate errors that affect the operation of the data warehouse.
Identify and eliminate the causes that cause errors in the data warehouse.
Optimizing the time to access data warehouse items.
аудита и рефакторинга кода
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The purpose of the audit is to generate recommendations for improving the performance of the data warehouse.

Base plus

3 weeks
1. List of works given in the proposal "Basic."

2. Auditing data retrieval processes from sources.

3. Audit ETL processes and bring data to a single model.
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Basic audit

2 weeks
1. Study of the initial design and operational documentation, analysis of the architecture of the data warehouse model.

2. Verification of compliance of the hardware used with the approved CD architecture class (for storage on hardware).

3. System fault tolerance analysis.

4. Detection of data growth rate, methods of data compression

5. Analysis of distribution of data warehouse elements by segments, identification of data distortions (for distributed DBMS)


4 weeks
1. List of works given in the proposal "Basic plus."

2. Monitor data warehouse operations, analyze peak loads, and number of users.

3. Auditing User Role Model for Access to Central Objects

Audit results:

Recommendations for changing the structure of the data store/storage model to improve its efficiency.
Best practices for troubleshooting errors that affect data warehouse operations in ETL and data extraction processes.
Best practices for optimizing time to access DataStore objects.
Recommendations for improving data access security.
Recommendations regarding the results of the storage download.
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