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Avesh Dhakal
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  • Morrisville, NC
  • United States
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Profile Information

My Web Site Or LinkedIn Profile
http://np.linkedin.com/in/aavesh
Professional Status
Consultant
Years of Experience:
5
Your Company:
TMW Systems
Industry:
Advocacy
Your Job Title:
Developer
How did you find out about DataScienceCentral?
Linkedin
Interests:
Finding a new position, Networking, New venture
What Other Analytical Website do you Recommend?
http://4058 Rambling Hills Drive

Avesh Dhakal's Blog

Success factor of the data warehouse and business intelligence implementation

Posted on June 16, 2014 at 2:30am 0 Comments

Data warehousing project is a complicated task that demands goals and resources from both business and technical departments. It is expensive but normally a basic project. If it is done by non experts and non skilled support, it can be an expensive and may cause project failure. Several business analysts believed most of the data warehousing projects are unsuccessful to meet their proposed objectives (Furlow, 2001).

Hwang and Xu (2007) have chosen eleven success…

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Modelling a Data Warehouse

Posted on June 8, 2014 at 7:54am 1 Comment

When designing a model for a data warehouse we should follow standard pattern, such as gathering requirements, building credentials and collecting a considerable quantity of information about the data or metadata. This helps to figure out the formation and scope of the data warehouse. This model of data warehouse is known as conceptual model. General elements for the model are fact and dimension tables. These tables will be related to each other which will help to identity relationships…

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Dimensional Modelling

Posted on May 29, 2014 at 4:12am 0 Comments

There isn’t any specific standard to model data warehouse. It can be built either using the “dimensional” model or the “normalised” model methodologies. Normalised model normalises the data into third normal form (3NF) whereas dimensional model collects the transactional data in the form of facts and dimensions. Normalised model is easy to use as we can add related topics without affecting the existing data. But one must have good knowledge of how data is associated before performing…

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Data Warehouse Architecture

Posted on May 20, 2014 at 12:30am 0 Comments

According to Weisensee et al., Data warehouse architecture follows following principles:

  • Data Sources
  • Data Warehouses
  • Data Marts
  • Publication Services

Extraction, Transformation and Loading (ETL):

ETL process is the foundation of BI. Success and failure of BI projects depends upon ETL process. It plays a vital role to integrate and enhance the worth of data. After the extraction, cleansing and arrangement…

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