The development life cycle of QlikView implementations

Joe Smith, being a seasoned QlikView consultant, knows that for successful implementation he needs to follow the development life cycle of QlikView. At a high level, he will do the following:

• Gain an understanding of Adventure works' business
• Gather user requirements
• Analyze data model/data sources
• Follow data modeling best practices
• Load data
• Follow visualization/dashboarding best practices
• Create dashboard
• Deployment

About Adventure Works

Adventure Works Cycles, is a large, multinational manufacturing company. The company manufactures and sells metal and composite bicycles to North American, European, and Asian commercial markets.

Coming off a successful fiscal year, Adventure Works Cycles is looking to broaden its market share by targeting their sales to their best customers, extending their product availability through an external website, and reducing their cost of sales through lower production costs.

User requirements

At Adventure works, executive management wants to utilize QlikView to address the following:

• Create an enterprise wide, scalable Business Analytics platform where the information is easily available, shared, and collaborated
• Integrate data from different data sources
• Gain visibility into the company's key performance indicators
• Comparative analysis of data by different time periods
• Access relevant information quickly and efficiently
• Gain business insights to make better business decisions

Analyze data model/data sources

After understanding the business and business requirements, it's time to analyze the underlying data.

Adventure works is a relational database.

Management is interested in utilizing the data elements stored in the following tables. Tables are sourced from relational database, Excel files, and text files.

• Product
• ProductSubcategory
• Product Category
• Order Header
• Order Detail
• Customers
• Territory
• Employees
• Shippers

At high level, the tables from the source system have the following relationships:

Star schema and snow flake schema

QlikView can handle Star schema and Snow flake schemas effectively. Star schema is simple to understand. It is good for reporting as number of joins are reduced.

Star schema consists of dimensions and facts. It has a fact in the middle and dimensions surrounding the fact. The schema shapes like a star and hence the name star schema.

• Facts: A fact table contains numeric value. It contains a quantitative value such as sales, revenue, or profit.
• Dimensions: A dimension table contains textual description. Dimensions provide context to the facts, for example, sales by product.

Fact tables contain foreign keys of dimension tables. The following schematic represents the relationship between the fact and dimension tables:

In a snow flake schema, a dimension is not connected directly to the fact. It is connected to another dimension.

In Adventure works source data model, the dimension tables are:

• Customers
• Product
• ProductSubcategory
• Product Category
• Territory
• Employees

The fact tables are:

• Order Header
• Order Detail