OLAP business databases & dashboards

13 important questions on OLAP business databases & dashboards

What are the different frequencies of ETL?

Extraction can happen any second
Transformation can happen every day
Loading can happen every week

What are the four transformation activities?

  • transfer: getting data from one system to another and for this you need things like middleware and software which interconnects applications.
  • cleaning: removing noise
  • integration: getting data from different databases and putting in one unified format
  • aggregation: in the back-end system we might have information stored per hour, and in the database we are more interested in how the management sees things and we need to integrate things on a daily or weekly level.

What are the advantages/disadvantages of an incremental load?

Advantages: less quantitative data traffic
Disadvantages: relatively complex to program, will take some time to work
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What are the three BI front-end applications?

  1. Query & reporting; static reports generated with SQL or SQL-generators via a meta layer
  2. OLAP; enables users to interactively analyze multidimensional data from multiple perspectives
  3. Data mining models; objective is to discover new valuable knowledge in databases

What is multi dimensional data?

  • Data is classified into measures and dimensions
  • Measures
    • Summable information concerning a business process
    • eg. profit, costs
  • Dimensions
    • Represent different perspectives on viewing measures
    • Are organized hierarchically
    • Hierarchy represents different levels of aggregation
    • e.g. Time: month, quarter, year, all times
  • Aggregating measures up to a certain dimension create a multidimensional view on the data (= data cube)

What are the OLAP operators?

  • Roll-up
  • Drill-down
  • Slice & Dice
  • Pivot or Rotate

How many cubes (i.e. Aggregations) are there in a multi-dimensional database with n dimensions?

  • No dimension hierarchies: 2n
  • With hierarchies

What is a snowflake schema?

A refinement of star schema where some dimensional hierarchy is normalized into a set of smaller dimension tables, forming a shape similar to a snowflake

Why a snowflake schema instead of a star schema?

Snowflake schema tackles the disadvantages of the star schema, because it is less restricted, smaller data volumes and the possibility to store aggregations

However, you lose the advantages of the star schema. It is not easily understood by end-users, high number of joints and no predictable/standard framework

Why use surrogate keys?

To save storage dimensions and space and increase performances

What are the three solutions by Kimball for slowly changing dimensions?

  1. Overwrite old value = restating (infrequent changes (e.g., new customer address))
  2. Add 'version number' field as part of the key (Small individual changes( e.g., store size has been enlarged))
  3. Add new column(s) to dimension table  (Suddenly big changes (e.g., new categorization))

What are business dashboards used for?

Provide visual displays of important information that is consolidated and arranged on single screen so that information can be digested at a single glance and easily drilled in and further explored

What are the 3 layers with design dashboard situation awareness?

  1. Capability of the management of being aware of what is happening around the company (perception of the elements in the environment)
  2. Understanding what that information means for the company now (comprehension of the current situation)
  3. Future (a projection of future status)

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