Lernkarten

Karten 14 Karten
Lernende 2 Lernende
Sprache English
Stufe Andere
Erstellt / Aktualisiert 12.12.2017 / 01.07.2019
Lizenzierung Keine Angabe
Weblink
Einbinden
0 Exakte Antworten 14 Text Antworten 0 Multiple Choice Antworten
Fenster schliessen

Describe DIKW

It shows a hierarchy of components contributing to an organizations intelligence.

•Data comes in the form of raw observations, e.g. temperature, scores, and bits of news.

•Information adds context to data; it is created by analyzing relationships and connections between the data.

•Knowledge is created by using the information for action. Knowledge answers the question "how".

•Wisdom is created through the use of knowledge and through reflection. It is the ultimate level of understanding.

Fenster schliessen

How can we transform data into information?

Condensation: Data is summarized. Unnecessary depth is eliminated.

Calculate: Data is analyzed mathematically or statistically.

Contextualization: We know why the data was collected.

Correction: Errors removed.

Categorization: Unit of analysis is known.

Fenster schliessen

How can we derive Knowledge from Information?

Comparison: How does this situation compare to others?

Consequence: What implications does the information have for decisions and actions?

Connection: How does this bit of information relate to others?

Conversation: What do other people think about this information?

Fenster schliessen

Define Data Warehouse using its main characteristics.

A Data Warehouse is a subject-oriented, integrated time-variant, non-volatile collection of data in support of management's decision-making process.

Fenster schliessen

Describe the two different approaches in designing a data warehouse.

top-down: user requirements

bottom-up: which data sources are available

Fenster schliessen

Describe the ETL tasks.

Extract data from source systems

Clean up data and transform it

Consolidate (index the data, summarize)

Restructure keys

Load data into the DW

Maintain the metadata

Refresh the DW with updated data

Fenster schliessen

Why are the ETL tasks so important for Data Warehouses?

ETL tasks ensure that the data in the DW is.

Relevant

Useful

Quality

Accurate

Accessible

Fenster schliessen

Which transformation problems could arise during the ETL process? List and describe them.

•Multipart keys: record key structures with built-in meaning

•Multiple local standards

•Complexity of integrating Multiple files

•Missing values

•Duplicate values

•Element names: variation in naming conventions in fields from source to source.

•Element meanings: different interpretations of the name of an element.

•Inconsistent Input formats

•Inconsistent data values

•Referential integrity constraints

•Name and address