Business Intelligence & Analytics

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Cartes-fiches	14
Langue	English
Catégorie	Gestion d'entreprise
Niveau	Autres
Crée / Actualisé	12.12.2017 / 08.06.2020
Lien de web	https://card2brain.ch/box/20171212_business_intelligence_analytics
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Describe DIKW

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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.

How can we transform data into information?

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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.

How can we derive Knowledge from Information?

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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?

Define Data Warehouse using its main characteristics.

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

Describe the two different approaches in designing a data warehouse.

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top-down: user requirements

bottom-up: which data sources are available

Describe the ETL tasks.

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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

Why are the ETL tasks so important for Data Warehouses?

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ETL tasks ensure that the data in the DW is.

Relevant

Useful

Quality

Accurate

Accessible

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

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•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

Why is data visualization gaining importance?

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Data explosion

Humans are visual beings and sight is the key sense for information understanding

Need to harness this data for better decision making

What are the key benefits of data visualization?

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Facilitate awareness and understanding

Help to raise new question and supply answers

Generate insights

Make a point by telling a story

Elaborate on the human perception process.

Stage 1: Parallel, Pre-attentive, Shapes / Color / Spatial / Movement

Stage 2: Serial, Gestalt Principle, Pattern recognition

Stage 3: Goal-directed processing, Attention-driven, Objects held in visual memory

What are the Gestalt Principles and what do they do?

Proximity, Similarity, Continuation, Closure

they describe how people tend to organize visual elements into groups or unified wholes when these principles are applied

What are the 8 visual variables?

Position

Mark

Size

Brightness

Color

Orientation

Texture

Motion

What types of data are there?

Qualitative:
- Nominal: Members of a certain class eg. North, South, East, West
- Ordinal: Related by order e.g. low, medium, high for temperature
Quantitative:
- Discrete: With a well defined finite set of possible values eg. age
- Continuous: Takes any value within a range eg. temperature readings

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