Spørgsmål

Question 1

Hvad er kardinalitet

Answer 1

• 1-1 Betyder at i noget kun kan være i begge tabel 1 gang. Der kan kun være 1 Land
• 1-x En til mange: Der kan være et land, men mange forskllige mennesker i det land
• x-x Mange til mange:

Question 2

Natrual key

Answer 2

Kan entydigt forklare i en tabel - Entydigt hentyer til et produkt

Question 3

Atomisk granularity

Answer 3

• Ned på en række, så langt ned man kan slice
• Hvis noget slettes er det den nuværene. Hvad er det en række repræsentrere

Question 4

Bus Matrix

Answer 4

Matrix over dim og facts der er afhænige, eller når man kan slice gennem dem.

Question 5

Story telling

Answer 5

At guide læseren, mod den retning der ønskes. At sørge for der de visuele elementer matcher ønsket.

Question 6

MDM: Master data managment,

Answer 6

Sørger for der er en aurtoriativ (den vigtige) (1) sandhed - processer for at man kan validere. Opretholder en standartiseret sandhed gennem hele virksomehden - ved process håndtering

Question 7

Hvad er Profilering

Answer 7

Dataprofilering er processen med at undersøge de tilgængelige data fra en eksisterende informationskilde og indsamle statistikker eller informative resume om disse data. Formålet med disse statistikker kan være at: Find ud af, om eksisterende data let kan bruges til andre formål

Question 8

What are relational databases?

Answer 8

They are databases that have data stored in tables and any new information is automatically added into the table without the need to reorganize the table itself

A table can have multiple parents

Question 9

Metadata present a more complete picture of the data in the database than the data itself.

Answer 9

True

Question 10

In an SQL-based relational database, rows in different tables are related based on common values in common attributes.

Answer 10

True

Question 11

How can businesses get the most out of their data?

Answer 11

Unlock data through accurate storytelling

Question 12

What is Data Analysis? How does this work?

Answer 12

• Processing - Data analysis is the process of identifying, cleaning, transforming, and modelling data to discover meaningful and useful information.
• Selling Story - The data is then crafted into a story through reports for analysis to support the critical decision-making process.

Question 13

Diagnostic analytics? What is the process?

Answer 13

• Diagnostic analytics answer questions about why events happened
• Diagnostic techniques supplement findings from descriptive statistics to uncover the cause of events (e.g. why these events became better or worse)
  (1) Identify anomaly
  (2) Collect data related to anomaly
  (3) Use statistical techniques to discover relationships in these patterns

Question 14

Predictive analytics?

Answer 14

• Predictive analytics techniques use historical data to identify trends and determine if they are likely to occur again in the future
• Usually one outcome
• Includes statistical and machine learning techniques

Question 15

Prescriptive analytics?

Answer 15

• Prescriptive analytics help answer questions about which actions should be taken to achieve a goal or target.
• Analyses past data to estimate the likelihood of different outcomes (multiple outcomes)
• Uses machine learning techniques

Question 16

Visualizations? What is the goal of a visualisation?

Answer 16

• A visualization (sometimes also referred to as a visual) is a visual representation of data, like a chart, a color-coded map, or other interesting things you can create to represent your data visually.
• Ultimate goal - to present data in a way that provides context and insights, both of which would probably be difficult to discern from a raw table of numbers or text.

Question 17

Benefits of a good data model?

Answer 17

Data exploration is faster
Aggregations are simpler to build

Power BI Reports
Reports are more accurate
Writing reports takes less time
Reports are easier to maintain in the future

Question 18

What are the differences between fact and dimension tables?

Answer 18

Fact table
- Observational/event data
- Contains measures and numbers
- Distinct values in multiple rows

Dimension table
- Contains details about the fact table
- Unique values appear in one row

Question 19

What are hierarchies?

Answer 19

Natural segments in data that are capable of being decomposed
Systemic layers such as parent-child relationships or tree structures

Question 20

What is flattening the parent-child hierarchy?

Answer 20

he process of viewing multiple child levels based on a top-level parent is known as flattening the hierarchy.
These uses multiple columns to indicate multiple levels
Flatten the hierarchy so you can see multiple individual levels
In this process, you are creating multiple columns in a table to show the hierarchical path of the parent to the child in the same record.

Question 21

What is a role-playing dimension?

Answer 21

Role-playing dimensions have multiple valid relationships with fact tables, meaning that the same dimension can be used to filter multiple columns or tables of data.

Question 22

Why are role-playing dimensions important to understand?

Answer 22

As a result, you can filter data differently depending on what information you need to retrieve

Question 23

What is cardinality best practice?

Answer 23

Avoid one-to-one: Is not recommended because this relationship stores redundant information and suggests that the model is not designed correctly. It is better practice to combine the tables.
Avoid many-to-many: a lack of unique values introduces ambiguity and your users might not know which column of values is referring to what.

Question 24

Explain the types of cardinality within Power BI?

Answer 24

Many-to-one (*:1) or one-to-many (1: *) cardinality:
Describes a relationship in which you have many instances of a value in one column that are related to only one unique corresponding instance in another column.
Describes the directionality between fact and dimension tables.
Is the most common type of directionality and is the Power BI default when you are automatically creating relationships.

One-to-one (1:1) cardinality:
Describes a relationship in which only one instance of a value is common between two tables.
Requires unique values in both tables.

Many-to-many (.) cardinality:
Describes a relationship where many values are in common between two tables.
Does not require unique values in either table in a relationship

Question 25

What is best practice for relationships and cardinality?

Answer 25

A word of caution regarding bi-directional cross-filtering: You should not enable bi-directional cross-filtering relationships unless you fully understand the ramifications of doing so. Enabling it can lead to ambiguity, over-sampling, unexpected results, and potential performance degradation.

Arrows should point to fact tables

many-to-many relationships and/or bi-directional relationships are complicated. Unless you are certain what your data looks like when aggregated, these types of open-ended relationships with multiple filtering directions can introduce multiple paths through the data.

Question 26

Should BI be used on the tactical or stratigeic level

Answer 26

BI as a tactical solution is suboptimal because:

–It results in separate BI initiatives which might fail to be interconnected, use incompat-ible technologies and use different interpretations and measurements of data concepts(e.g. lifetime value of a customer)

–Tactical solutions might optimize local decision making, but provides no guarantee thatit contributes to the company-wide strategy or that the decisions made are also optimalat a company-wide level

–Governance of information and decision-making processes becomes very hard whenBI-initiatives are scattered across the organization.