DWH LEC - Details

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These techniques are suitable for delivering a solution. But in case of decision-support systems, we do not know what query and operation needs to be executed in future.

System Processes

We have a fixed number of operations to be applied on the operational databases and we have well-defined techniques such as use normalized data, keep table small, etc.

System Processes

True or False: techniques applied on operational databases are not suitable for data warehouses.

TRUE

Involves determining when to start data extraction and the consistency check on data; Ensures that the tools, the logic modules, and the programs are executed in correct sequence and at correct time.

Controlling the Process

Data extraction takes data from the source systems. Data load takes the extracted data and loads it into the data warehouse.

Extract and Load Process

True or False: Data needs to be in an inconsistent state when it is extracted, i.e., the data warehouse should represent a single, consistent version of the information to the user.

FALSE

True or False: After extracting the data, it is loaded into a permanent data store where it is cleaned up and made consistent.

FALSE

True or False: Consistency checks are executed only when all the data sources have been loaded into the temporary data store.

TRUE

Involves converting the source data into a structure.

Transforming

Increases the query performance and decreases the operational cost.

Structuring

It will optimize the hardware performance and simplify the management of data warehouse.

Partition the Data

Is required to speed up common queries.; relies on the fact that most common queries will analyze a subset or an aggregation of the detailed data.

Aggregation

Involves removing the old data from the system in a format that allow it to be quickly restored whenever required.

Archiving

In order to recover the data in the event of data loss, software failure, or hardware failure, it is necessary to keep regular backups.

Backup and Archive the Data

The information generated in this process is used by the warehouse management process to determine which aggregations to generate.

Query Management Process

Is a method of defining the overall architecture of data communication processing and presentation that exist for end-clients computing within the enterprise. Each data warehouse is different, but all are characterized by standard vital components.

Data Warehouse Architecture

Simplifies data cleansing and consolidation for operational method coming from multiple source systems, especially for enterprise data warehouses where all relevant data of an enterprise is consolidated.

Staging Area

A place where data is processed before entering the warehouse

Staging Area

Is a segment of a data warehouses that can provided information for reporting and analysis on a section, unit, department or operation in the company., sales, payroll, production, etc.

Data Marts

Analytical and transactional processing should be kept apart as much as possible

Separation

Hardware and software architectures should be simple to upgrade the data volume, which has to be managed and processed, and the number of user’s requirements, which have to be met, progressively increase

Scalability

The architecture should be able to perform new operations and technologies without redesigning the whole system.

Extensibility

Monitoring accesses are necessary because of the strategic data stored in the data warehouses.

Security

Data Warehouse management should not be complicated.

Administrability

Is not periodically used in practice. Its purpose is to minimize the amount of data stored to reach this goal; it removes data redundancies.

Single-tier Architecture

Shows the only layer physically available in Single-tier Architecture

Source Layer

True or False: Cleaning and transforming the loaded data will slowdown the queries.

False

True or False: Controlling the process involves determining when to start data extraction and the consistency check on data.

TRUE

True or False: Data needs to be in an inconsistent state when it is extracted

FALSE

True or False: Structuring the data decreases the query performance and increase the operational cost

FALSE

True or False: There are five major processes that contribute to a data warehouse

FALSE

True or False: Consistency checks are executed only when all the data sources have been loaded into the temporary data store.

TRUE

True or False: Aggregation is not required to speed up common queries.

FALSE

True or False: Data extraction takes data from the source systems. Data load takes the extracted data and loads it into the data warehouse.

TRUE

True or False: After extracting the data, it is loaded into a temporary data store where it is cleaned up and made consistent

TRUE

True or False: Archiving involves removing the old data from the system in a format that allow it to be quickly restored whenever required

TRUE

Properties of data warehouse architectures should be able to perform new operations and technologies without redesigning the whole system.

Extensibility

A method used in data warehousing to refer to a system that is used to process the day-to-day transactions of an organization.

Operational System

True or False: A staging area simplifies data cleansing and consolidation for operational method coming from multiple source systems, especially for enterprise data warehouses where all relevant data of an enterprise is consolidated.

TRUE

True or False: The goals of the summarized information are to speed up query performance.

TRUE

Properties of data warehouse architectures management should not be complicated..

Administrability

Properties of data warehouse architectures that monitors the accesses are necessary because of the strategic data stored in the data warehouses.

Security

True or False: The principal purpose of a data warehouse is to provide information to the business managers for strategic decision-making.

TRUE

True or False: Each data warehouse is the same and all are characterized by standard vital components.

FALSE

True or False: Single-Tier architecture is not periodically used in practice. Its purpose is to minimize the amount of data stored to reach this goal;

TRUE

True or False: A warehouse database is updated from operational systems continuously, usually during office hours

FALSE

True or False: Meta Data summarizes necessary information about data, which can make finding and work with particular instances of data more accessible

TRUE

Properties of data warehouse architectures that analytical and transactional processing should be kept apart as much as possible.

Separation

Properties of data warehouse architectures should be simple to upgrade the data volume, which has to be managed and processed, and the number of user's requirements, which have to be met, progressively increase

Scalability

True or False: Data Warehouse applications are designed to support the user ad-hoc data requirements,

TRUE

True or False: Data Warehouse applications are designed to support the user ad-hoc data requirements,

TRUE

True or False: A data warehouse architecture is a method of defining the overall architecture of data communication processing and presentation that exist for end-clients computing within the enterprise.

TRUE

True or False: A data mart is a segment of a data warehouses that can provided information for reporting and analysis on a section, unit, department or operation in the company

TRUE

A set of data that defines and gives information about other data.

Meta Data

Is a system of files in which transactional data is stored, and every file in the system must have a different name.

Flat Files

The mechanism of extracting information from source systems and bringing it into the data warehouse

ETL

Extraction, Transformation, and Loading

Crucial in a data warehouse technique because it is supposed to improve data quality.

Cleansing

Primary data cleansing features found in ETL tools

Rectification, Homogenization

The core of the reconciliation phase.

Transformation

Two ways to carry load

Refresh, Update

Data Warehouse data is completely rewritten

Refresh

Only those changes applied to source information are added to the Data Warehouse.

Update

ETL or ELT: High amounts of data

ELT

ETL OR ELT: Data is transferred to it and moved back to DB. High network bandwidth required.

ETL

ETL or ELT: Easily add the calculated column to the existing table.

ELT

ETL or ELT: Low maintenance as data is always available.

ELT

ETL or ELT: It needs high maintenance as you need to select data to load and transform.

ETL

ETL or ELT: Transformations are performed (in the source or) in the target.

ELT

ETL or ELT: Data Remains in the DB except for cross Database loads (e.g., source to object).

ELT

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