Modern Database Management - Self Check 10

________ is achieved by coordinating the flow of event information between business applications.

Application integration

________ provides a virtual view of integrated data without actually bringing the data into one physical database.

Data federation

________ can cause delays and extra work on information systems projects.

Dirty data

Total quality management (TQM) focuses on defect correction rather than defect prevention.

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A data governance committee is always made up of high-ranking government officials.

False

A data stewardship program does not help to involve the organization in data quality.

False

After the extract, transform, and load is done on data, the data warehouse is never fully normalized.

False

Data are moved to the staging area before extraction takes place.

False

Data federation consolidates all data into one database.

False

Data transformation is not an important part of the data reconciliation process.

False

Data which arrive via XML and B2B channels is always guaranteed to be accurate

False

Dirty data saves work for information systems projects

False

Generally, records in a customer file never become obsolete.

False

Master data management is the disciplines, technologies and methods to ensure the currency, meaning and quality of data within one subject area.

False

Quality data are not essential for well-run organizations.

False

Quality data does not have to be unique.

False

Retention refers to the amount of data that is not purged periodically from tables.

False

Static extract is a method of capturing only the changes that have occurred in the source data since the last capture.

False

The process of transforming data from detailed to summary levels is called normalization.

False

There are six major steps to ETL.

False

Update mode is used to create a data warehouse.

False

A data quality audit helps an organization understand the extent and nature of data quality problems.

True

A data steward is a person assigned the responsibility of ensuring the organizational applications properly support the organization's enterprise goals for data quality

True

Bit-mapped indexing is often used in a data warehouse environment.

True

Completeness means that all data that are needed are present.

True

Data quality is essential for SOX and Basel II compliance

True

Data reconciliation occurs in two stages, an initial load and subsequent updates.

True

Data scrubbing is a technique using pattern recognition and other artificial intelligence techniques to upgrade the quality of raw data before transforming and moving the data to the data warehouse.

True

ETL is short for Extract, Tranform, Load.

True

Joining is often complicated by problems such as errors in source data.

True

Loading data into the warehouse typically means appending new rows to tables in the warehouse as well as updating existing rows with new data.

True

One of the biggest challenges of the extraction process is managing changes in the source system.

True

Refresh mode is an approach to filling the data warehouse that employs bulk rewriting of the target data at periodic intervals.

True

The data reconciliation process is responsible for transforming operational data to reconciled data.

True

The major advantage of the data propagation approach to data integration is the near real-time cascading of data changes throughout the organization.

True

The uncontrolled proliferation of spreadsheets, databases and repositories leads to data quality problems.

True

User interaction integration is achieved by creating fewer user interfaces.

True

The process of transforming data from a detailed to a summary level is called ________.

aggregation

A(n) ________ will thoroughly review all process controls on data entry and maintenance.

audit

Improving ________ is a fundamental step in data quality improvement.

data capture processes

A technique using pattern recognition to upgrade the quality of raw data is called ________.

data scrubbing

A ________ is a person assigned the responsibility of ensuring that organizational applications properly support the organization's enterprise goals of data quality

data steward

Converting data from the format of its source to the format of its destination is called ________.

data transformation

A(n) ________ function converts data from a given format in a source record to a different format in a target record

field-level

Conformance refers to whether the data is stored, exchanged or presented in a format that is as specified by its ________.

metadata

Sound data ________ is a central ingredient of a data quality program.

modeling

In the ________ approach, one consolidated record is maintained from which all applications draw data.

persistent

Data propagation duplicates data across databases, usually with no ________ delay.

real-time

The process of partitioning data according to predefined criteria is called ________.

selection

A method of capturing data in a snapshot at a point in time is called ________ extract

static

An approach in which only changes in the source data are written to the data warehouse is called ________

update mode

User interaction integration is achieved by creating fewer ________ that feed different systems.

user interfaces

Completeness means that all data that must have a ________ does have a ________.

value, value