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DATA GOVERNANCE EXAM 1 REVIEW QUESTIONS AND ANSWERS

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DATA GOVERNANCE EXAM 1 REVIEW QUESTIONS AND ANSWERS Difference Between Data and Information - CORRECT ANSWER

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DATA GOVERNANCE EXAM 1 REVIEW QUESTIONS AND
ANSWERS
Difference Between Data and Information - CORRECT ANSWER✅✅𝐃𝐚𝐭𝐚:

• Raw facts with no context.

▪ E.g., Name: John Smith

Age: 20

DOB: 3/13/2000

Major: Finance

Salary: $20,000



𝐈𝐧𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐨𝐧:

• Processed data arranged in a meaningful way to facilitate decision making.

▪ E.g. "At age 20, John was earning $1,000 a month while studying finance."



𝐊𝐞𝐲 𝐏𝐨𝐢𝐧𝐭𝐬:

• Data constitutes the building blocks of information.

• Information is produced by processing data

• Information is used to reveal the meaning

• Accurate and timely information is essential to good decision-making.



What is a Database? - CORRECT ANSWER✅✅𝐃𝐚𝐭𝐚𝐛𝐚𝐬𝐞:

• A database is a shared, integrated software structure that houses a collection of:

▪ Data (raw facts of interest)

▪ Metadata (Data about data or information about data's structure and meaning).



𝐃𝐁𝐌𝐒:

• Database Management System (DBMS) is a collection of programs that manage the database and
control its access, making it possible to share the data with applications and users.

,Typical DBMS Capabilities - CORRECT ANSWER✅✅• Data dictionary



• Query and reporting



• Data presentation for different users



• Backup and recovery



• Data integrity management



Relational DBMS - CORRECT ANSWER✅✅• Represent data as two-dimensional tables.



• Each table contains data on entities and attributes.



• Table: Grid of Columns and Rows

▪ Rows aka records

▪ Fields (aka columns) - represent attributes and store values.

▪ A primary key uniquely identifies each record.

▪ A foreign key is a primary key from one table used as a lookup value to identify records in another
table.



Problems with Traditional File Structure - CORRECT ANSWER✅✅• Files maintained separately by
different departments.



• Data redundancy - unnecessarily duplicated data.



• Inconsistent data

▪ E.g., John Smith's age vs his DOB

,• Lack of flexibility and data sharing.



• Poor security.



Data Modeling - CORRECT ANSWER✅✅𝐃𝐚𝐭𝐚 𝐌𝐨𝐝𝐞𝐥𝐢𝐧𝐠:

• The basic building blocks of all data models are entities, attributes, and relationships.



• Entity - person, place, thing, or event for which data.



• Attribute - characteristic of an entity.



• Relationships - describe the association among entities:

▪ 𝐎𝐧𝐞-𝐭𝐨-𝐦𝐚𝐧𝐲 (𝟏:𝐌):

- A painter paints many different paintings, but each one is painted by only one painter.



▪ 𝐌𝐚𝐧𝐲-𝐭𝐨-𝐚𝐧𝐲 (𝐌:𝐌):

- Employee learns many job skills, each job skill might be learned by many employees.



▪ 𝐎𝐧𝐞-𝐭𝐨-𝐨𝐧𝐞 (𝟏:𝟏):

- A Verizon manager oversees one store.



Logical vs Physical Model - CORRECT ANSWER✅✅



Big Data - CORRECT ANSWER✅✅• Massive sets of structured and unstructured data from web traffic,
social media, sensors, etc.



• Volumes of data are too great for a typical DBMS

, • Can reveal more patterns and relationships.



• At its core, big data is about predictions.



• "Datafy" an event - capture an event in a quantified format so it can be tabulated/analyzed.



Data Warehouse - CORRECT ANSWER✅✅𝐃𝐚𝐭𝐚 𝐖𝐚𝐫𝐞𝐡𝐨𝐮𝐬𝐞:

• A home for high value data or data assets that originates in other corporate applications.



• 𝐃𝐚𝐭𝐚 𝐖𝐚𝐫𝐞𝐡𝐨𝐮𝐬𝐢𝐧𝐠:

▪ A coordinated and periodic copying of data from various sources both inside and outside the company,
into an environment optimized for analytical and informational processing.



• Stores current and historical data



• Provides analysis and reporting tools



• Relies exclusively on data obtained from other applications.



Data Management - CORRECT ANSWER✅✅𝐃𝐚𝐭𝐚 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭:

• Development, execution, and supervision of plans, policies, programs, and practices that deliver,
control, protect, and enhance the value of data and information assets throughout their lifecycles.



• Companies now recognize their data as a strategic asset where they can learn insights about
customers, products, internal processes, etc.



• 𝐃𝐚𝐭𝐚 𝐦𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭 𝐚𝐜𝐭𝐢𝐯𝐢𝐭𝐢𝐞𝐬 𝐚𝐫𝐞 𝐛𝐫𝐨𝐚𝐝:

▪ Profiling data, aligning data to regulations, extracting data, defining data.

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