Data Engineering and Analysis - Topics 1 & 2
30 Questions
0 Views

Choose a study mode

Play Quiz
Study Flashcards
Spaced Repetition
Chat to Lesson

Podcast

Play an AI-generated podcast conversation about this lesson

Questions and Answers

Which characteristic of data refers to how closely data represents the true value or state of what it aims to depict?

  • Completeness
  • Reliability
  • Accuracy (correct)
  • Validity

Which characteristic emphasizes the extent to which data is applicable to a particular situation or context?

  • Accuracy
  • Reliability
  • Relevance (correct)
  • Timeliness

Which characteristic of data assesses whether the same data can be obtained consistently over time?

  • Validity
  • Reliability (correct)
  • Completeness
  • Timeliness

What characteristic describes the degree to which data is available when it is needed?

<p>Timeliness (D)</p> Signup and view all the answers

Which characteristic evaluates whether the data is free from errors and adheres to the expected format?

<p>Validity (C)</p> Signup and view all the answers

What is a primary benefit of using software engineering methods in software production?

<p>It reduces the cost of software production. (D)</p> Signup and view all the answers

How does the cost of software that does not utilize software engineering methods compare?

<p>It is typically higher than the cost of engineered software. (B)</p> Signup and view all the answers

Which statement best reflects the relationship between software engineering methods and production costs?

<p>Software engineering methods lead to lower production costs over time. (A)</p> Signup and view all the answers

What could be a consequence of not using software engineering methods in production?

<p>Decreased reliability of the software. (B)</p> Signup and view all the answers

In terms of cost comparison, how do software engineering methods affect production?

<p>They lower the cost of production compared to non-engineered software. (C)</p> Signup and view all the answers

What type of information is stored in individual columns of the database?

<p>Customer's name, shipping information, and phone number (C)</p> Signup and view all the answers

What does the system generate for each row in the database?

<p>A unique key (A)</p> Signup and view all the answers

Which of the following is NOT a piece of information typically included in the database?

<p>Customer's email address (B)</p> Signup and view all the answers

Why is a unique key assigned to each row in the database?

<p>To ensure proper indexing and retrieval (A)</p> Signup and view all the answers

Which of the following best describes the database's structure?

<p>Relational data organized in tables (D)</p> Signup and view all the answers

What describes batch processing in data engineering?

<p>Data is processed in batches on a set schedule. (B)</p> Signup and view all the answers

Which of the following is NOT a characteristic of batch processing?

<p>Immediate response to data input (D)</p> Signup and view all the answers

Why is batch processing important in data engineering?

<p>It enables efficient processing of large volumes of data at scheduled times. (A)</p> Signup and view all the answers

Which scenario would most likely benefit from batch processing?

<p>Generating weekly sales reports from a month's worth of data. (C)</p> Signup and view all the answers

What advantage does batch processing provide over real-time processing?

<p>Lower costs due to reduced processing resources. (A)</p> Signup and view all the answers

What primary advantage does the loose infrastructure provide?

<p>It allows for application in various tasks. (B)</p> Signup and view all the answers

Which task is NOT associated with the use of the loose infrastructure?

<p>Project management (C)</p> Signup and view all the answers

How does the loose infrastructure impact the application of tasks?

<p>It promotes flexibility in task application. (A)</p> Signup and view all the answers

Which of the following is an example of a task that can be performed using the repository under a loose infrastructure?

<p>Predictive modeling (D)</p> Signup and view all the answers

What kind of analytics can the loose infrastructure facilitate?

<p>Descriptive and diagnostic analytics (B)</p> Signup and view all the answers

What does the acronym ETL stand for in the context of data processing?

<p>Extract, Transform, Load (D)</p> Signup and view all the answers

Which of the following tools is commonly used for debugging in data processing systems?

<p>Hadoop (D)</p> Signup and view all the answers

Which process involves finding and fixing errors in data processing systems?

<p>Debugging (B)</p> Signup and view all the answers

What is one of the primary functions of ETL tools?

<p>To fetch and reorganize data (C)</p> Signup and view all the answers

Which of the following is NOT a task typically performed in the ETL process?

<p>Data visualization (D)</p> Signup and view all the answers

Flashcards

Software production cost

The cost of creating software.

Software engineering methods

Systematic approaches to software development.

Software cost comparison

Comparing the cost of software built using and without software engineering methods.

Software engineering method cost efficiency

Software engineering methods lead to lower software production costs.

Signup and view all the flashcards

Software engineering method benefit

Software engineering methods are beneficial for cost control in software development.

Signup and view all the flashcards

Batch Processing

A data processing technique where data is processed in groups at set intervals.

Signup and view all the flashcards

Data Processing Techniques

Methods used to manipulate and organize data for analysis.

Signup and view all the flashcards

Data Engineering

The practice of building and maintaining systems for storing and processing data.

Signup and view all the flashcards

Data

Facts, figures, or other types of information.

Signup and view all the flashcards

Scheduled Interval

A predefined time period for processing data in batch processing

Signup and view all the flashcards

Data Accuracy

The degree to which data reflects reality, free from errors or mistakes.

Signup and view all the flashcards

Data Validity

The degree to which data conforms to predefined rules or standards.

Signup and view all the flashcards

Data Reliability

The consistency and trustworthiness of data, ensuring it produces similar results when retrieved multiple times.

Signup and view all the flashcards

Data Timeliness

The degree to which data is up-to-date and relevant to the current context.

Signup and view all the flashcards

Data Completeness

The extent to which data is complete and contains all necessary information.

Signup and view all the flashcards

Debugging Data Processing

Finding and fixing errors in systems that handle data. This might involve checking code, data quality, or system setup.

Signup and view all the flashcards

Hadoop

A framework for processing massive amounts of data using a distributed computing approach.

Signup and view all the flashcards

Spark

A framework similar to Hadoop, but designed for faster processing of large datasets, especially for real-time analysis.

Signup and view all the flashcards

Data Processing Systems

Systems that handle the manipulation and organization of data for analysis and other purposes.

Signup and view all the flashcards

Customer Database

A collection of information about customers, typically stored in rows and columns, with each row representing a unique customer and columns containing attributes like name, shipping address, and phone number.

Signup and view all the flashcards

Unique Key

A unique identifier assigned to each customer record in a database, ensuring that every customer is distinguishable from others.

Signup and view all the flashcards

Columns in a Database

Vertical categories within a database that hold specific information about each customer record, such as name, shipping information, and phone number.

Signup and view all the flashcards

Rows in a Database

Horizontal entries in a database, representing a unique customer record with all their associated information.

Signup and view all the flashcards

What is a Customer Database Used For?

Customer databases are essential for managing customer interactions, providing personalized services, and tracking purchase history. Businesses utilize customer databases to improve customer satisfaction and drive sales.

Signup and view all the flashcards

Loose Infrastructure

A flexible and adaptable system that allows various tasks, like machine learning, reporting, and analysis, to be performed with ease.

Signup and view all the flashcards

Machine Learning

A type of artificial intelligence that allows computers to learn from data without being explicitly programmed.

Signup and view all the flashcards

Reporting

Presenting processed data in a structured and organized way, often in the form of charts, graphs or tables.

Signup and view all the flashcards

Visualization

Representing data visually using graphs, charts, and other visual elements to make it easier to understand and interpret.

Signup and view all the flashcards

Analytics

The process of examining data to uncover insights, trends, and patterns that can be used to improve decision-making.

Signup and view all the flashcards

Study Notes

Data Engineering and Analysis - Topic 1

  • Data engineering involves designing, building, and maintaining systems for collecting, storing, and processing data.
  • Data engineers are crucial for data science to ensure efficient, reliable, and scalable data collection and processing.
  • Data engineers build programs to generate and process data meaningfully for analysis.
  • Data engineers are responsible for data collection from diverse sources (social media, databases, IoT devices).
  • Data storage in data warehouses or data lakes for large volumes of data.
  • Processing of data includes cleaning, aggregating, and transforming data for analysis.
  • Data integration from diverse sources creates a comprehensive view
  • Managing data quality, reliability, and adherence to standards relevant to the data.
  • Data provisioning to end users and applications.

Data Engineering and Analysis - Topic 2

  • Data is defined as individual facts, measurements, observations, or descriptions of things.
  • Quantitative data (numerical): prices, weights
  • Qualitative data (descriptive): names, colors.
  • Key characteristics of data: accuracy, validity, reliability, timeliness, relevance, completeness.

Topic 2 (continued): Data Lifecycle Management

  • Data lifecycle refers to stages: creation, usage, maintenance to disposal.
  • Data creation: acquiring, capturing and inputting data.
  • Data storage: storing data in a warehouse for analysis and decisions.
  • Data usage: utilizing data and analytics results to guide action.
  • Data archival: storing data for long-term retention and compliance purposes.
  • Data destruction: deleting unused or redundant data to manage costs.

Topic 2 (continued): Data Sources

  • Data repositories store, collect, and manage data.
  • Relational databases: store data in tables, with relationships between data.
  • Data warehouses: store data from various sources.
  • Data marts: focus on specific departments.
  • Data lakes: flexible, store various data formats and scale easily.
  • Operational data stores: central repositories for timely operational reports.
  • Data cubes: multi-dimensional data structures.
  • Metadata repositories: store information about the data itself.

Topic 2 (continued): Types of digital data

  • Structured data: organised, fixed format, stored in relational databases (e.g. employee table).
  • Unstructured data: irregular & ambiguous (e.g. pictures, videos, social media).
  • Semi-structured data: somewhere between structured and unstructured (e.g., XML, JSON).

Topic 2 (continued): Data Repositories - Languages

  • Query languages (e.g., SQL): for accessing and manipulating data in relational databases.
  • Programming languages (e.g., Python, R, Java): for developing applications.
  • Shell scripting (e.g., Unix, Linux): for automating tasks.

Topic 2 (continued): Tips for using Data Repositories

  • Use ETL tools to maintain data quality during transfer.
  • Define access rights and restrictions for sensitive data.
  • Data repositories should be flexible to adapt to changing needs.
  • Initially, implement repositories with limited scope to test efficiency, then incrementally increase complexity.
  • Automate functions for higher efficiency.

Studying That Suits You

Use AI to generate personalized quizzes and flashcards to suit your learning preferences.

Quiz Team

Related Documents

Data Engineering and Analysis PDF

Description

Explore the fundamentals of data engineering and analysis in this quiz covering key aspects like data collection, processing, and storage. Understand the pivotal role data engineers play in data science and the integration of diverse data sources. Topics include data quality, management, and the significance of data warehouses and lakes.

More Like This

Use Quizgecko on...
Browser
Open
Browser
Browser