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Learn Python The Hard Way VS Google BigQuery

Compare Learn Python The Hard Way VS Google BigQuery and see what are their differences

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Learn Python The Hard Way logo Learn Python The Hard Way

One of the best guides to learn Python & coding in general

Google BigQuery logo Google BigQuery

A fully managed data warehouse for large-scale data analytics.
  • Learn Python The Hard Way Landing page
    Landing page //
    2022-06-16
  • Google BigQuery Landing page
    Landing page //
    2023-10-03

Learn Python The Hard Way features and specs

  • Hands-On Practice
    The book emphasizes learning through practical exercises, helping learners to reinforce their understanding by actively writing code and solving problems.
  • Structured Learning Path
    The book offers a well-defined progression path that gradually increases in complexity, making it suitable for beginners who need a clear roadmap.
  • Focus on Basics
    It emphasizes fundamental concepts and core programming skills, ensuring a solid foundation in Python programming.
  • Immediate Feedback
    By practicing exercises and checking their code against provided solutions, learners receive immediate feedback which facilitates faster learning.

Possible disadvantages of Learn Python The Hard Way

  • Limited Depth
    The book may not cover advanced Python topics in depth, which might be a limitation for intermediate learners needing more comprehensive material.
  • Learning Style Restriction
    The 'Hard Way' approach may not suit everyone, especially learners who prefer theoretical explanations before diving into coding exercises.
  • Paid Access
    Some of the content, especially the extended and video materials, require purchase, which might be a drawback for those seeking completely free resources.
  • Rigid Problem Solving
    Some users may find the exercise solutions to be somewhat rigid, not encouraging alternative problem-solving techniques or creative code implementations.

Google BigQuery features and specs

  • Scalability
    BigQuery can effortlessly scale to handle large volumes of data due to its serverless architecture, thereby reducing the operational overhead of managing infrastructure.
  • Speed
    It leverages Google's infrastructure to provide high-speed data processing, making it possible to run complex queries on massive datasets in a matter of seconds.
  • Integrations
    BigQuery easily integrates with various Google Cloud Platform services, as well as other popular data tools like Looker, Tableau, and Power BI.
  • Automatic Optimization
    Features like automatic data partitioning and clustering help to optimize query performance without requiring manual tuning.
  • Security
    BigQuery provides robust security features including IAM roles, customer-managed encryption keys, and detailed audit logging.
  • Cost Efficiency
    The pricing model is based on the amount of data processed, which can be cost-effective for many use cases when compared to traditional data warehouses.
  • Managed Service
    Being fully managed, BigQuery takes care of database administration tasks such as scaling, backups, and patch management, allowing users to focus on their data and queries.

Possible disadvantages of Google BigQuery

  • Cost Predictability
    While the pay-per-use model can be cost-efficient, it can also make cost forecasting difficult. Unexpected large queries could lead to higher-than-anticipated costs.
  • Complexity
    The learning curve can be steep for those who are not already familiar with SQL or Google Cloud Platform, potentially requiring training and education.
  • Limited Updates
    BigQuery is optimized for read-heavy operations, and it can be less efficient for scenarios that require frequent updates or deletions of data.
  • Query Pricing
    Costs are based on the amount of data processed by each query, which may not be suitable for use cases that require frequent analysis of large datasets.
  • Data Transfer Costs
    While internal data movement within Google Cloud can be cost-effective, transferring data to or from other services or on-premises systems can incur additional costs.
  • Dependency on Google Cloud
    Organizations heavily invested in multi-cloud or hybrid-cloud strategies may find the dependency on Google Cloud limiting.
  • Cold Data Performance
    Query performance might be slower for so-called 'cold data,' or data that has not been queried recently, affecting the responsiveness for some workloads.

Analysis of Learn Python The Hard Way

Overall verdict

  • Learn Python The Hard Way is considered a good resource for beginners, especially those who prefer hands-on learning.

Why this product is good

  • This book adopts a practical approach, focusing on writing and testing code to reinforce concepts. It favors direct practice over theoretical explanation, which can be beneficial for learners who appreciate experiential learning. It also introduces debugging early on, which is a crucial skill for programming.

Recommended for

  • Absolute beginners who are new to programming.
  • Individuals who prefer learning by doing rather than just reading.
  • People looking for a structured, exercise-driven way to learn Python.

Analysis of Google BigQuery

Overall verdict

  • Google BigQuery is a powerful and flexible data warehouse solution that suits a wide range of data analytics needs. Its ability to handle large volumes of data quickly makes it a preferred choice for organizations looking to leverage their data effectively.

Why this product is good

  • Google BigQuery is a fully-managed data warehouse that simplifies the analysis of large datasets. It is known for its scalability, speed, and integration with other Google Cloud services. It supports standard SQL, has built-in machine learning capabilities, and allows for seamless data integration from various sources. The serverless architecture means that users don't need to worry about infrastructure management, and its pay-as-you-go model provides cost efficiency.

Recommended for

  • Businesses requiring fast processing of large datasets
  • Organizations that already utilize Google Cloud services
  • Companies looking for a cost-effective, scalable analytics solution
  • Teams interested in using SQL for data analysis
  • Data scientists integrating machine learning with their data workflows

Learn Python The Hard Way videos

Learn Python the Hard Way by Zed A Shaw: Review | Complete python tutorial. Learn Python coding

More videos:

  • Review - Learn Python The Hard Way - Review

Google BigQuery videos

Cloud Dataprep Tutorial - Getting Started 101

More videos:

  • Review - Advanced Data Cleanup Techniques using Cloud Dataprep (Cloud Next '19)
  • Demo - Google Cloud Dataprep Premium product demo

Category Popularity

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Online Learning
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Data Dashboard
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100% 100
Development
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Big Data
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Reviews

These are some of the external sources and on-site user reviews we've used to compare Learn Python The Hard Way and Google BigQuery

Learn Python The Hard Way Reviews

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Google BigQuery Reviews

Database for Data Analytics
Processing typeDescriptionUse casesCommon databasesProcessing typesProcesses data in scheduled intervals (hours, days). High-latency but cost-efficient for large datasets.Financial reporting, trend analysis, historical analyticsSnowflake, Amazon Redshift, Google BigQueryContinuously ingests and processes data with minimal latency for real-time decision-making.Fraud...
Source: blog.devart.com
Data Warehouse Tools
Google BigQuery: Similar to Snowflake, BigQuery offers a pay-per-use model with separate charges for storage and queries. Storage costs start around $0.01 per GB per month, while on-demand queries are billed at $5 per TB processed.
Source: peliqan.io
Top 6 Cloud Data Warehouses in 2023
You can also use BigQueryโ€™s columnar and ANSI SQL databases to analyze petabytes of data at a fast speed. Its capabilities extend enough to accommodate spatial analysis using SQL and BigQuery GIS. Also, you can quickly create and run machine learning (ML) models on semi or large-scale structured data using simple SQL and BigQuery ML. Also, enjoy a real-time interactive...
Source: geekflare.com
Top 5 Cloud Data Warehouses in 2023
Google BigQuery is an incredible platform for enterprises that want to run complex analytical queries or โ€œheavyโ€ queries that operate using a large set of data. This means itโ€™s not ideal for running queries that are doing simple filtering or aggregation. So if your cloud data warehousing needs lightning-fast performance on a big set of data, Google BigQuery might be a great...
Top 5 BigQuery Alternatives: A Challenge of Complexity
BigQuery's emergence as an attractive analytics and data warehouse platform was a significant win, helping to drive a 45% increase in Google Cloud revenue in the last quarter. The company plans to maintain this momentum by focusing on a multi-cloud future where BigQuery advances the cause of democratized analytics.
Source: blog.panoply.io

Social recommendations and mentions

Based on our record, Google BigQuery should be more popular than Learn Python The Hard Way. It has been mentiond 47 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Learn Python The Hard Way mentions (14)

  • Cloudflare Introduces Default Blocking of A.I. Data Scrapers
    These kinds of comparisons rarely lead to good discussions. Let's instead be focused and talk about real stuff. Consider https://learnpythonthehardway.org/ for example. It has influenced a generation of Python developers. Not just the main website, but the tons of Python code and Python-related content it inspired. Why would anyone write these kinds of textbooks/websites/guides if AI can replace them? Arguibly,... - Source: Hacker News / about 1 year ago
  • Should I learn Python with GPT?
    Try this instead: https://learnpythonthehardway.org/ LLMs will give you an uncertain percentage of wrong answers. Itโ€™s like having a teacher that lies to you and doesnโ€™t know when they are lying and has zero understanding of the information they give you. - Source: Hacker News / almost 2 years ago
  • How to Get Started as a New Open Source Contributor to PgAdmin4
    Basic Python Knowledge: Ensure you have a solid understanding of Python basics. Resources like Python.org and Learn Python the Hard Way are great starting points. - Source: dev.to / almost 2 years ago
  • Python Concepts for Product Manager.
    Go here: https://learnpythonthehardway.org/. Source: about 3 years ago
  • What is the best way to learn VFX Programming and Concepts for someone who is more โ€œartโ€ minded.
    Also, I havenโ€™t looked at it in a super long time but personally I got started with Python using https://learnpythonthehardway.org after originally training to be an artist and ended up having a pretty successful career in Pipeline instead. Source: about 3 years ago
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Google BigQuery mentions (47)

  • Ruby on Rails Performance: 7 Lessons from Scaling FirstPromoter
    We migrated the analytics layer to Google BigQuery. Same queries that timed out in PostgreSQL now run in under 2 seconds. But not everything belongs in BigQuery โ€” we initially moved too aggressively and actually reverted some queries back when the added complexity wasn't justified. Our rule of thumb: if a query scans hundreds of thousands of rows or involves complex time-series aggregations, BigQuery. Everything... - Source: dev.to / 3 months ago
  • How to Analyze 47 Million Hacker News Posts: A Data Scientist's Dream Dataset Just Got Better
    Google BigQuery - For large-scale data processing and SQL-based analysis. - Source: dev.to / 4 months ago
  • What if ML pipelines had a lock file?
    Data Pipelines usually read from tables that change over time. Most of these tables are stored in a data warehouse like Amazon Redshift or Google BigQuery. Rows are added or removed. Backfills happen. A column gets renamed or its meaning changes. Even when teams snapshot data, those snapshots are often implicit, not recorded as part of the pipeline run itself. - Source: dev.to / 5 months ago
  • Best SQL Courses with Certificates for 2026
    SQL endures because it's the non-negotiable interface for relational data. Enterprise data storage still relies heavily on relational databases despite new alternatives. What makes SQL valuable for learners is transferabilityโ€”while dialects differ across PostgreSQL, SQL Server, and BigQuery, the fundamentals stay consistent. - Source: dev.to / 7 months ago
  • Why Your Snowflake Bill is High and How to Fix It with a Hybrid Approach
    Within classic cloud data warehouses, Google BigQuery presents a different pricing model. Its on-demand, per-terabyte-scanned pricing can be cost-effective for sporadic forensic queries. But it carries the risk of a runaway query where a single mistake leads to a massive bill. - Source: dev.to / 8 months ago
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What are some alternatives?

When comparing Learn Python The Hard Way and Google BigQuery, you can also consider the following products

Google's Python Class - Assorted educational materials provided by Google.

Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.โ€ŽWhat is Apache Spark?

A Byte of Python - A Byte of Python is a Python programming tutorial and learning book that teaches you how to program with the Python programming language.

Looker - Looker makes it easy for analysts to create and curate custom data experiencesโ€”so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.

Think Python - Learning Resources

Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.