![Revisit consent button](../images/body-df29beacd7496220cc94.svg) We value your privacy We use cookies to enhance your browsing experience, serve personalised ads or content, and analyse our traffic. By clicking "Accept All", you consent to our use of cookies. Customise Reject All Accept All Customise Consent Preferences ![](../images/body-2159bb67f3de8ad870eb.svg) We use cookies to help you navigate efficiently and perform certain functions. You will find detailed information about all cookies under each consent category below. The cookies that are categorised as "Necessary" are stored on your browser as they are essential for enabling the basic functionalities of the site. ... Show more NecessaryAlways Active Necessary cookies are required to enable the basic features of this site, such as providing secure log-in or adjusting your consent preferences. These cookies do not store any personally identifiable data. * Cookie BCTempID * Duration 10 minutes * Description No description available. * Cookie __cf_bm * Duration 1 hour * Description This cookie, set by Cloudflare, is used to support Cloudflare Bot Management. * Cookie AWSALBCORS * Duration 7 days * Description Amazon Web Services set this cookie for load balancing. * Cookie _cfuvid * Duration session * Description Cloudflare sets this cookie to track users across sessions to optimize user experience by maintaining session consistency and providing personalized services * Cookie li_gc * Duration 6 months * Description Linkedin set this cookie for storing visitor's consent regarding using cookies for non-essential purposes. * Cookie __hssrc * Duration session * Description This cookie is set by Hubspot whenever it changes the session cookie. The __hssrc cookie set to 1 indicates that the user has restarted the browser, and if the cookie does not exist, it is assumed to be a new session. * Cookie __hssc * Duration 1 hour * Description HubSpot sets this cookie to keep track of sessions and to determine if HubSpot should increment the session number and timestamps in the __hstc cookie. * Cookie wpEmojiSettingsSupports * Duration session * Description WordPress sets this cookie when a user interacts with emojis on a WordPress site. It helps determine if the user's browser can display emojis properly. * Cookie BCSessionID * Duration 1 year 1 month 4 days * Description Blueconic sets this cookie as a unique identifier for the BlueConic profile. * Cookie _octo * Duration 1 year * Description No description available. * Cookie logged_in * Duration 1 year * Description No description available. * Cookie __Secure-YEC * Duration past * Description YouTube sets this cookie to stores the user's video player preferences using embedded YouTube video * Cookie __eoi * Duration 6 months * Description Description is currently not available. * Cookie AWSALBTGCORS * Duration 7 days * Description No description available. * Cookie login-status-p * Duration past * Description Description is currently not available. * Cookie AWSALBTG * Duration 7 days * Description No description available. * Cookie csrf_token * Duration session * Description No description available. * Cookie token_v2 * Duration 1 day * Description Description is currently not available. * Cookie D * Duration 1 year * Description Description is currently not available. * Cookie PHPSESSID * Duration session * Description This cookie is native to PHP applications. The cookie stores and identifies a user's unique session ID to manage user sessions on the website. The cookie is a session cookie and will be deleted when all the browser windows are closed. * Cookie VISITOR_PRIVACY_METADATA * Duration 6 months * Description YouTube sets this cookie to store the user's cookie consent state for the current domain. * Cookie cookietest * Duration session * Description The cookietest cookie is typically used to determine whether the user's browser accepts cookies, essential for website functionality and user experience. * Cookie __Host-airtable-session * Duration 1 year * Description This cookie is used to enable us to integrate the services of Airtable. * Cookie __Host-airtable-session.sig * Duration 1 year * Description This cookie is used to enable us to integrate the services of Airtable. * Cookie m * Duration 1 year 1 month 4 days * Description Stripe sets this cookie for fraud prevention purposes. It identifies the device used to access the website, allowing the website to be formatted accordingly. * Cookie BIGipServer* * Duration session * Description Marketo sets this cookie to collect information about the user's online activity and build a profile about their interests to provide advertisements relevant to the user. * Cookie __cfruid * Duration session * Description Cloudflare sets this cookie to identify trusted web traffic. * Cookie _GRECAPTCHA * Duration 6 months * Description Google Recaptcha service sets this cookie to identify bots to protect the website against malicious spam attacks. * Cookie __Secure-YNID * Duration 6 months * Description Google cookie used to protect user security and prevent fraud, especially during the login process. * Cookie cookieyes-consent * Duration 1 year * Description CookieYes sets this cookie to remember users' consent preferences so that their preferences are respected on subsequent visits to this site. It does not collect or store any personal information about the site visitors. Functional Functional cookies help perform certain functionalities like sharing the content of the website on social media platforms, collecting feedback, and other third-party features. * Cookie lidc * Duration 1 day * Description LinkedIn sets the lidc cookie to facilitate data center selection. * Cookie brw * Duration 1 year * Description No description available. * Cookie brwConsent * Duration 5 minutes * Description Description is currently not available. * Cookie WMF-Uniq * Duration 1 year * Description Description is currently not available. * Cookie loom_anon_comment * Duration 1 year * Description No description available. * Cookie loom_referral_video * Duration session * Description Description is currently not available. * Cookie VISITOR_INFO1_LIVE * Duration 6 months * Description A cookie set by YouTube to measure bandwidth that determines whether the user gets the new or old player interface. * Cookie yt-remote-connected-devices * Duration Never Expires * Description YouTube sets this cookie to store the user's video preferences using embedded YouTube videos. * Cookie ytidb::LAST_RESULT_ENTRY_KEY * Duration Never Expires * Description The cookie ytidb::LAST_RESULT_ENTRY_KEY is used by YouTube to store the last search result entry that was clicked by the user. This information is used to improve the user experience by providing more relevant search results in the future. * Cookie yt-remote-device-id * Duration Never Expires * Description YouTube sets this cookie to store the user's video preferences using embedded YouTube videos. * Cookie yt-remote-session-name * Duration session * Description The yt-remote-session-name cookie is used by YouTube to store the user's video player preferences using embedded YouTube video. * Cookie yt-remote-fast-check-period * Duration session * Description The yt-remote-fast-check-period cookie is used by YouTube to store the user's video player preferences for embedded YouTube videos. * Cookie yt-remote-session-app * Duration session * Description The yt-remote-session-app cookie is used by YouTube to store user preferences and information about the interface of the embedded YouTube video player. * Cookie yt-remote-cast-available * Duration session * Description The yt-remote-cast-available cookie is used to store the user's preferences regarding whether casting is available on their YouTube video player. * Cookie yt-remote-cast-installed * Duration session * Description The yt-remote-cast-installed cookie is used to store the user's video player preferences using embedded YouTube video. * Cookie cp_session * Duration 3 months * Description Codepen sets this cookie for Help systems found in the website. * Cookie loid * Duration 1 year 1 month 4 days * Description This cookie is set by the Reddit. The cookie enables the sharing of content from the website onto the social media platform. Analytics Analytical cookies are used to understand how visitors interact with the website. These cookies help provide information on metrics such as the number of visitors, bounce rate, traffic source, etc. * Cookie __hstc * Duration 6 months * Description Hubspot set this main cookie for tracking visitors. It contains the domain, initial timestamp (first visit), last timestamp (last visit), current timestamp (this visit), and session number (increments for each subsequent session). * Cookie hubspotutk * Duration 6 months * Description HubSpot sets this cookie to keep track of the visitors to the website. This cookie is passed to HubSpot on form submission and used when deduplicating contacts. * Cookie _ga * Duration 1 year 1 month 4 days * Description Google Analytics sets this cookie to calculate visitor, session and campaign data and track site usage for the site's analytics report. The cookie stores information anonymously and assigns a randomly generated number to recognise unique visitors. * Cookie _ga_* * Duration 1 year 1 month 4 days * Description Google Analytics sets this cookie to store and count page views. * Cookie __Host-psifi.analyticsTrace * Duration 6 hours * Description Description is currently not available. * Cookie __Host-psifi.analyticsTraceV2 * Duration 6 hours * Description Description is currently not available. * Cookie _gh_sess * Duration session * Description GitHub sets this cookie for temporary application and framework state between pages like what step the user is on in a multiple step form. * Cookie YSC * Duration session * Description YSC cookie is set by Youtube and is used to track the views of embedded videos on Youtube pages. * Cookie ajs_anonymous_id * Duration 1 year * Description This cookie is set by Segment to count the number of people who visit a certain site by tracking if they have visited before. * Cookie vuid * Duration 1 year 1 month 4 days * Description Vimeo installs this cookie to collect tracking information by setting a unique ID to embed videos on the website. Performance Performance cookies are used to understand and analyse the key performance indexes of the website which helps in delivering a better user experience for the visitors. * Cookie AWSALB * Duration 7 days * Description AWSALB is an application load balancer cookie set by Amazon Web Services to map the session to the target. * Cookie acq * Duration past * Description Description is currently not available. * Cookie acq.sig * Duration past * Description Description is currently not available. * Cookie ptc * Duration 2 years * Description No description available. Advertisement Advertisement cookies are used to provide visitors with customised advertisements based on the pages you visited previously and to analyse the effectiveness of the ad campaigns. * Cookie muc_ads * Duration 1 year 1 month 4 days * Description Twitter sets this cookie to collect user behaviour and interaction data to optimize the website. * Cookie guest_id_marketing * Duration 1 year 1 month 4 days * Description Twitter sets this cookie to identify and track the website visitor. * Cookie guest_id_ads * Duration 1 year 1 month 4 days * Description Twitter sets this cookie to identify and track the website visitor. * Cookie personalization_id * Duration 1 year 1 month 4 days * Description Twitter sets this cookie to integrate and share features for social media and also store information about how the user uses the website, for tracking and targeting. * Cookie guest_id * Duration 1 year 1 month 4 days * Description Twitter sets this cookie to identify and track the website visitor. It registers if a user is signed in to the Twitter platform and collects information about ad preferences. * Cookie bcookie * Duration 1 year * Description LinkedIn sets this cookie from LinkedIn share buttons and ad tags to recognize browser IDs. * Cookie __Secure-ROLLOUT_TOKEN * Duration 6 months * Description YouTube sets this cookie to manage feature rollout and experimentation. It helps Google control which new features or interface changes are shown to users as part of testing and staged rollouts, ensuring consistent experience for a given user during an experiment. * Cookie yt.innertube::nextId * Duration Never Expires * Description YouTube sets this cookie to register a unique ID to store data on what videos from YouTube the user has seen. * Cookie yt.innertube::requests * Duration Never Expires * Description YouTube sets this cookie to register a unique ID to store data on what videos from YouTube the user has seen. * Cookie session_tracker * Duration session * Description This cookie is set by the Reddit. This cookie is used to identify trusted web traffic. It also helps in adverstising on the website. * Cookie edgebucket * Duration session * Description Reddit sets this cookie to save the information about a log-on Reddit user, for the purpose of advertisement recommendations and updating the content. * Cookie did * Duration 1 year * Description Arbor sets this cookie to show targeted ads to site visitors.This cookie expires after 2 months or 1 year. Uncategorised Other uncategorised cookies are those that are being analysed and have not been classified into a category as yet. No cookies to display. Reject All Save My Preferences Accept All Toggle Search[](https://towardsdatascience.com/)Toggle Mobile Navigation [](https://towardsdatascience.com/) Publish AI, ML & data-science insights to a global community of data professionals. Sign in[Submit an Article](https://write.insightmediagroup.io) [Latest](https://towardsdatascience.com/latest/)[Editor's Picks](https://towardsdatascience.com/tag/editors-pick/)[Newsletter](https://towardsdatascience.com/tag/the-variable/)[ShipAI](https://towardsdatascience.com/shipai/) * * * [Write For TDS](https://towardsdatascience.com/submissions/) [LinkedIn](https://www.linkedin.com/company/towards-data-science/)[X](https://x.com/TDataScience)Toggle Search [Data Engineering](https://towardsdatascience.com/category/data-science/data-engineering/) # Mastering Hadoop, Part 1: Installation, Configuration, and Modern Big Data Strategies A comprehensive guide covering Hadoop setup, HDFS commands, MapReduce, debugging, advantages, challenges, and the future of big data technologies. [Niklas Lang](https://towardsdatascience.com/author/niklas_lang/) March 11, 20258 min read ![An elephant standing on brown grass against a cloudy sky](../images/000.png) Photo by Nam Anh on Unsplash Nowadays, a large amount of data is collected on the internet, which is why companies are faced with the challenge of being able to store, process, and analyze these volumes efficiently. Hadoop is an open-source framework from the Apache Software Foundation and has become one of the leading big data management technologies in recent years. The system enables the distributed storage and processing of data across multiple servers. As a result, it offers a scalable solution for a wide range of applications from data analysis to machine learning. This article provides a comprehensive overview of Hadoop and its components. We also examine the underlying architecture and provide practical tips for getting started with it. Before we can start with it, we need to mention that the whole topic of Hadoop is huge and even though this article is already long, it is not even close to going into too much detail on all topics. This is why we split it into three parts: To let you decide for yourself how deep you want to dive into it: **Part 1: Hadoop 101: What it is, why it matters, and who should care** This part is for everyone interested in Big Data and Data Science that wants to get to know this classic tool and also understand the downsides of it. **Part 2: Getting Hands-On: Setting up and scaling Hadoop** All readers that weren’t scared off by the disadvantages of Hadoop and the size of the ecosystem, can use this part to get a guideline on how they can start with their first local cluster to learn the basics on how to operate it. **Part 3: Hadoop ecosystem: Get the most out of your cluster** In this section, we go under the hood and explain the core components and how they can be further advanced to meet your requirements. Learn this step by step with the interactive [Data Engineer](https://roadmap.sh/data-engineer) roadmap. ## Part 1: Hadoop 101: What it is, why it matters, and who should care Hadoop is an open-source framework for the distributed storage and processing of large amounts of data. It was originally developed by Doug Cutting and Mike Cafarella and started as a search engine optimization project under the name Nutch. It was only later renamed Hadoop by its founder Cutting, based on the name of his son's toy elephant. This is where the yellow elephant in today's logo comes from. The original concept was based on two Google papers on distributed file systems and the [MapReduce](https://databasecamp.de/en/data/mapreduce-algorithm) mechanism and initially comprised around 11,000 lines of code. Other methods, such as the YARN resource manager, were only added in 2012. Today, the ecosystem comprises a large number of components that go far beyond pure file storage. Hadoop differs fundamentally from traditional relational databases (RDBMS): | **Attribute** | **Hadoop** | **RDBMS** | | --- | --- | --- | | Data Structure | Unstructured, semi-structured, and unstructured data | Structured Data | | Processing | Batch processing or partial real-time processing | Transaction-based with SQL | | Scalability | Horizontal scaling across multiple servers | Vertical scaling through stronger servers | | Flexibility | Supports many data formats | Strict schemes must be adhered to | | Costs | Open source with affordable hardware | Mostly open source, but with powerful, expensive servers | ## Which applications use Hadoop? Hadoop is an important big data framework that has established itself in many companies and applications in recent years. In general, it can be used primarily for the storage of large and unstructured data volumes and, thanks to its distributed architecture, is particularly suitable for data-intensive applications that would not be manageable with traditional databases. Typical use cases for Hadoop include: * **Big data analysis** : Hadoop enables companies to centrally collect and store large amounts of data from different systems. This data can then be processed for further analysis and made available to users in reports. Both structured data, such as financial transactions or sensor data, and unstructured data, such as social media comments or website usage data, can be stored in Hadoop. * **Log analysis & IT monitoring**: In modern IT infrastructure, a wide variety of systems generate data in the form of logs that provide information about the status or log certain events. This information needs to be stored and reacted to in real-time, for example, to prevent failures if the memory is full or the program is not working as expected. Hadoop can take on the task of data storage by distributing the data across several nodes and processing it in parallel, while also analyzing the information in batches. * **Machine learning & AI**: Hadoop provides the basis for many machine learning and AI models by managing the data sets for large models. In text or image processing in particular, the model architectures require a lot of training data that takes up large amounts of memory. With the help of Hadoop, this storage can be managed and operated efficiently so that the focus can be on the architecture and training of the AI algorithms. * **ETL processes** : ETL processes are essential in companies to prepare the data so that it can be processed further or used for analysis. To do this, it must be collected from a wide variety of systems, then transformed and finally stored in a data lake or data warehouse. Hadoop can provide central support here by offering a good connection to different data sources and allowing data processing to be parallelized across multiple servers. In addition, cost efficiency can be increased, especially in comparison to classic ETL approaches with data warehouses. The list of well-known companies that use Hadoop daily and have made it an integral part of their architecture is very long. Facebook, for example, uses Hadoop to process several petabytes of user data every day for advertisements, feed optimization, and machine learning. Twitter, on the other hand, uses Hadoop for real-time trend analysis or to detect spam, which should be flagged accordingly. Finally, Yahoo has one of the world’s largest Hadoop installations with over 40,000 nodes, which was set up to analyze search and advertising data. ## What are the advantages and disadvantages of Hadoop? Hadoop has become a powerful and popular big data framework used by many companies, especially in the 2010s, due to its ability to process large amounts of data in a distributed manner. In general, the following advantages arise when using Hadoop: * **Scalability** : The cluster can easily be scaled horizontally by adding new nodes that take on additional tasks for a job. This also makes it possible to process data volumes that exceed the capacity of a single computer. * **Cost efficiency** : This horizontal scalability also makes Hadoop very cost-efficient, as more low-cost computers can be added for better performance instead of equipping a server with expensive hardware and scaling vertically. In addition, Hadoop is open-source software and can therefore be used free of charge. * **Flexibility** : Hadoop can process both unstructured data and structured data, offering the flexibility to be used for a wide variety of applications. It offers additional flexibility by providing a large library of components that further extend the existing functionalities. * **Fault tolerance** : By replicating the data across different servers, the system can still function in the event of most hardware failures, as it simply falls back on another replication. This also results in high availability of the entire system. These disadvantages should also be taken into account. * **Complexity** : Due to the strong networking of the cluster and the individual servers in it, the administration of the system is rather complex, and a certain amount of training is required to set up and operate a Hadoop cluster correctly. However, this point can be avoided by using a cloud connection and the automatic scaling it contains. * **Latency** : Hadoop uses batch processing to handle the data and thus establishes latency times, as the data is not processed in real-time, but only when enough data is available for a batch. Hadoop tries to avoid this with the help of mini-batches, but this still means latency. * **Data management** : Additional components are required for data management, such as data quality control or tracking the data sequence. Hadoop does not include any direct tools for data management. Hadoop is a powerful tool for processing big data. Above all, scalability, cost efficiency, and flexibility are decisive advantages that have contributed to the widespread use of Hadoop. However, there are also some disadvantages, such as the latency caused by batch processing. ## Does Hadoop have a future? Hadoop has long been the leading technology for distributed big data processing, but new systems have also emerged and become increasingly relevant in recent years. One of the biggest trends is that most companies are turning to fully managed cloud data platforms that can run Hadoop-like workloads without the need for a dedicated cluster. This also makes them more cost-efficient, as only the hardware that is needed has to be paid for. In addition, Apache Spark in particular has established itself as a faster alternative to MapReduce and is therefore outperforming the classic Hadoop setup. It is also interesting because it offers an almost complete solution for AI workloads thanks to its various functionalities, such as Apache Streaming or the machine learning library. Although Hadoop remains a relevant big data framework, it is slowly losing importance these days. Even though many established companies continue to rely on the clusters that were set up some time ago, companies that are now starting with big data are using cloud solutions or specialized analysis software directly. Accordingly, the Hadoop platform is also evolving and offers new solutions that adapt to this zeitgeist. ## Who should still learn Hadoop? With the rise of cloud-native data platforms and modern distributed computing frameworks, you might be wondering: Is Hadoop still worth learning? The answer depends on your role, industry, and the scale of data you work with. While Hadoop is no longer the _default_ choice for big data processing, it remains highly relevant in many enterprise environments. Hadoop could be still relevant for you if at least one of the following is true for you: * Your company still has a Hadoop-based data lake. * The data you are storing is confidential and needs to be hosted on-premises. * You work with ETL processes, and data ingestion at scale. * Your goal is to optimize batch-processing jobs in a distributed environment. * You need to work with tools like Hive, HBase, or Apache Spark on Hadoop. * You want to optimize cost-efficient data storage and processing solutions. Hadoop is definitely not necessary for every data professional. If you're working primarily with cloud-native analytics tools, serverless architectures, or lightweight data-wrangling tasks, spending time on Hadoop may not be the best investment. You can skip Hadoop if: * Your work is focused on SQL-based analytics with cloud-native solutions (e.g., BigQuery, Snowflake, Redshift). * You primarily handle small to mid-sized datasets in Python or Pandas. * Your company has already migrated away from Hadoop to fully cloud-based architectures. Hadoop is no longer the cutting edge technology that it once was, but it still has importance in different applications and companies with existing data lakes, large-scale ETL processes, or on-premises infrastructure. [In the following part](https://towardsdatascience.com/mastering-hadoop-part-2-getting-hands-on-setting-up-and-scaling-hadoop/), we will finally be more practical and show how an easy cluster can be set up to build your big data framework with Hadoop. ## Register Now to Continue Reading ### Unlock Towards Data Science with a Free Account All articles on Towards Data Science are available to registered users. Create a free account today to access this article and thousands more. Register for freeSign in to your account * * * ![](../images/body-d123f8ba604c7f334425.jpeg) Written By ## [Niklas Lang](https://towardsdatascience.com/author/niklas_lang/) [See all from Niklas Lang](https://towardsdatascience.com/author/niklas_lang/) [Big Data](https://towardsdatascience.com/tag/big-data/)[Data Processing](https://towardsdatascience.com/tag/data-processing/)[Data Science](https://towardsdatascience.com/tag/data-science/)[Getting Started](https://towardsdatascience.com/tag/getting-started/)[Hadoop](https://towardsdatascience.com/tag/hadoop/) Share This Article * [](https://www.facebook.com/sharer/sharer.php?u=https%3A%2F%2Ftowardsdatascience.com%2Fmastering-hadoop-part-1-installation-configuration-and-modern-big-data-strategies%2F&title=Mastering%20Hadoop%2C%20Part%201%3A%20Installation%2C%20Configuration%2C%20and%20Modern%20Big%20Data%20Strategies) * [](https://www.linkedin.com/shareArticle?mini=true&url=https%3A%2F%2Ftowardsdatascience.com%2Fmastering-hadoop-part-1-installation-configuration-and-modern-big-data-strategies%2F&title=Mastering%20Hadoop%2C%20Part%201%3A%20Installation%2C%20Configuration%2C%20and%20Modern%20Big%20Data%20Strategies) * [](https://x.com/share?url=https%3A%2F%2Ftowardsdatascience.com%2Fmastering-hadoop-part-1-installation-configuration-and-modern-big-data-strategies%2F&text=Mastering%20Hadoop%2C%20Part%201%3A%20Installation%2C%20Configuration%2C%20and%20Modern%20Big%20Data%20Strategies) Towards Data Science is a community publication. Submit your insights to reach our global audience and earn through the TDS Author Payment Program. [Write for TDS](https://towardsdatascience.com/submissions/) ## Related Articles * [![](../images/body-63beb50f664a055ed739.jpg)](https://towardsdatascience.com/latest-picks-handling-data-scarcity-while-building-machine-learning-applications-254884c2c5b8/) ## [Latest picks: Handling Data Scarcity While Building Machine Learning Applications](https://towardsdatascience.com/latest-picks-handling-data-scarcity-while-building-machine-learning-applications-254884c2c5b8/) [Machine Learning](https://towardsdatascience.com/category/artificial-intelligence/machine-learning/) Your daily dose of data science [TDS Editors](https://towardsdatascience.com/author/towardsdatascience/) February 23, 20211 min read * [![](../images/002.jpg)](https://towardsdatascience.com/the-key-to-smarter-models-tracking-feature-histories-a9e3baadd52a/) ## [The Key to Smarter Models: Tracking Feature Histories](https://towardsdatascience.com/the-key-to-smarter-models-tracking-feature-histories-a9e3baadd52a/) [Artificial Intelligence](https://towardsdatascience.com/category/artificial-intelligence/) Capture context and improve predictions with historical data [Harrison Hoffman](https://towardsdatascience.com/author/harrisonfhoffman/) December 31, 20248 min read * [![](../images/003.png)](https://towardsdatascience.com/a-data-scientists-guide-to-fetching-covid-19-data-in-2022-d952b4697/) ## [A Data Scientist's Guide to Fetching COVID-19 Data in 2022](https://towardsdatascience.com/a-data-scientists-guide-to-fetching-covid-19-data-in-2022-d952b4697/) [Data Engineering](https://towardsdatascience.com/category/data-science/data-engineering/) Sometimes the best way to get something done is to do it yourself. [Bennett Meares](https://towardsdatascience.com/author/bmeares/) December 24, 20215 min read * [![](../images/004.jpg)](https://towardsdatascience.com/the-forgotten-guiding-role-of-data-modelling-a76f69364284/) ## [The Forgotten Guiding Role of Data Modelling](https://towardsdatascience.com/the-forgotten-guiding-role-of-data-modelling-a76f69364284/) [Data Engineering](https://towardsdatascience.com/category/data-science/data-engineering/) Getting to the bottom of what structuring your data responsibly really means [Dylan Anderson](https://towardsdatascience.com/author/dylansjanderson/) August 21, 202410 min read * [![](../images/005.jpg)](https://towardsdatascience.com/unlocking-data-modeling-success-3-must-have-contextual-tables-7b9ae9d4ad84/) ## [Unlocking Data Modeling Success: 3 Must-Have Contextual Tables](https://towardsdatascience.com/unlocking-data-modeling-success-3-must-have-contextual-tables-7b9ae9d4ad84/) [Data Engineering](https://towardsdatascience.com/category/data-science/data-engineering/) And how to ingest valuable data for free [Matthew Gazzano](https://towardsdatascience.com/author/mattgazzano/) July 6, 20236 min read * [![](../images/006.jpg)](https://towardsdatascience.com/improve-random-forest-with-linear-models-1fa789691e18/) ## [Improve Random Forest with Linear Models](https://towardsdatascience.com/improve-random-forest-with-linear-models-1fa789691e18/) [Artificial Intelligence](https://towardsdatascience.com/category/artificial-intelligence/) How can Random Forest survive to Feature Drifts [Marco Cerliani](https://towardsdatascience.com/author/cerlymarco/) November 30, 20215 min read * [![](../images/007.jpeg)](https://towardsdatascience.com/top-3-pandas-functions-you-didnt-know-existed-9789863cde25/) ## [Top 3 Pandas Functions You Didn't Know Existed](https://towardsdatascience.com/top-3-pandas-functions-you-didnt-know-existed-9789863cde25/) [Artificial Intelligence](https://towardsdatascience.com/category/artificial-intelligence/) You won't stumble on these by accident - guaranteed! [Dario Radečić](https://towardsdatascience.com/author/radecicdario/) August 16, 20214 min read * [![](../images/008.jpeg)](https://towardsdatascience.com/things-i-wish-i-knew-when-i-was-building-a-data-team-efcb43591204/) ## [Things I Wish I Knew When I Was Building a Data Team](https://towardsdatascience.com/things-i-wish-i-knew-when-i-was-building-a-data-team-efcb43591204/) [Data Engineering](https://towardsdatascience.com/category/data-science/data-engineering/) How to set the right foundation for a successful data practice depending on your company's stage of Data Maturity [Salma Bakouk](https://towardsdatascience.com/author/salmabakouk/) May 30, 202210 min read * [![](../images/009.jpeg)](https://towardsdatascience.com/google-sheet-permissions-python-fee1ff80363/) ## [How To Change Google Sheet Permissions with Python](https://towardsdatascience.com/google-sheet-permissions-python-fee1ff80363/) [Programming](https://towardsdatascience.com/category/programming/) Programmatically sharing Google Sheets with specific users using the Python API [Giorgos Myrianthous](https://towardsdatascience.com/author/gmyrianthous/) May 4, 20235 min read * [YouTube](https://www.youtube.com/c/TowardsDataScience) * [X](https://x.com/TDataScience) * [LinkedIn](https://www.linkedin.com/company/towards-data-science/) * [Threads](https://www.threads.net/@towardsdatascience) * [Bluesky](https://bsky.app/profile/towardsdatascience.com) [](https://towardsdatascience.com/) Your home for data science and AI. The world's leading publication for data science, data analytics, data engineering, machine learning, and artificial intelligence professionals. Subscribe to Our Newsletter[Write For TDS](https://towardsdatascience.com/submissions/)•[About](https://towardsdatascience.com/about-towards-data-science-d691af11cc2f/)•[Advertise](https://contact.towardsdatascience.com/advertise-with-towards-data-science)•[Privacy Policy](https://towardsdatascience.com/privacy-policy/)•[Terms of Use](https://towardsdatascience.com/website-terms-of-use/) © Insight Media Group, LLC 2026•[The New Stack](https://thenewstack.io)•[roadmap.sh](https://roadmap.sh)•[Creator Network](https://insightmediagroup.io/creator-network) #### Recommended Articles Close * [ ![](https://h030.towardsdatascience.com/rest/v2/contentStores/d7d3a4ab-7caf-4383-bbd2-fbf7fb4f1787/items/607686/image?etag=1782161464448&width=500&height=500) How Relevance Models Foreshadowed Transformers for NLP ](https://towardsdatascience.com/how-relevance-models-foreshadowed-transformers-for-nlp/ "How Relevance Models Foreshadowed Transformers for NLP") * [ ![](https://h030.towardsdatascience.com/rest/v2/contentStores/d7d3a4ab-7caf-4383-bbd2-fbf7fb4f1787/items/607639/image?etag=1781250125848&width=500&height=500) Javascript Fatigue: HTMX Is All You Need to Build ChatGPT — Part 1 ](https://towardsdatascience.com/javascript-fatigue-you-dont-need-js-to-build-chatgpt/ "Javascript Fatigue: HTMX Is All You Need to Build ChatGPT — Part 1") * [ ![](https://h030.towardsdatascience.com/rest/v2/contentStores/d7d3a4ab-7caf-4383-bbd2-fbf7fb4f1787/items/607930/image?etag=1782124566054&width=500&height=500) The Subset Sum Problem Solved in Linear Time for Dense Enough Inputs ](https://towardsdatascience.com/subset-sum-problem-solved-in-linear-time-for-dense-enough-inputs/ "The Subset Sum Problem Solved in Linear Time for Dense Enough Inputs") * [ ![](https://h030.towardsdatascience.com/rest/v2/contentStores/d7d3a4ab-7caf-4383-bbd2-fbf7fb4f1787/items/3660/image?etag=1780176246070&width=500&height=500) Does Your Company Have a Data Strategy? ](https://towardsdatascience.com/does-your-company-have-a-data-strategy-e8944dbec4ae/ "Does Your Company Have a Data Strategy?")