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Data Engineering (139)
- How to Build and Publish a Docker Image to Docker Hub - Sep 25, 2025.
Build once, run anywhere — deploy your app with Docker and Docker Hub. - Shortcuts for the Long Run: Automated Workflows for Aspiring Data Engineers - Aug 22, 2025.
Tired of repeating the same data tasks? Automate them. This article shows beginners how to build efficient, low-maintenance data engineering workflows that pay off in the long run. - Setting Up a Machine Learning Pipeline on Google Cloud Platform - Jul 25, 2025.
Learn the steps for setting up the machine learning pipeline in the top cloud provider. - Implementing Machine Learning Pipelines with Apache Spark - Jun 3, 2025.
Machine learning pipelines help turn data into predictions. Apache Spark makes it easy to build these pipelines for big data. - 7 Essential Ready-To-Use Data Engineering Docker Containers - Apr 25, 2025.
Ready to level up your data engineering game without wasting hours on setup? From ingestion to orchestration, these Docker containers handle it all. - 10 GitHub Repositories to Master Cloud Computing - Apr 2, 2025.
Learn cloud computing concepts, tools, and best practices through free, community-driven content on GitHub. - Creating a Data Science Pipeline for Real-Time Analytics Using Apache Kafka and Spark - Apr 1, 2025.
This article explains how to create a system that processes data in real time using Apache Kafka and Spark. - How to Secure Docker Containers with Best Practices - Mar 14, 2025.
Learn how to protect your Docker containers from vulnerabilities and security threats by following these best practices. - A Practical Guide to Modern Airflow - Mar 12, 2025.
Most data professionals and top companies, such as Airbnb and Netflix, use Apache Airflow daily. That is why you will learn how to install and use Apache Airflow in this article. - 5 Free Data Engineering Courses - Mar 3, 2025.
You want to learn data engineering, but don’t know where to start? Here are the suggestions of five free online courses, with some additional resources for skill practicing. - 10 Essential Docker Commands for Data Engineering - Feb 25, 2025.
Tired of 'it works on my machine' problems? Learn the top 10 Docker commands every data engineer needs to build, deploy, and scale projects like a pro! - How to Monitor Docker Containers - Jan 10, 2025.
This guide highlights the importance of container monitoring, key metrics to track, and tools ranging from Docker's built-in commands to comprehensive systems like Prometheus and Grafana. - Implementing Data Quality Assurance in Data Science Pipelines with Great Expectations - Jan 8, 2025.
This article shows how to use Great Expectations to check data quality in data science projects. - Getting Started with the Data Engineer Handbook - Jan 6, 2025.
Kickstart your data engineering career with an expert guide available on GitHub. - How to Use Docker for Local Development Environments - Dec 19, 2024.
Learn how to create containers and manage complex setups with Docker Compose to simplify your development workflow. - How to Perform Advanced SQL Queries in BigQuery - Dec 13, 2024.
Improve your SQL querying skills in BigQuery with these advanced querying templates. - 7 Projects to Master Data Engineering - Dec 4, 2024.
Learn to build, run, and manage data engineering pipelines both locally and in the cloud using popular tools. - Developing Robust ETL Pipelines for Data Science Projects - Nov 15, 2024.
In this article, we’ll look at how to build ETL pipelines for data science projects. - Beginner’s Guide to FastAPI - Oct 14, 2024.
FastApi is a contemporary web framework designed for creating RESTful APIs with Python 3.8 or later. - 7 Data Engineering Tools for Beginners - Oct 3, 2024.
Learn the data engineering tools for data orchestration, database management, batch processing, ETL (Extract, Transform, Load), data transformation, data visualization, and data streaming. - How to Write Basic SQL Queries in BigQuery - Sep 25, 2024.
Take the first steps in writing effective SQL queries to retrieve data in BigQuery - How to Import Data into BigQuery - Sep 20, 2024.
Master the process of loading datasets into BigQuery from four different data sources - How to Set Up Your First BigQuery Project - Sep 17, 2024.
Discover BigQuery: Google's structured data warehouse in the cloud, and take your first learning steps with this enthralling technology. - A Beginner’s Guide to ClickHouse Database - Sep 13, 2024.
Learn how to install ClickHouse DBMS, create a database, and run SQL queries using native and Python clients. - Project Ideas to Master Data Engineering - Aug 30, 2024.
Data engineering is best learned by doing projects. But which ones? Here are six projects focusing on different data engineering skills to ensure you have it all covered. - Building Data Pipeline with Prefect - Aug 28, 2024.
Learn how to build and deploy an end-to-end data pipeline using Prefect with a few lines of code. - How To Use Docker Volumes for Persistent Data Storage - Aug 23, 2024.
Learn how to use Docker volumes to ensure data persistence when working with Docker. - Landing a Data Engineer Role: Free Courses and Certifications - Jul 15, 2024.
Is it possible to learn data engineering for free? I claim it is and present the evidence for that in the form of 10 free data engineering courses. - How To Debug Running Docker Containers - Jul 12, 2024.
Debugging Docker containers is an essential skill when working with containerized applications. Let’s explore the different ways to debug Docker containers. - How To Use Docker Tags to Manage Image Versions Effectively - Jul 8, 2024.
Learn to use Docker tags for managing and versioning docker images, making it easier to handle different application versions. - How To Optimize Dockerfile Instructions for Faster Build Times - Jul 2, 2024.
Optimize Dockerfiles for faster builds by using build cache, minimizing build context, and following best practices. - How To Leverage Docker Cache for Optimizing Build Speeds - Jul 1, 2024.
Want to make your Docker builds much faster? Learn how to do so by leveraging Docker's layer caching mechanism. - How To Create Minimal Docker Images for Python Applications - Jun 25, 2024.
This tutorial will teach you how to create minimal Docker images for Python applications. - 10 GitHub Repositories to Master Data Engineering - May 21, 2024.
Learn data engineering through free courses, tutorials, books, tools, guides, roadmaps, practice exercises, projects, and other resources. - 7 Steps to Mastering Data Engineering - Apr 12, 2024.
The only data engineering roadmap you need for an introduction to concepts, tools, and techniques to collect, store, transform, analyze, and model data. - What is a Database? Everything You Need to Know - Mar 26, 2024.
Unlocking Database Basics. - 5 Airflow Alternatives for Data Orchestration - Feb 22, 2024.
Top list of open-source tools for building and managing workflows. - What Is Data Lineage, And Why Does It Matter? - Feb 14, 2024.
If you’ve ever had conversations with data professionals, you’ve probably heard “data lineage” pop up quite a few times. So what is data lineage all about, and why is it important? - Free Data Engineering Course for Beginners - Feb 12, 2024.
Interested in data engineering but don't know where to start? Get up to speed in data engineering fundamentals with this free course. - A Data Lake, You Call It? It’s a Data Swamp - Feb 5, 2024.
How and why the data lake architecture often fails to meet its promises. And how better governance helps mitigate such challenges. - The Only Free Course You Need To Become a Professional Data Engineer - Jan 26, 2024.
Data Engineering ZoomCamp offers free access to reading materials, video tutorials, assignments, homeworks, projects, and workshops. - Turn Your Laptop Into a Personal Analytics Engine with DuckDB and MotherDuck - Jan 16, 2024.
Bring the powerful tools to your laptop. - Evolution in ETL: How Skipping Transformation Enhances Data Management - Dec 12, 2023.
This article provides an overview of two new data preparation techniques that enable data democratization while minimizing transformation burdens. - Back to Basics Bonus Week: Deploying to the Cloud - Dec 11, 2023.
Welcome back to the KDnuggets’ "Back to Basics" series. This is the BONUS week and we will dive into learning about deploying to the cloud. - 5 Free Courses to Master Data Engineering - Nov 30, 2023.
Data engineers must prepare and manage the infrastructure and tools necessary for the whole data workflow in a data-driven company. - How Big Data Is Saving Lives in Real Time: IoV Data Analytics Helps Prevent Accidents - Nov 28, 2023.
This posts talks about what needs to be taken care of in IoV data analysis, and shows the difference between a near real-time analytic platform and an actual real-time analytic platform with a real-world example. - Getting Started with Graph Database Queries, with Cheat Sheet! - Nov 6, 2023.
Graph databases are quickly becoming a core part of the analytics toolset for enterprise IT organizations. If you know SQL, you can easily learn Cypher and open up a huge opportunity for data analysis. - Data Warehouses vs. Data Lakes vs. Data Marts: Need Help Deciding? - Oct 30, 2023.
A comparative overview of data warehouses, data lakes, and data marts to help you make informed decisions on data storage solutions for your data architecture. - 7 Best Cloud Database Platforms - Oct 18, 2023.
Cloud databases have made it easier and cheaper to develop enterprise-level applications, offering flexibility, convenience, and standard database functionality. See what KDnuggets recommends. - Exploring Data Mesh: A Paradigm Shift in Data Architecture - Oct 13, 2023.
Let’s explore Data Mesh, a modern approach to data architecture that decentralizes data ownership and management. - Best Practices for Building ETLs for ML - Oct 12, 2023.
This article talks about several best practices for writing ETLs for building training datasets. It delves into several software engineering techniques and patterns applied to ML. - Getting Started with Google Cloud Platform in 5 Steps - Oct 1, 2023.
Explore the essentials of Google Cloud Platform for data science and ML, from account setup to model deployment, with hands-on project examples. - A Comprehensive Guide to Pinecone Vector Databases - Sep 12, 2023.
This blog discusses vector databases, specifically pinecone vector databases. A vector database is a type of database that stores data as mathematical vectors, which represent features or attributes. These vectors have multiple dimensions, capturing complex data relationships. This allows for efficient similarity and distance calculations, making it useful for tasks like machine learning, data analysis, and recommendation systems. - Working with Big Data: Tools and Techniques - Sep 11, 2023.
Where do you start in a field as vast as big data? Which tools and techniques to use? We explore this and talk about the most common tools in big data. - Building a Formula 1 Streaming Data Pipeline With Kafka and Risingwave - Sep 5, 2023.
Build a streaming data pipeline using Formula 1 data, Python, Kafka, RisingWave as the streaming database, and visualize all the real-time data in Grafana. - How to Digest 15 Billion Logs Per Day and Keep Big Queries Within 1 Second - Sep 1, 2023.
This article describes a large-scale data warehousing use case to provide reference for data engineers who are looking for log analytic solutions. It introduces the log processing architecture and real-case practice in data ingestion, storage, and queries. - 2024 Data Management Crystal Ball: Top 4 Emerging Trends - Aug 31, 2023.
These are my predictions based on my personal experiences, recent research and reports from leading platforms. - Creating A Simple Docker Data Science Image - Aug 28, 2023.
This concise primer walks through setting up a Python data science environment using Docker, covering creating a Dockerfile, building an image, running a container, sharing and deploying images, and pushing to Docker Hub. - Things You Should Know When Scaling Your Web Data-Driven Product - Aug 25, 2023.
Scaling your data-driven product helps grow your business, but it requires certain expertise. In this article, you will learn how scaling works and what to keep in mind while doing it. - How to Build a Real-Time Recommendation Engine Using Graph Databases - Aug 18, 2023.
"You may also like" is a simple phrase that implies a new era in the way businesses interact and connect with their customers, and graph databases can easily help to build recommendation engines. - Top 6 Tools to Improve Your Productivity on Snowflake - Aug 15, 2023.
The post reviews 6 top tools for improving productivity with Snowflake for data preparation, visualization, integration, BI and governance. - CDC Data Replication: Techniques, Tradeoffs, Insights - Aug 7, 2023.
The author discusses common use cases for CDC data replication, implementation techniques and their tradeoffs, and firsthand insights. - A Beginner’s Guide to Data Engineering - Jul 20, 2023.
So you want to break into data engineering? Start today by learning more about data engineering and the fundamental concepts. - How to Build a Streaming Semi-structured Analytics Platform on Snowflake - Jul 1, 2023.
Building a datalake for semi-structured data or json has always been challenging. Imagine if the json documents are streaming or continuously flowing from healthcare vendors then we need a robust modern architecture that can deal with such a high volume. At the same time analytics layer also needs to be created so as to generate value from it. - Evolution of the Data Landscape - Jun 27, 2023.
The article follows the story of evolution in the data space through the lens of evolutionary patterns. It talks of the state of significant milestones in the evolutionary journey, their achievements, challenges, and the next milestone that solved those challenges. The article comes from both a business and technical perspective, owing to the persona of the authors. - Data Engineering Landscape in the AI-Driven World - May 24, 2023.
Generative AI has just started to capture the imagination of data engineers, so the impact thus far has been just a fraction of what it will be a year or two from now. - Should You Consider a DataOps Career? - May 15, 2023.
Transitioning your career to DataOps could be just the change you need - not only will it provide the possibility to expand your technical skills, but also a rewarding salary with many job openings. - Schedule & Run ETLs with Jupysql and GitHub Actions - May 1, 2023.
This blog provided you with a comprehensive overview of ETL and JupySQL, including a brief introduction to ETLs and JupySQL. We also demonstrated how to schedule an example ETL notebook via GitHub actions, which allows you to automate the process of executing ETLs and JupySQL from Jupyter. - 11 Best Practices of Cloud and Data Migration to AWS Cloud - Apr 14, 2023.
list of Best Practices compiled from our learnings during our migration journey to the AWS cloud. - How to Build a Scalable Data Architecture with Apache Kafka - Apr 5, 2023.
Learn about Apache Kafka architecture and its implementation using a real-world use case of a taxi booking app. - ETL vs ELT: Which One is Right for Your Data Pipeline? - Mar 31, 2023.
Learn about the differences between ETL and ELT data integration techniques and determine which is right for your data pipeline. - Data Quality Dimensions: Assuring Your Data Quality with Great Expectations - Mar 23, 2023.
This article highlights the significance of ensuring high-quality data and presents six key dimensions for measuring it. These dimensions include Completeness, Consistency, Integrity, Timelessness, Uniqueness, and Validity. - A List of 7 Best Data Modeling Tools for 2023 - Mar 3, 2023.
Learn about data modeling tools to create, design and manage data models, allowing data scientists to access and use them more quickly. - Data Warehousing and ETL Best Practices - Feb 27, 2023.
How you can improve your data warehousing ETL process with these simple practices. - 5 SQL Visualization Tools for Data Engineers
- Feb 24, 2023.
This article will discuss SQL visualization, its role in augmenting the modern-day data engineer, and five categories of SQL visualization tools. - Docker for Data Science Cheat Sheet - Feb 14, 2023.
Docker is dependency management on steroids, helping to ensure both reproducibility and collaboration, making it an important tool for data science. Our latest cheat sheet serves as a handy Docker reference. Check it out now! - Learn Data Engineering From These GitHub Repositories
- Feb 7, 2023.
Kickstart your Data Engineering career with these curated GitHub repositories. - Tapping into the Potential of Data Products in 2023 - Jan 31, 2023.
Learn how data can be treated as a product and how it can be used to derive value. - Scaling Data Management Through Apache Gobblin - Jan 20, 2023.
Software companies can manage big data at a hyper-scale on different infrastructure stacks using Apache Gobblin. - SQL and Data Integration: ETL and ELT - Jan 19, 2023.
In this article, we will discuss use cases and methods for using ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) processes along with SQL to integrate data from various sources. - Data Lakes and SQL: A Match Made in Data Heaven - Jan 16, 2023.
In this article, we will discuss the benefits of using SQL with a data lake and how it can help organizations unlock the full potential of their data. - Overcome Your Data Quality Issues with Great Expectations - Jan 12, 2023.
Bad data costs organizations money, reputation, and time. Hence it is very important to monitor and validate data quality continuously. - Where Collaboration Fails Around Data (And 4 Tips for Fixing It) - Jan 9, 2023.
Data-driven organizations require complex collaboration between data teams and business stakeholders. Here are 4 proactive tips for reducing information asymmetries and achieving better collaboration. - 7 Essential Cheat Sheets for Data Engineering
- Dec 6, 2022.
Learn about the data life cycle, PySpark, dbt, Kafka, BigQuery, Airflow, and Docker. - The Complete Data Engineering Study Roadmap
- Nov 28, 2022.
Everything you need to know to start your career in Data Engineering. - Is OLAP Dead? - Oct 21, 2022.
OLAP enables citizen analysts to quickly, efficiently, and cost-effectively uncover new business insights at a reduced time-to-value. - Essential Books You Need to Become a Data Engineer
- Oct 18, 2022.
In this article, I will go through the roadmap of books you need to become a Data Engineer. - 11 Questions About Data Engineers: What’s the profession about, and where’s it heading? - Oct 6, 2022.
I hope my answers will be useful to novice data engineers and anyone interested in data engineering. - The Evolution of Apache Druid - Jul 19, 2022.
And so true to the origins of its name, Apache Druid is shapeshifting - with the addition of a new multi-stage query engine. - 10 Modern Data Engineering Tools - Jul 11, 2022.
Learn about the modern tools for data orchestration, data storage, analytical engineering, batch processing, and data streaming. - Free Data Engineering Courses - May 30, 2022.
Get into the highly in-demand world of data engineering for free and earn 6 figures salary. - Deploying a Streamlit WebApp to Heroku using DAGsHub - Feb 7, 2022.
Transform your machine learning models into a web app and share them with your friends and colleagues. - Is the Modern Data Stack Leaving You Behind? - Nov 1, 2021.
The modern data stack narrative is largely dominated by analytics engineering. Where does that leave data engineers? Discover the difference between the MDS for data engineers & analytics engineers. - Data Engineering Technologies 2021 - Sep 21, 2021.
Emerging technologies supporting the field of data engineering are growing at a rapid clip. This curated list includes the most important offerings available in 2021.Abacus.ai, Dask, Data Engineering, Databricks, Dataiku, DataRobot, dbt, Fivetran, Pachyderm
Data Scientists Without Data Engineering Skills Will Face the Harsh Truth - Sep 14, 2021.
Although the role of the data scientist is still evolving, data remains at its core. Setting the right expectations for what you will do as a data scientist is important, and, to be sure, knowing the tools of data engineering will get yourself ready for the real world.- The Most Important Tool for Data Engineers - Aug 26, 2021.
And it has nothing to do with Python or SQL - Model Drift in Machine Learning – How To Handle It In Big Data - Aug 17, 2021.
Rendezvous Architecture helps you run and choose outputs from a Champion model and many Challenger models running in parallel without many overheads. The original approach works well for smaller data sets, so how can this idea adapt to big data pipelines?Big Data, Data Engineering, Data Preparation, Machine Learning, Model Drift
- Development & Testing of ETL Pipelines for AWS Locally - Aug 2, 2021.
Typically, development and testing ETL pipelines is done on real environment/clusters which is time consuming to setup & requires maintenance. This article focuses on the development and testing of ETL pipelines locally with the help of Docker & LocalStack. The solution gives flexibility to test in a local environment without setting up any services on the cloud. - dbt for Data Transformation – Hands-on Tutorial - Jul 28, 2021.
The data build tool (dbt) is gaining in popularity and use, and this hands-on tutorial covers creating complex models, using variables and functions, running tests, generating docs, and many more features. - MLOps is an Engineering Discipline: A Beginner’s Overview - Jul 8, 2021.
MLOps = ML + DEV + OPS. MLOps is the idea of combining the long-established practice of DevOps with the emerging field of Machine Learning.Data Engineering, Deployment, Machine Learning, MLOps, Modeling
Analytics Engineering Everywhere - Jun 22, 2021.
Many new roles have appeared in the data world ever since the rise of the Data Scientist took the spotlight several years ago. Now, there is a new core player ready to take center stage, and we may see in five years, nearly every organization will have an Analytics Engineering team.- DataOps: 5 things that you need to know - May 20, 2021.
DataOps (Data Operations) has assumed a critical role in the age of big data to drive definitive impact on business outcomes. This process-oriented and agile methodology synergizes the components of DevOps and the capabilities of data engineers and data scientists to support data-focused workloads in enterprises. Here is a detailed look at DataOps. Why You Should Consider Being a Data Engineer Instead of a Data Scientist - Apr 27, 2021.
A new king of the jungle has emerged.Career Advice, Data Engineer, Data Engineering, Data Science, Data Scientist
- Data careers are NOT one-size fits all! Tips for uncovering your ideal role in the data space - Apr 23, 2021.
Thriving as a data professional is about more than just making good money! It’s about FULFILLMENT & IMPACT. In this article, I will help you discover the BEST data role for you given your unique skill sets, personality & goals. - How to build a DAG Factory on Airflow - Mar 19, 2021.
A guide to building efficient DAGs with half of the code. - Introducing dbt, the ETL and ELT Disrupter - Mar 17, 2021.
Moving and processing data is happening 24/7/365 world-wide at massive scales that only get larger by the hour. Tools exist to introduce efficiencies in how data can be extracted from sources, transformed through calculations, and loaded into target data repositories. However, on their own, these tools can introduce some restrictions in the processing, especially for the needs of data analytics and data science. Data Science Learning Roadmap for 2021 - Feb 26, 2021.
Venturing into the world of Data Science is an exciting, interesting, and rewarding path to consider. There is a great deal to master, and this self-learning recommendation plan will guide you toward establishing a solid understanding of all that is foundational to data science as well as a solid portfolio to showcase your developed expertise.Data Engineering, Data Preparation, Data Science, Data Science Education, Python, Roadmap, SQL
- Data Observability, Part II: How to Build Your Own Data Quality Monitors Using SQL - Feb 23, 2021.
Using schema and lineage to understand the root cause of your data anomalies.Data Engineering, Data Quality, Data Science, Data Science Platform, SQL
- Feature Store as a Foundation for Machine Learning - Feb 19, 2021.
With so many organizations now taking the leap into building production-level machine learning models, many lessons learned are coming to light about the supporting infrastructure. For a variety of important types of use cases, maintaining a centralized feature store is essential for higher ROI and faster delivery to market. In this review, the current feature store landscape is described, and you can learn how to architect one into your MLOps pipeline.Data Engineering, Data Infrastructure, Data Lake, Feature Engineering, Feature Store, Machine Learning, Metadata, MLOps, Pipeline
- Data Observability: Building Data Quality Monitors Using SQL - Feb 16, 2021.
To trigger an alert when data breaks, data teams can leverage a tried and true tactic from our friends in software engineering: monitoring and observability. In this article, we walk through how you can create your own data quality monitors for freshness and distribution from scratch using SQL.Data Engineering, Data Quality, Data Science, Data Science Platform, SQL
Data Engineering — the Cousin of Data Science, is Troublesome - Jan 22, 2021.
A Data Scientist must be a jack of many, many trades. Especially when working in broader teams, understanding the roles of others, such as data engineering, can help you validate progress and be aware of potential pitfalls. So, how can you convince your analysts to realize the importance of expanding their toolkit? Examples from real life often provide great insight.Data Analyst, Data Engineer, Data Engineering, Data Scientist
- How to Get a Job as a Data Engineer - Jan 5, 2021.
Data engineering skills are currently in high demand. If you are looking for career prospects in this fast-growing profession, then these 10 skills and key factors will help you prepare to land an entry-level position in this field. - The Future of Cloud is Now - Dec 22, 2020.
Our recent survey of over 130 top data engineers, data architects, and executives uncovered details and trends of the current state of data engineering and DataOps.Read our survey report to learn more about these trends as well as our predictions for future obstacles and our recommendations for avoiding them. - The Ultimate Guide to Data Engineer Interviews - Dec 7, 2020.
If you are preparing for data engineering interviews, then follow these technical recommendations regarding your resume, programming skills, SQL acumen, and system design problem-solving, as well as the non-technical aspects of your upcoming interview session.Career Advice, Data Engineer, Data Engineering, Interview Questions, Programming, SQL
Why the Future of ETL Is Not ELT, But EL(T) - Dec 4, 2020.
The well-established technologies and tools around ETL (Extract, Transform, Load) are undergoing a potential paradigm shift with new approaches to data storage and expanding cloud-based compute. Decoupling the EL from T could reconcile analytics and operational data management use cases, in a new landscape where data warehouses and data lakes are merging.Data Analysis, Data Engineering, Data Lakes, Data Preparation, ELT, ETL
Introduction to Data Engineering - Dec 3, 2020.
The Q&A for the most frequently asked questions about Data Engineering: What does a data engineer do? What is a data pipeline? What is a data warehouse? How is a data engineer different from a data scientist? What skills and programming languages do you need to learn to become a data engineer?Analytics, Data Engineer, Data Engineering, Data Science, Skills
The Rise of the Machine Learning Engineer - Nov 23, 2020.
The evolution of Big Data into machine learning applications ushered in an exciting era of new roles and skillsets that became necessary to implement these technologies. With the Machine Learning Engineer being such a crucial component today, where the evolution of this field will take us tomorrow should be fascinating.Data Engineer, Data Engineering, Data Scientist, Machine Learning Engineer, Trends
- Moving from Data Science to Machine Learning Engineering - Nov 10, 2020.
The world of machine learning — and software — is changing. Read this article to find out how, and what you can do to stay ahead of it.Career Advice, Data Engineering, Data Science, Machine Learning, Machine Learning Engineer
- The Missing Teams For Data Scientists - Nov 2, 2020.
Still today, too large a percent of data science projects fail, many of which can be attributed to the impacts of how hard missing data teams hit the data science team. Advocating for the missing data engineering and operations components to your team will make your professional life easier and more productive.Data Engineering, Data Science Skills, Data Science Team, Data Scientist, Team
- You Don’t Have to Use Docker Anymore - Oct 29, 2020.
Docker is not the only containerization tool out there and there might just be better alternatives… - Apache Spark Cluster on Docker - Jul 22, 2020.
Build your own Apache Spark cluster in standalone mode on Docker with a JupyterLab interface. Skills to Build for Data Engineering - Jun 4, 2020.
This article jumps into the latest skill set observations in the Data Engineering Job Market which could definitely add a boost to your existing career or assist you in starting off your Data Engineering journey.- Why and How to Use Dask with Big Data - Apr 15, 2020.
The Pandas library for Python is a game-changer for data preparation. But, when the data gets big, really big, then your computer needs more help to efficiency handle all that data. Learn more about how to use Dask and follow a demo to scale up your Pandas to work with Big Data. - Five Interesting Data Engineering Projects - Mar 17, 2020.
As the role of the data engineer continues to grow in the field of data science, so are the many tools being developed to support wrangling all that data. Five of these tools are reviewed here (along with a few bonus tools) that you should pay attention to for your data pipeline work.Dask, Data Engineering, dbt, DVC, Python
- Scaling the Wall Between Data Scientist and Data Engineer - Feb 17, 2020.
The educational and research focuses of machine learning tends to highlight the model building, training, testing, and optimization aspects of the data science process. To bring these models into use requires a suite of engineering feats and organization, a standard for which does not yet exist. Learn more about a framework for operating a collaborative data science and engineering team to deploy machine learning models to end-users.Advice, Data Engineer, Data Engineering, Data Scientist, Deployment, DevOps, Machine Learning Engineer, MLflow, MLOps, Production
- Observability for Data Engineering - Feb 10, 2020.
Going beyond traditional monitoring techniques and goals, understanding if a system is working as intended requires a new concept in DevOps, called Observability. Learn more about this essential approach to bring more context to your system metrics.Data Engineering, DevOps, Explainability, KPI, Monitoring, Time Series
7 Resources to Becoming a Data Engineer - Jan 7, 2020.
An estimated 8,650% growth of the volume of Data to 175 zetabytes from 2010 to 2025 has created an enormous need for Data Engineers to build an organization's big data platform to be fast, efficient and scalable.Advice, Big Data, Cloud Computing, Data Engineering, Data Science, MOOC, SQL
- Four questions to help accurately scope analytics engineering project - Oct 9, 2019.
Being really good at scoping analytics projects is crucial for team productivity and profitability. You can consistently deliver on time if you work out the issue first, and these four questions can help you prepare. - The thin line between data science and data engineering - Sep 25, 2019.
Today, as companies have finally come to understand the value that data science can bring, more and more emphasis is being placed on the implementation of data science in production systems. And as these implementations have required models that can perform on larger and larger datasets in real-time, an awful lot of data science problems have become engineering problems. - Mongo DB Basics - Jun 5, 2019.
Mongo DB is a document oriented NO SQL database unlike HBASE which has a wide column store. The advantage of Document oriented over relation type is the columns can be changed as an when required for each case as opposed to the same column name for all the rows.
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