Building a Scalable ETL with SQL + Python
KDnuggets
APRIL 21, 2022
This post will look at building a modular ETL pipeline that transforms data with SQL and visualizes it with Python and R.
Data Science ETL SQL 
Remote Data Science Jobs: 5 High-Demand Roles for Career Growth
Data Science Dojo
OCTOBER 31, 2024
Remote work quickly transitioned from a perk to a necessity, and data science—already digital at heart—was poised for this change. For data scientists, this shift has opened up a global market of remote data science jobs, with top employers now prioritizing skills that allow remote professionals to thrive.
Data Science 
195
195 Join 17,000+
professionals
Sign Up for our Newsletter
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
From Blob Storage to SQL Database Using Azure Data Factory
Analytics Vidhya
APRIL 29, 2022
This article was published as a part of the Data Science Blogathon. Introduction Azure data factory (ADF) is a cloud-based ETL (Extract, Transform, Load) tool and data integration service which allows you to create a data-driven workflow. In this article, I’ll show […].
Azure 329
329 
KDnuggets News, April 27: A Brief Introduction to Papers With Code; Machine Learning Books You Need To Read In 2022
KDnuggets
APRIL 27, 2022
A Brief Introduction to Papers With Code; Machine Learning Books You Need To Read In 2022; Building a Scalable ETL with SQL + Python; 7 Steps to Mastering SQL for Data Science; Top Data Science Projects to Build Your Skills.
Machine Learning 270
270 
Navigate your way to success – Top 10 data science careers to pursue in 2023
Data Science Dojo
MAY 10, 2023
Navigating the realm of data science careers is no longer a tedious task. In the current landscape, data science has emerged as the lifeblood of organizations seeking to gain a competitive edge.
Data Science 298
298 
CI/CD for Data Pipelines: A Game-Changer with AnalyticsCreator
Data Science Blog
MAY 20, 2024
Continuous Integration and Continuous Delivery (CI/CD) for Data Pipelines: It is a Game-Changer with AnalyticsCreator! The need for efficient and reliable data pipelines is paramount in data science and data engineering. Data Lakes : It supports MS Azure Blob Storage. pipelines, Azure Data Bricks.
Data Pipeline 262
262 
Serverless High Volume ETL data processing on Code Engine
IBM Data Science in Practice
JANUARY 13, 2025
By Santhosh Kumar Neerumalla , Niels Korschinsky & Christian Hoeboer Introduction This blogpost describes how to manage and orchestrate high volume Extract-Transform-Load (ETL) loads using a serverless process based on Code Engine. The source data is unstructured JSON, while the target is a structured, relational database.
ETL 100
100 
Understand Apache Drill and its Working
Analytics Vidhya
AUGUST 29, 2022
This article was published as a part of the Data Science Blogathon. Introduction Data scientists, engineers, and BI analysts often need to analyze, process, or query different data sources.
ETL 288
288 
A Guide to Choose the Best Data Science Bootcamp
Data Science Dojo
JULY 3, 2024
Data science bootcamps are intensive short-term educational programs designed to equip individuals with the skills needed to enter or advance in the field of data science. They cover a wide range of topics, ranging from Python, R, and statistics to machine learning and data visualization.
Data Science 150
150 
How Rocket Companies modernized their data science solution on AWS
AWS Machine Learning Blog
FEBRUARY 21, 2025
Rockets legacy data science environment challenges Rockets previous data science solution was built around Apache Spark and combined the use of a legacy version of the Hadoop environment and vendor-provided Data Science Experience development tools.
Data Science 70
70 
Why using Infrastructure as Code for developing Cloud-based Data Warehouse Systems?
Data Science Blog
SEPTEMBER 19, 2023
In the contemporary age of Big Data, Data Warehouse Systems and Data Science Analytics Infrastructures have become an essential component for organizations to store, analyze, and make data-driven decisions. So why using IaC for Cloud Data Infrastructures?
Data Warehouse 259
259 
The 2021 Executive Guide To Data Science and AI
Applied Data Science
AUGUST 2, 2021
This post is a bitesize walk-through of the 2021 Executive Guide to Data Science and AI — a white paper packed with up-to-date advice for any CIO or CDO looking to deliver real value through data. Team Building the right data science team is complex. Download the free, unabridged version here.
Data Science 130
130 
CI/CD für Datenpipelines – Ein Game-Changer mit AnalyticsCreator
Data Science Blog
JULY 20, 2024
Die Bedeutung effizienter und zuverlässiger Datenpipelines in den Bereichen Data Science und Data Engineering ist enorm. Automatisierung: Erstellt SQL-Code, DACPAC-Dateien, SSIS-Pakete, Data Factory-ARM-Vorlagen und XMLA-Dateien. Data Lakes: Unterstützt MS Azure Blob Storage.
Azure 130
130 
Explore data with ease: Use SQL and Text-to-SQL in Amazon SageMaker Studio JupyterLab notebooks
AWS Machine Learning Blog
APRIL 16, 2024
In the process of working on their ML tasks, data scientists typically start their workflow by discovering relevant data sources and connecting to them. They then use SQL to explore, analyze, visualize, and integrate data from various sources before using it in their ML training and inference.
SQL 113
113 
5 Reasons Why SQL is Still the Most Accessible Language for New Data Scientists
ODSC - Open Data Science
APRIL 6, 2023
Though both are great to learn, what gets left out of the conversation is a simple yet powerful programming language that everyone in the data science world can agree on, SQL. But why is SQL, or Structured Query Language , so important to learn? Finally, SQL’s window function. Let’s briefly dive into each bit.
SQL 98
98 
Essential data engineering tools for 2023: Empowering for management and analysis
Data Science Dojo
JULY 6, 2023
Data engineering tools are software applications or frameworks specifically designed to facilitate the process of managing, processing, and transforming large volumes of data. It allows data engineers to define and manage complex workflows as directed acyclic graphs (DAGs).
Data Engineering 195
195 
ETL Process Explained: Essential Steps for Effective Data Management
Pickl AI
OCTOBER 17, 2024
Summary: The ETL process, which consists of data extraction, transformation, and loading, is vital for effective data management. Following best practices and using suitable tools enhances data integrity and quality, supporting informed decision-making. Introduction The ETL process is crucial in modern data management.
ETL 52
52 
Maximising Efficiency with ETL Data: Future Trends and Best Practices
Pickl AI
OCTOBER 17, 2024
Summary: This article explores the significance of ETL Data in Data Management. It highlights key components of the ETL process, best practices for efficiency, and future trends like AI integration and real-time processing, ensuring organisations can leverage their data effectively for strategic decision-making.
ETL 52
52 
Top ETL Tools: Unveiling the Best Solutions for Data Integration
Pickl AI
JUNE 7, 2024
Summary: Choosing the right ETL tool is crucial for seamless data integration. Top contenders like Apache Airflow and AWS Glue offer unique features, empowering businesses with efficient workflows, high data quality, and informed decision-making capabilities. Choosing the right ETL tool is crucial for smooth data management.
ETL 40
40 
The Data Dilemma: Exploring the Key Differences Between Data Science and Data Engineering
Pickl AI
JULY 25, 2023
Data engineers are essential professionals responsible for designing, constructing, and maintaining an organization’s data infrastructure. They create data pipelines, ETL processes, and databases to facilitate smooth data flow and storage. Big Data Technologies: Hadoop, Spark, etc.
What is Open Database Connectivity (ODBC) and Why Is It Important?
Pickl AI
NOVEMBER 4, 2024
Each database type requires its specific driver, which interprets the application’s SQL queries and translates them into a format the database can understand. The driver manages the connection to the database, processes SQL commands, and retrieves the resulting data. INSERT : Add new records to a table.
Database 52
52 
How to Shift from Data Science to Data Engineering
ODSC - Open Data Science
JANUARY 18, 2024
These professionals will work with their colleagues to ensure that data is accessible, with proper access. So let’s go through each step one by one, and help you build a roadmap toward becoming a data engineer. Identify your existing data science strengths. Stay on top of data engineering trends.
Difference Between JDBC and ODBC in Database Connectivity
Pickl AI
NOVEMBER 5, 2024
It allows developers to easily connect to databases, execute SQL queries, and retrieve data. It operates as an intermediary, translating Java calls into SQL commands the database understands. For instance, reporting and analytics tools commonly use it to pull data from various database systems. from 2023 to 2030.
Database 52
52 
Top Data Analytics Skills and Platforms for 2023
ODSC - Open Data Science
APRIL 3, 2023
As the sibling of data science, data analytics is still a hot field that garners significant interest. Companies have plenty of data at their disposal and are looking for people who can make sense of it and make deductions quickly and efficiently. Cloud Services: Google Cloud Platform, AWS, Azure.
Analytics 52
52 
Data Version Control for Data Lakes: Handling the Changes in Large Scale
ODSC - Open Data Science
SEPTEMBER 27, 2023
Data Warehouses and Relational Databases It is essential to distinguish data lakes from data warehouses and relational databases, as each serves different purposes and has distinct characteristics. Schema Enforcement: Data warehouses use a “schema-on-write” approach. This ensures data consistency and integrity.
Data Lakes 98
98 
Introduction to Power BI Datamarts
ODSC - Open Data Science
JUNE 12, 2023
Then we have some other ETL processes to constantly land the past 5 years of data into the Datamarts. Then we have some other ETL processes to constantly land the past 5 years of data into the Datamarts. No-code/low-code experience using a diagram view in the data preparation layer similar to Dataflows.
Power BI 52
52 
Azure service cloud summarized: Part I
Mlearning.ai
APRIL 24, 2023
Over the past few years Data Science has MIGRATED from individual computers to service cloud platforms. I just finished learning Azure’s service cloud platform using Coursera and the Microsoft Learning Path for Data Science. It will take a couple of months but it is worth it!
Azure 52
52 6 Data And Analytics Trends To Prepare For In 2020
Smart Data Collective
MAY 20, 2019
By 2020, over 40 percent of all data science tasks will be automated. The popular tools, on the other hand, include Power BI, ETL, IBM Db2, and Teradata. This means that data professionals must be able to effectively communicate complex subjects to non-technical professionals. Machine Learning Experience is a Must.
Analytics 111
111 
Software Engineering Patterns for Machine Learning
The MLOps Blog
SEPTEMBER 7, 2023
Data Scientists and ML Engineers typically write lots and lots of code. From writing code for doing exploratory analysis, experimentation code for modeling, ETLs for creating training datasets, Airflow (or similar) code to generate DAGs, REST APIs, streaming jobs, monitoring jobs, etc. Related post MLOps Is an Extension of DevOps.
The Modern Data Stack Explained: What The Future Holds
Alation
JANUARY 17, 2023
It is known to have benefits in handling data due to its robustness, speed, and scalability. A typical modern data stack consists of the following: A data warehouse. Data ingestion/integration services. Reverse ETL tools. Data orchestration tools. A Note on the Shift from ETL to ELT.
How to Better Plan Your Snowflake Migration
phData
SEPTEMBER 26, 2023
Data flows from the current data platform to the destination. The necessary access is granted so data flows without issue. SQL Server Agent jobs). Transformations Transformations can be a part of data ingestion (ETL pattern) or can take place at a later stage after data has been landed (ELT pattern).
SQL 52
52 
Data Lakes Vs. Data Warehouse: Its significance and relevance in the data world
Pickl AI
NOVEMBER 15, 2023
What Is a Data Warehouse? On the other hand, a Data Warehouse is a structured storage system designed for efficient querying and analysis. It involves the extraction, transformation, and loading (ETL) process to organize data for business intelligence purposes. It often serves as a source for Data Warehouses.
Data Lakes 52
52 
How to Use Exploratory Notebooks [Best Practices]
The MLOps Blog
OCTOBER 20, 2023
Jupyter notebooks have been one of the most controversial tools in the data science community. Nevertheless, many data scientists will agree that they can be really valuable – if used well. I’ll show you best practices for using Jupyter Notebooks for exploratory data analysis. documentation. For one, Git diffs within.py
SQL 52
52 
Discover the Most Important Fundamentals of Data Engineering
Pickl AI
NOVEMBER 4, 2024
Additionally, Data Engineers implement quality checks, monitor performance, and optimise systems to handle large volumes of data efficiently. Differences Between Data Engineering and Data Science While Data Engineering and Data Science are closely related, they focus on different aspects of data.
Beginner’s Guide To GCP BigQuery (Part 1)
Mlearning.ai
JULY 10, 2023
In my 7 years of Data Science journey, I’ve been exposed to a number of different databases including but not limited to Oracle Database, MS SQL, MySQL, EDW, and Apache Hadoop. A lot of you who are already in the data science field must be familiar with BigQuery and its advantages.
SQL 52
52 
Where Does Fivetran Fit into The Modern Data Stack?
phData
JULY 17, 2023
In order to fully leverage this vast quantity of collected data, companies need a robust and scalable data infrastructure to manage it. This is where Fivetran and the Modern Data Stack come in. We can also create advanced data science models with this data using AI/ Machine Learning. What is Fivetran?
How Does Snowpark Work?
phData
FEBRUARY 7, 2024
Snowpark is the set of libraries and runtimes in Snowflake that securely deploy and process non-SQL code, including Python, Java, and Scala. A DataFrame is like a query that must be evaluated to retrieve data. An action causes the DataFrame to be evaluated and sends the corresponding SQL statement to the server for execution.
Python 52
52 
Importing Data in Python Cheat Sheet with Comprehensive Tutorial
Pickl AI
NOVEMBER 14, 2023
Whether you’re working on Data Analysis, Machine Learning, or any other data-related task, having a well-organized Importing Data in Python Cheat Sheet for importing data in Python is invaluable. So, let me present to you an Importing Data in Python Cheat Sheet which will make your life easier.
Python 52
52 
Top 50+ Data Analyst Interview Questions & Answers
Pickl AI
APRIL 26, 2024
This comprehensive blog outlines vital aspects of Data Analyst interviews, offering insights into technical, behavioural, and industry-specific questions. It covers essential topics such as SQL queries, data visualization, statistical analysis, machine learning concepts, and data manipulation techniques.
Data Analyst 52
52 
What is Alteryx certification: A comprehensive guide
Pickl AI
FEBRUARY 4, 2024
Furthermore, Alteryx provides an array of tools and connectors tailored for different data sources, spanning Excel spreadsheets, databases, and social media platforms. Data Analytics automation Alteryx’s standout feature lies in its capability to automate data analytics workflows. Is Alteryx an ETL tool?
Drowning in Data? A Data Lake May Be Your Lifesaver
ODSC - Open Data Science
SEPTEMBER 29, 2023
It truly is an all-in-one data lake solution. HPCC Systems and Spark also differ in that they work with distinct parts of the big data pipeline. Spark is more focused on data science, ingestion, and ETL, while HPCC Systems focuses on ETL and data delivery and governance. Tell me more about ECL.
Data Lakes 52
52 
Exploring the AI and data capabilities of watsonx
IBM Journey to AI blog
JULY 17, 2023
By supporting open-source frameworks and tools for code-based, automated and visual data science capabilities — all in a secure, trusted studio environment — we’re already seeing excitement from companies ready to use both foundation models and machine learning to accomplish key tasks.
AI 74
74 
What Free Tools Pair Well With The Snowflake AI Data Cloud?
phData
OCTOBER 17, 2024
Apache Airflow Airflow is an open-source ETL software that is very useful when paired with Snowflake. dbt offers a SQL-first transformation workflow that lets teams build data transformation pipelines while following software engineering best practices like CI/CD, modularity, and documentation.
AI 52
52 
Data architecture strategy for data quality
IBM Journey to AI blog
JANUARY 5, 2023
The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases.
Data Quality 52
52 
Let's personalize your content