KDnuggets

JUNE 6, 2025

Blog Top Posts About Topics AI Career Advice Computer Vision Data Engineering Data Science Language Models Machine Learning MLOps NLP Programming Python SQL Datasets Events Resources Cheat Sheets Recommendations Tech Briefs Advertise Join Newsletter 5 Error Handling Patterns in Python (Beyond Try-Except) Stop letting errors crash your app.

Python 235

Python Natural Language Processing Data Science Machine Learning 235

databricks

JUNE 11, 2025

Deeply integrated with the lakehouse, Lakebase simplifies operational data workflows. It eliminates fragile ETL pipelines and complex infrastructure, enabling teams to move faster and deliver intelligent applications on a unified data platform In this blog, we propose a new architecture for OLTP databases called a lakebase.

Database 212

Database Data Lakes ETL Analytics 212

databricks

JUNE 11, 2025

160 Spear Street, 15th Floor San Francisco, CA 94105 1-866-330-0121 See Careers at Databricks © Databricks 2025.

Analytics 331

Analytics Analytics AI Data Science 331

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

Data Pipeline Data Warehouse Azure Data Lakes 262

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

ETL Data Pipeline Database Data Warehouse 100

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 287

ETL Data Scientist Data Science Analytics 287

databricks

JUNE 12, 2025

160 Spear Street, 15th Floor San Francisco, CA 94105 1-866-330-0121 See Careers at Databricks © Databricks 2025.

Data Engineer 233

Data Engineer Data Engineering Data Engineering Data Engineering 233

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

Data Science Machine Learning Machine Learning Data Visualization 150

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 72

Data Science AWS Hadoop Data Scientist 72

How to Learn Machine Learning

APRIL 26, 2025

The field of data science is now one of the most preferred and lucrative career options available in the area of data because of the increasing dependence on data for decision-making in businesses, which makes the demand for data science hires peak.

Data Science 52

Data Science Data Analyst Data Scientist Machine Learning 52

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

Data Warehouse Azure SQL Database 259

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

Data Science Data Scientist ML ML 130

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

SQL Data Scientist Database Data Science 98

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 118

SQL AWS Database Data Scientist 118

databricks

JUNE 4, 2025

160 Spear Street, 15th Floor San Francisco, CA 94105 1-866-330-0121 See Careers at Databricks © Databricks 2025.

AWS 130

AWS AI AI Data Science 130

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

Data Engineering Data Engineering Data Engineering Data Engineer 195

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

ETL Data Warehouse Data Quality SQL 52

AWS Machine Learning Blog

JUNE 11, 2025

Gardenia Technologies, a data analytics company, partnered with the AWS Prototyping and Cloud Engineering (PACE) team to develop Report GenAI , a fully automated ESG reporting solution powered by the latest generative AI models on Amazon Bedrock. The Lambda-hosted text-to-SQL tool provides the agent with the required analytical capabilities.

AWS 89

AWS SQL Database AI 89

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

ETL Data Warehouse Data Quality Data Governance 52

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.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

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

Database SQL ETL Azure 52

Flipboard

NOVEMBER 24, 2023

This use case highlights how large language models (LLMs) are able to become a translator between human languages (English, Spanish, Arabic, and more) and machine interpretable languages (Python, Java, Scala, SQL, and so on) along with sophisticated internal reasoning. Room for improvement!

Database 157

Database AWS ETL SQL 157

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

ETL Data Quality Data Pipeline Data Warehouse 40

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.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

Pickl AI

MARCH 19, 2025

Summary: Data engineering tools streamline data collection, storage, and processing. Tools like Python, SQL, Apache Spark, and Snowflake help engineers automate workflows and improve efficiency. Learning these tools is crucial for building scalable data pipelines. How is Data Engineering Different from Data Science?

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

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

Database SQL Python Database Administration 52

ODSC - Open Data Science

DECEMBER 9, 2024

What was once only possible for tech giants is now at our fingertipsvast amounts of data and analytical tools with the power to drive real progress. Open data science is making it a reality. Remarkably, open data science is democratizing analytics. In fact, statistics show the expansion firsthand.

Data Science 40

Data Science Python Machine Learning Machine Learning 40

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

Analytics Analytics Data Analyst Data Science 52

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

Data Lakes Data Warehouse Database Big Data 98

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

Power BI Data Warehouse ETL Data Preparation 52

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

Azure SQL Database Python 52

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

Analytics Analytics Data Analyst Machine Learning 111

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.

Machine Learning 52

Machine Learning Machine Learning ETL ML 52

AWS Machine Learning Blog

SEPTEMBER 18, 2024

An example direct acyclic graph (DAG) might automate data ingestion, processing, model training, and deployment tasks, ensuring that each step is run in the correct order and at the right time. Though it’s worth mentioning that Airflow isn’t used at runtime as is usual for extract, transform, and load (ETL) tasks.

AWS 118

AWS Machine Learning Machine Learning ML 118

IBM Journey to AI blog

SEPTEMBER 25, 2023

Every day, millions of riders use the Uber app, unwittingly contributing to a complex web of data-driven decisions. This blog takes you on a journey into the world of Uber’s analytics and the critical role that Presto, the open source SQL query engine, plays in driving their success. What is Presto?

Data Lakes 102

Data Lakes Analytics Analytics Clustering 102

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.

Data Warehouse 52

Data Warehouse ETL Tableau Cloud Data 52

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

SQL Database ETL Data Models 52