KDnuggets

NOVEMBER 23, 2021

Also: How I Redesigned over 100 ETL into ELT Data Pipelines; Where NLP is heading; Don’t Waste Time Building Your Data Science Network; Data Scientists: How to Sell Your Project and Yourself.

Data Science 209

Data Science ETL Data Pipeline Data Scientist 209

KDnuggets

NOVEMBER 17, 2021

Don’t Waste Time Building Your Data Science Network; 19 Data Science Project Ideas for Beginners; How I Redesigned over 100 ETL into ELT Data Pipelines; Anecdotes from 11 Role Models in Machine Learning; The Ultimate Guide To Different Word Embedding Techniques In NLP.

Data Science 162

Data Science ETL Data Pipeline Machine Learning 162

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

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

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. Automation Automating data pipelines and models ➡️ 6. Team Building the right data science team is complex.

Data Science 130

Data Science Data Scientist ML ML 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. Airflow: Apache Airflow is an open-source platform for orchestrating and scheduling data pipelines.

Data Engineering 195

Data Engineering Data Engineer Data Engineering Data Engineering 195

Data Science Dojo

MARCH 15, 2023

Data Science Dojo is offering Meltano CLI for FREE on Azure Marketplace preconfigured with Meltano, a platform that provides flexibility and scalability. Not to worry as Data Science Dojo’s Meltano CLI instance fixes all of that. Meltano CLI stands out as a data engineering tool. What Data Science Dojo has for you?

Azure 195

Azure Data Science Data Engineering Data Engineer 195

Data Science Dojo

FEBRUARY 20, 2023

Best tools and platforms for MLOPs – Data Science Dojo Google Cloud Platform Google Cloud Platform is a comprehensive offering of cloud computing services. Google Cloud Platform is a great option for businesses that need high-performance computing, such as data science, AI, machine learning, and financial services.

Machine Learning 195

Machine Learning Machine Learning AWS Azure 195

Pickl AI

JULY 8, 2024

Summary: This blog explains how to build efficient data pipelines, detailing each step from data collection to final delivery. Introduction Data pipelines play a pivotal role in modern data architecture by seamlessly transporting and transforming raw data into valuable insights.

Data Pipeline 52

Data Pipeline Data Quality Database Apache Kafka 52

IBM Data Science in Practice

DECEMBER 7, 2022

One of the key elements that builds a data fabric architecture is to weave integrated data from many different sources, transform and enrich data, and deliver it to downstream data consumers. As a part of data pipeline, Address Verification Interface (AVI) can remediate bad address data.

Data Pipeline 130

Data Pipeline Data Quality Data Preparation ETL 130

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

Data Science Blog

FEBRUARY 4, 2023

The fusion of data in a central platform enables smooth analysis to optimize processes and increase business efficiency in the world of Industry 4.0 using methods from business intelligence , process mining and data science. Cloud Data Platform for shopfloor management and data sources such like MES, ERP, PLM and machine data.

Cloud Data 147

Cloud Data Data Science Business Intelligence Business Intelligence 147

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 SQL Data Quality 52

Pickl AI

OCTOBER 15, 2024

Summary: Selecting the right ETL platform is vital for efficient data integration. Consider your business needs, compare features, and evaluate costs to enhance data accuracy and operational efficiency. Introduction In today’s data-driven world, businesses rely heavily on ETL platforms to streamline data integration processes.

ETL 52

ETL Azure AWS Data Governance 52

ODSC - Open Data Science

FEBRUARY 19, 2025

In the world of AI-driven data workflows, Brij Kishore Pandey, a Principal Engineer at ADP and a respected LinkedIn influencer, is at the forefront of integrating multi-agent systems with Generative AI for ETL pipeline orchestration. ETL ProcessBasics So what exactly is ETL? What is an Agent?

ETL 52

ETL AI AI Data Warehouse 52

Towards AI

MARCH 21, 2023

Last Updated on March 21, 2023 by Editorial Team Author(s): Data Science meets Cyber Security Originally published on Towards AI. Navigating the World of Data Engineering: A Beginner’s Guide. A GLIMPSE OF DATA ENGINEERING ❤ IMAGE SOURCE: BY AUTHOR Data or data? What are ETL and data pipelines?

Data Engineering 98

Data Engineering Data Engineer Data Engineering Data Engineering 98

IBM Data Science in Practice

NOVEMBER 28, 2022

Implementing a data fabric architecture is the answer. What is a data fabric? Data fabric is defined by IBM as “an architecture that facilitates the end-to-end integration of various data pipelines and cloud environments through the use of intelligent and automated systems.”

Data Pipeline 130

Data Pipeline Data Quality Data Preparation Data Governance 130

ODSC - Open Data Science

OCTOBER 18, 2024

The advent of big data, affordable computing power, and advanced machine learning algorithms has fueled explosive growth in data science across industries. However, research shows that up to 85% of data science projects fail to move beyond proofs of concept to full-scale deployment.

Data Science 52

Data Science Data Scientist Analytics Analytics 52

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

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. Read more to know.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

ODSC - Open Data Science

JANUARY 18, 2024

This individual is responsible for building and maintaining the infrastructure that stores and processes data; the kinds of data can be diverse, but most commonly it will be structured and unstructured data. They’ll also work with software engineers to ensure that the data infrastructure is scalable and reliable.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Smart Data Collective

SEPTEMBER 19, 2022

To ensure their customers have a satisfactory experience, financial businesses will use big data analytics to tweak their services across various platforms to suit a customer’s needs. They will also use historical and real-time data to identify possible customer challenges. How Can Big Data In Fintech Influence The Customer Experience?

Big Data 145

Big Data Big Data Big Data Analytics Big Data Analytics 145

Heartbeat

NOVEMBER 6, 2023

Image Source —  Pixel Production Inc In the previous article, you were introduced to the intricacies of data pipelines, including the two major types of existing data pipelines. You might be curious how a simple tool like Apache Airflow can be powerful for managing complex data pipelines.

Data Pipeline 52

Data Pipeline Clean Data ETL Python 52

AWS Machine Learning Blog

MARCH 1, 2023

To solve this problem, we had to design a strong data pipeline to create the ML features from the raw data and MLOps. Multiple data sources ODIN is an MMORPG where the game players interact with each other, and there are various events such as level-up, item purchase, and gold (game money) hunting.

AWS 97

AWS ML ML ETL 97

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

ODSC - Open Data Science

JUNE 19, 2023

However, it can be the OS that runs powerful embedded systems capable of collecting, governing, and managing huge amounts of data and running advanced analytics. When it comes to data integration, RTOS can work with systems that employ data warehousing, API management, and ETL technologies.

Big Data 96

Big Data Big Data Artificial Intelligence Artificial Intelligence 96

Pickl AI

NOVEMBER 4, 2024

Effective data governance enhances quality and security throughout the data lifecycle. What is Data Engineering? Data Engineering is designing, constructing, and managing systems that enable data collection, storage, and analysis. ETL is vital for ensuring data quality and integrity.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Kaggle

JULY 29, 2020

In August 2019, Data Works was acquired and Dave worked to ensure a successful transition. David: My technical background is in ETL, data extraction, data engineering and data analytics. An ETL process was built to take the CSV, find the corresponding text articles and load the data into a SQLite database.

ETL 71

ETL Data Scientist Machine Learning Machine Learning 71

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?

Data Warehouse 52

Data Warehouse Data Pipeline Cloud Data ETL 52

Smart Data Collective

OCTOBER 17, 2022

Cloud data warehouses provide various advantages, including the ability to be more scalable and elastic than conventional warehouses. Can’t get to the data. All of this data might be overwhelming for engineers who struggle to pull in data sets quickly enough. Data pipeline maintenance.

Big Data 119

Big Data Big Data Data Engineering Data Engineer 119

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

ODSC - Open Data Science

APRIL 4, 2024

There are many factors, but here, we’d like to hone in on the activities that a data science team engages in. Find out how to weave data reliability and quality checks into the execution of your data pipelines and more. Register now before tickets sell out! Learn more about them here!

Data Visualization 52

Data Visualization Analytics Analytics Big Data Analytics 52

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.

Data Lakes 52

Data Lakes Clustering Big Data Big Data 52

Dataconomy

FEBRUARY 23, 2023

This involves creating data validation rules, monitoring data quality, and implementing processes to correct any errors that are identified. Creating data pipelines and workflows Data engineers create data pipelines and workflows that enable data to be collected, processed, and analyzed efficiently.

Big Data 91

Big Data Big Data Data Engineering Data Engineer 91

phData

JANUARY 5, 2023

Connecting Snowflake to Python can be a game changer for your data services. Python can be used to migrate your data from a previous platform to Snowflake , create or manage data pipelines for Extract, Transform, and Load (ETL) processes, perform data science tasks such as machine learning or create data analysis visualizations.

Python 52

Python Data Engineering Data Engineer Data Engineering 52

DagsHub

APRIL 7, 2024

Image generated with Midjourney In today’s fast-paced world of data science, building impactful machine learning models relies on much more than selecting the best algorithm for the job. Data scientists and machine learning engineers need to collaborate to make sure that together with the model, they develop robust data pipelines.

Machine Learning 59

Machine Learning Machine Learning ML ML 59

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

AI AI Machine Learning Machine Learning 74