Analytics Vidhya

FEBRUARY 17, 2023

Introduction Are you curious about the latest advancements in the data tech industry? In that case, we invite you to check out DataHour, a series of webinars led by experts in the field. Perhaps you’re hoping to advance your career or transition into this field.

Analytics 319

Analytics Analytics Data Pipeline Data Warehouse 319

ODSC - Open Data Science

MAY 10, 2023

Many mistakenly equate tabular data with business intelligence rather than AI, leading to a dismissive attitude toward its sophistication. Standard data science practices could also be contributing to this issue. Making data engineering more systematic through principles and tools will be key to making AI algorithms work.

Data Scientist 87

Data Scientist Data Science Deep Learning Deep Learning 87

IBM Journey to AI blog

NOVEMBER 3, 2023

When you make it easier to work with events, other users like analysts and data engineers can start gaining real-time insights and work with datasets when it matters most. As a result, you reduce the skills barrier and increase your speed of data processing by preventing important information from getting stuck in a data warehouse. .”

Apache Kafka 79

Apache Kafka Data Warehouse Data Pipeline Big Data 79

Alation

JUNE 14, 2023

Every organization wants to better serve its customers, and that goal is often achieved through data. We didn’t have access to hundreds of data engineers out in the marketplace,” Lavorini points out. In the diagram above, the bottom layer of the stream are the data management and governance capabilities.

Data Pipeline 52

Data Pipeline ETL Data Warehouse SQL 52

Snorkel AI

JUNE 22, 2023

So, in those projects, you have more than 70% of the engineering development resources that are tied to data engineering activities. That is a mix of data engineering, feature engineering work, a mix of data transformation work writ large. It is at the level of data quality and joining tasks.

Data Quality 52

Data Quality AI AI ML 52

Pickl AI

SEPTEMBER 5, 2024

Data Preparation: Cleaning, transforming, and preparing data for analysis and modelling. Collaborating with Teams: Working with data engineers, analysts, and stakeholders to ensure data solutions meet business needs.

Azure 52

Azure Data Scientist Machine Learning Machine Learning 52

Alation

DECEMBER 23, 2021

The elf teams used data engineering to improve gift matching and deployed big data to scale the naughty and nice list long ago , before either approach was even considered within our warmer climes. Get the most out of their Snowflake data cloud. Did anyone else catch Frizzle and Sparkle on our joint webinars this quarter?

Data Governance 59

Data Governance Data Pipeline Tableau Big Data 59