Rockset

JANUARY 3, 2023

This blog compiles real-time data predictions from industry leaders so you know what’s coming in 2023. Confluent’s State of Data in Motion Report found that 97% of companies around the world are using streaming data, making it central to the data landscape.

Data Warehouse 52

Data Warehouse Education Database Data 52

ProjectPro

JUNE 18, 2021

Why do data scientists prefer Python over Java? Java vs Python for Data Science- Which is better? These are the most common questions that our ProjectAdvisors get asked a lot from beginners getting started with a data science career. Why do data scientists love Python for Data Science?

Java 52

Java Data Science Python Programming Language 52

Snowflake

FEBRUARY 6, 2023

Some seek new methods to get to the top, hence the rise of ski touring or “uphill skiing.” The mantra is “earn your turns.” Now think of the growing demand for data and insights. Data mesh offers an answer in four principles The data mesh paradigm set out to solve some of these issues.

Government 64

Government Data Data Pipeline Architecture 64

Snowflake

JUNE 22, 2023

Talk of data products has taken the data world by storm. It’s the use of data that delivers value. Data as a product puts that into practice. We often hear the term “data products” as one of the four pillars of a data mesh. The data mesh paradigm embraces the principle of data as a product.

Building 52

Building Business Analyst Aggregated Data Data 52

dbt Developer Hub

MARCH 1, 2022

In this article, I will walk through forming the first analytics engineering team at Smartsheet including how momentum built around forming the team, the challenges we faced, and the solutions we developed within the first year. How does an AE team even start? Strong data engineering and data analytics teams.

Engineering 52

Engineering Database Database Design Raw Data 52

Snowflake

NOVEMBER 2, 2023

Over the years, the technology landscape for data management has given rise to various architecture patterns, each thoughtfully designed to cater to specific use cases and requirements. These patterns include both centralized storage patterns like data warehouse , data lake and data lakehouse , and distributed patterns such as data mesh.

Data Lake 88

Data Lake Data Warehouse Cloud Unstructured Data 88

DataKitchen

NOVEMBER 29, 2021

Many in the data industry recognize the serious impact of AI bias and seek to take active steps to mitigate it. Many in the data industry recognize the serious impact of AI bias and seek to take active steps to mitigate it. With data and tools increasingly in the cloud, data organizations are finding ways to accommodate remote work.

Data Lake 98

Data Lake Manufacturing Architecture Data Architecture 98

DataKitchen

SEPTEMBER 17, 2021

Below is our final post (5 of 5) on combining data mesh with DataOps to foster innovation while addressing the challenges of a data mesh decentralized architecture. We see a DataOps process hub like the DataKitchen Platform playing a central supporting role in successfully implementing a data mesh.

Architecture 94

Architecture Data Architecture Government Raw Data 94

Monte Carlo

NOVEMBER 21, 2022

What’s next for the future of data engineering? Each year, we chat with one of our industry’s pioneering leaders about their predictions for the modern data stack – and share a few of our own. Pro-tip: be sure to check out his talk from IMPACT: The Data Observability Summit.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Rockset

FEBRUARY 24, 2023

Introduction Let’s get this out of the way at the beginning: understanding effective streaming data architectures is hard, and understanding how to make use of streaming data for analytics is really hard. What Is Streaming Data? We’re going to start with a basic question: what is streaming data?

Kafka 52

Kafka AWS Amazon Web Services Programming Language 52

Data Engineering Weekly

NOVEMBER 13, 2022

Data Engineering Weekly Is Brought to You by RudderStack RudderStack provides data pipelines that make it easy to collect data from every application, website, and SaaS platform, then activate it in your warehouse and business tools. I'm a software engineer; how can I transition to a Machine Learning engineer?

Data Engineering 52

Data Engineering Data Engineer Engineering Kafka 52

DataKitchen

JUNE 24, 2021

In May 2021 at the CDO & Data Leaders Global Summit, DataKitchen sat down with the following data leaders to learn how to use DataOps to drive agility and business value. Kurt Zimmer, Head of Data Engineering for Data Enablement at AstraZeneca. Jim Tyo, Chief Data Officer, Invesco. You expect it to work.

Pipeline-centric 84

Pipeline-centric Manufacturing Education Data Cleanse 84

Snowflake

JULY 13, 2023

As we continue to revolutionize the way businesses operate, allowing them to solve their most pressing problems and drive revenue through the Data Cloud, the insights, expertise, and experiences we offer at Summit have continued to grow. Snowflake is democratizing access to data and intelligence with AI and large language models (LLMs).

Entertainment 57

Entertainment Manufacturing Retail Media 57

Cloudera

OCTOBER 11, 2021

Modak, a leading provider of modern data engineering solutions, is now a certified solution partner with Cloudera. Customers can now seamlessly automate migration to Cloudera’s Hybrid Data Platform — Cloudera Data Platform (CDP) to dynamically auto-scale cloud services with Cloudera Data Engineering (CDE) integration with Modak Nabu.

Data Engineering 95

Data Engineering Data Engineer Cloud Engineering 95

Monte Carlo

MAY 17, 2023

Data observability, an organization’s ability to fully understand the health and quality of the data in their systems, has become one of the hottest technologies in modern data engineering. Because the technology is so extensible, there have been a wide array of suggestions–some more grounded than others–for how it can be used.

Data 52

Data Data Pipeline Data Engineering Data Engineer 52

Monte Carlo

MAY 17, 2023

Data observability, an organization’s ability to fully understand the health and quality of the data in their systems, has become one of the hottest technologies in modern data engineering. Because the technology is so extensible, there have been a wide array of suggestions–some more grounded than others–for how it can be used.

Data Pipeline 52

Data Pipeline Data Data Engineering Data Engineer 52

phData: Data Engineering

JULY 18, 2023

The Ultimate Modern Data Stack Migration Guide phData Marketing July 18, 2023 This guide was co-written by a team of data experts, including Dakota Kelley, Ahmad Aburia, Sam Hall, and Sunny Yan. Imagine a world where all of your data is organized, easily accessible, and routinely leveraged to drive impactful outcomes.

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 52