article thumbnail

5 Real-Time Data Processing and Analytics Technologies – And Where You Can Implement Them

Seattle Data Guy

Real-time data can help you do just that. Real-time data processing can satisfy the ever-increasing demand for… Read more The post 5 Real-Time Data Processing and Analytics Technologies – And Where You Can Implement Them appeared first on Seattle Data Guy.

article thumbnail

2. Diving Deeper into Psyberg: Stateless vs Stateful Data Processing

Netflix Tech

By Abhinaya Shetty , Bharath Mummadisetty In the inaugural blog post of this series, we introduced you to the state of our pipelines before Psyberg and the challenges with incremental processing that led us to create the Psyberg framework within Netflix’s Membership and Finance data engineering team.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Type-safe data processing pipelines

Tweag

Moreover, these steps can be combined in different ways, perhaps omitting some or changing the order of others, producing different data processing pipelines tailored to a particular task at hand. Even then, however, GHC will not complain if we write myPipeline = monomorphize. What is the requirement of the composition?

article thumbnail

Simplifying Data Processing with Snowpark

Cloudyard

Read Time: 1 Minute, 42 Second In this blog post, we’ll delve into a practical example that showcases the prowess of Snowpark by processing customer invoice data from a CSV file and handling credit card details from a JSON source. The journey begins with customer invoice data stored in a CSV file.

article thumbnail

John Lewis Partnership Standardizes its Data Processes in Snowflake’s Data Cloud

Snowflake

It needed to unite its data silos to give its customer, trading, and operational teams timely and robust insight to drive informed strategic decisions. Find out why its Chief Data and Insight Officer chose Snowflake as its unifying data platform—and how it’s given the partnership greater control over its data.

article thumbnail

Centralize Your Data Processes With a DataOps Process Hub

DataKitchen

DataOps concerns itself with the complex flow of data across teams, data centers and organizational boundaries. It expands beyond tools and data architecture and views the data organization from the perspective of its processes and workflows. One data engineer called it the “last mile problem.” .

Process 98
article thumbnail

Improving SAP® Master Data Processes with Excel

Precisely

Organizations that run SAP can use Excel-to-SAP automation to do more with less, while also increasing agility and improving their SAP master data management process automation. We bring automation closer to the business users who own the data and the day-to-day processes that drive the business. Check out our free ebook.