Data Engineering Podcast

JANUARY 21, 2024

Summary Databases and analytics architectures have gone through several generational shifts. A substantial amount of the data that is being managed in these systems is related to customers and their interactions with an organization. How has that changed the architectural approach to CDPs?

Data Lake 147

Data Lake High Quality Data NoSQL Data Warehouse 147

Data Engineering Podcast

AUGUST 21, 2022

Select Star’s data discovery platform solves that out of the box, with an automated catalog that includes lineage from where the data originated, all the way to which dashboards rely on it and who is viewing them every day. Can you describe what is driving the adoption of real-time analytics?

Lambda Architecture 100

Lambda Architecture MongoDB Scala MySQL 100

Striim

AUGUST 22, 2024

Moreover, there are two forms of real-time analytics. These include: On-demand real-time analytics With on-demand real-time analytics, users send a request, such as with an SQL query, to deliver the analytics outcome. It relies on fresh data, but queries are run on an as-needed basis.

Data Warehouse 52

Data Warehouse Retail Machine Learning Database 52

Data Engineering Weekly

NOVEMBER 13, 2022

[link] If you are a modern data leader and interested in adopting Data Contract or talking to understand what it is, say hi on LinkedIn [link] Netflix: New Series - Creating Media with Machine Learning Can ML replace creative content generators, or can it be an excellent assistant to take creativity to a new height? Not Endless DAGs!

Data Engineer 52

Data Engineer Data Engineering Engineering Kafka 52

Edureka

FEBRUARY 7, 2023

Dynamic data masking serves several important functions in data security. It is possible to use Azure SQL Database, Azure SQL Managed Instance and Azure Synapse Analytics. It can be set up as a security policy on all SQL Databases in an Azure subscription. 4) What is Polybase?

Data Engineering 52

Data Engineering Data Engineer Engineering Hadoop 52

Rockset

MARCH 19, 2020

With all of these stream processing and real-time data store options, though, also comes questions for when each should be used and what their pros and cons are. I hope by the end you find yourself better informed and less confused about the real-time analytics landscape and are ready to dive in to it for yourself.

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Kafka Database Process SQL 40

Knowledge Hut

FEBRUARY 27, 2023

Engineers work with Data Scientists to help make the most of the data they collect and have deep knowledge of distributed systems and computer science. In large organizations, data engineers concentrate on analytical databases, operate data warehouses that span multiple databases, and are responsible for developing table schemas.

Data Engineer 52

Data Engineer Data Engineering Database-centric Pipeline-centric 52