Data Engineering Podcast

MAY 29, 2022

What are some of the capabilities that it offers to reduce the need to incorporate multiple data stores for application and analytical architectures? What are some of the capabilities that it offers to reduce the need to incorporate multiple data stores for application and analytical architectures?

Architecture 100

Architecture Database Data Architecture PostgreSQL 100

Teradata

OCTOBER 26, 2020

Identify the true capabilities of a modern analytics architecture and achieve what really matters: answers. Find out more.

Analytics Architecture 59

Analytics Architecture Cloud Architecture 59

DataKitchen

AUGUST 19, 2021

Data mesh is a powerful design pattern that leading enterprises are using to organize their enterprise analytics architectures. DataOps keeps inter-domain tasks flowing so that the domain team can progress at their optimal speed. In our next post, we will look at tools capabilities essential for building a successful data mesh.

Pharmaceutical 98

Pharmaceutical Data Lake Data Warehouse Raw Data 98

Towards Data Science

JANUARY 16, 2024

This builds my case to justify the existence of the decentralised data architecture popularly known as the Data Mesh. Data Mesh is a type of analytical architecture but most importantly an operating model that shifts the ownership of analytical data to teams that most intimately know and own the data — the data producers and consumers.

Data Warehouse 63

Data Warehouse Data Architecture Relational Database NoSQL 63

Monte Carlo

FEBRUARY 9, 2022

“[Insights is] a new and powerful way to understand what data assets matter most to our business and how we can better drive an impact with our data across the organization,” s aid Valerie Rogoff , Director of Data Analytics Architecture at ShopRunner.

Raw Data 52

Raw Data Analytics Architecture Data Data Analytics 52

Knowledge Hut

JUNE 23, 2023

Real-time data analytics is an essential innovation that enables companies to act quickly on data. This demonstrates the rising significance of real-time analytics architecture in the hectic corporate climate of today. Analytics will continue to allow more adaptable and real-time decision-making in 2023.

Data Analytics 52

Data Analytics IT Transportation Analytics Architecture 52

Towards Data Science

MAY 22, 2023

Markus Stadi is a Senior Cloud Data Engineer at Dehn SE working in the field of Data Engineering, Data Science and Data Analytics for many years. Lukas Berle is a Data Architect at TeamBank AG specialized in the design and implementation of robust data analytics architectures.

Data Engineer 89

Data Engineer Data Engineering Engineering Data Science 89

Data Engineering Weekly

NOVEMBER 13, 2022

link] Uber: Uber Freight Near-Real-Time Analytics Architecture Uber writes about its Uber Fright architecture highlighting how it archives data freshness, latency, reliability, and accuracy.

Data Engineer 52

Data Engineer Data Engineering Engineering Kafka 52

ThoughtSpot

JUNE 24, 2024

This entire experience can only come together the way it has with the right analytics architecture, semantic engine, and consumer UX. With the same AI-powered ThoughtSpot features you love, like NLQ and SpotIQ, embedded in your application, you can deliver on this massive wave of opportunity created by GenAI.

BI 59

BI Analytics Architecture SQL Cloud 59

Rockset

JULY 8, 2021

Shrey Batra comes from LinkedIn and Innovaccer, two companies with particularly data-intensive products, so I'm really interested to hear what type of real-time analytics architectures he's had experience with that employ MongoDB Change Streams. release.

MongoDB 40

MongoDB Manufacturing Analytics Architecture Architecture 40

Striim

AUGUST 22, 2024

Real-Time Analytics Architecture When implementing real-time analytics, you’ll need a different architecture and approach than you would with traditional batch-based data analytics. The streaming and processing of large volumes of data will also require a unique set of technologies.

Data Warehouse 52

Data Warehouse Retail Machine Learning Database 52

Rockset

MARCH 19, 2020

In this post, I’ll discuss some common real-time analytics use-cases that we have seen with our customers here at Rockset and how different real-time analytics architectures suit each of them. Like any other technology, Kafka can be extremely powerful when used correctly and extremely clumsy when not.

Kafka 40

Kafka Database Process SQL 40

ArcGIS

JUNE 21, 2023

Check out exciting sessions, special interest groups and activities on BIM, CAD, and GIS integrations featured at Esri UC 2023.

Analytics Architecture 98

Analytics Architecture Designing Architecture Engineering 98

ArcGIS

NOVEMBER 8, 2023

Surfaces in a centralized location

Datasets 69

Datasets Analytics Architecture Data Management Architecture 69

ArcGIS

NOVEMBER 8, 2023

Terrain datasets as ground—Create scenes in ArcGIS Pro and publish to ArcGIS Online

Datasets 69

Datasets Analytics Architecture Data Management Architecture 69

ArcGIS

NOVEMBER 8, 2023

Surface modeling across Autodesk Civil 3D and ArcGIS Pro 3.2 using newly supported feature classes

Analytics Architecture 69

Analytics Architecture Datasets Data Management Architecture 69

Edureka

FEBRUARY 7, 2023

Azure Synapse is a boundless analytics service that combines enterprise data warehousing and Big Data analytics. 7) Describe the Azure Synapse Analytics architecture. Users are given the choice to query data on specific terms for using either serverless on-demand or scale-out provisioned resources.

Data Engineer 52

Data Engineer Data Engineering Engineering Hadoop 52

ArcGIS

MAY 22, 2024

Defining the Topography feature class as current ground to visualize underground Autodesk Civil 3D components.

Designing 59

Designing Analytics Architecture Architecture Engineering 59

ArcGIS

MAY 22, 2024

Defining the Topography feature class as current ground to visualize underground Autodesk Civil 3D components.

Designing 59

Designing Analytics Architecture Architecture Engineering 59

Knowledge Hut

FEBRUARY 27, 2023

Some of the most common responsibilities of data engineers include Data collection Matching the architecture to the business his needs Discovering tasks that can be automated using data Using advanced analytics programs, machine learning, and statistical techniques Updating stakeholders based on analytics Architecture development, building, testing, (..)

Data Engineer 52

Data Engineer Data Engineering Database-centric Pipeline-centric 52

Monte Carlo

JULY 25, 2022

But one thing’s for sure: if you can’t trust the data powering your analytics architecture, it’s hard to justify the investment. There’s a lot of content out there about why a data mesh is (or isn’t) the best thing since sliced bread.

Government 52

Government Data Architecture Insurance 52

Monte Carlo

MAY 17, 2023

. “That’s the beauty of Monte Carlo because it allows us to see who is using data and where it is being consumed,” said Valerie Rogoff, former director of analytics architecture, ShopRunner. ” 36.

Data 52

Data Data Pipeline Data Engineer Data Engineering 52

Monte Carlo

MAY 17, 2023

. “That’s the beauty of Monte Carlo because it allows us to see who is using data and where it is being consumed,” said Valerie Rogoff, former director of analytics architecture, ShopRunner. ” 36.

Data Pipeline 52

Data Pipeline Data Engineer Data Engineering Data 52