Remove Database-centric Remove Pipeline-centric Remove Relational Database
article thumbnail

Data Engineering Weekly #186

Data Engineering Weekly

Take Astro (the fully managed Airflow solution) for a test drive today and unlock a suite of features designed to simplify, optimize, and scale your data pipelines. The author writes an overview of the performance implication of disaggregated systems compared to traditional monolithic databases.

article thumbnail

The Rise of Unstructured Data

Cloudera

Structured data can be defined as data that can be stored in relational databases, and unstructured data as everything else. Related to the neglect of data quality, it has been observed that much of the efforts in AI have been model-centric, that is, mostly devoted to developing and improving models , given fixed data sets.

Insiders

Sign Up for our Newsletter

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

article thumbnail

How to Become an Azure Data Engineer? 2023 Roadmap

Knowledge Hut

The demand for data-related professions, including data engineering, has indeed been on the rise due to the increasing importance of data-driven decision-making in various industries. Becoming an Azure Data Engineer in this data-centric landscape is a promising career choice. Learn how to process and analyze large datasets efficiently.

article thumbnail

Toward a Data Mesh (part 2) : Architecture & Technologies

François Nguyen

To illustrate that, let’s take Cloud SQL from the Google Cloud Platform that is a “Fully managed relational database service for MySQL, PostgreSQL, and SQL Server” It looks like this when you want to create an instance. You are starting to be an operation or technology centric data team.

article thumbnail

Building a Scalable Search Architecture

Confluent

As the databases professor at my university used to say, it depends. Using SQL to run your search might be enough for your use case, but as your project requirements grow and more advanced features are needed—for example, enabling synonyms, multilingual search, or even machine learning—your relational database might not be enough.

article thumbnail

97 things every data engineer should know

Grouparoo

This provided a nice overview of the breadth of topics that are relevant to data engineering including data warehouses/lakes, pipelines, metadata, security, compliance, quality, and working with other teams. 7 Be Intentional About the Batching Model in Your Data Pipelines Different batching models. Test system with A/A test.

article thumbnail

Azure Synapse vs Databricks: 2023 Comparison Guide

Knowledge Hut

It offers a wide range of services, including computing, storage, databases, machine learning, and analytics, making it a versatile choice for businesses looking to harness the power of the cloud. This cloud-centric approach ensures scalability, flexibility, and cost-efficiency for your data workloads.