Knowledge Hut

SEPTEMBER 26, 2023

Key Features of Azure Synapse Here are some of the key features of Azure Synapse: Cloud Data Service: Azure Synapse operates as a cloud-native service, residing within the Microsoft Azure cloud ecosystem. This cloud-centric approach ensures scalability, flexibility, and cost-efficiency for your data workloads.

Data Lake 52

Data Lake Database-centric Pipeline-centric Machine Learning 52

Grouparoo

OCTOBER 6, 2021

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. Open question: how to seed data in a staging environment? Test system with A/A test. Be adaptable.

Data Engineering 52

Data Engineering Data Engineer Engineering Pipeline-centric 52

DataKitchen

AUGUST 27, 2021

Without DataOps, companies can employ hundreds of data professionals and still struggle. The data pipelines must contend with a high level of complexity – over seventy data sources and a variety of cadences, including daily/weekly updates and builds. The DataOps Platform does not replace a data lake or the data hub.

Pharmaceutical 98

Pharmaceutical Pipeline-centric Data Lake Data Analytics 98

RandomTrees

NOVEMBER 29, 2023

So, a data vault model forms the core for a data vault approach and is a data modeling design pattern used to build a data warehouse for organizations adopting enterprise-scalable analytics as and for its solutions. The data from many data bases are sent to the data warehouse through the ETL processes.

Data Warehouse 52

Data Warehouse Data Lake Database-centric Data Cleanse 52

Knowledge Hut

JULY 3, 2023

Real-time Data ingestion performs the utilization of data from various origins, does the data cleaning, validation, and preprocessing operations and at the end store it in the required format, either structured or unstructured. As real-time insights gain popularity, real-time data ingestion remains vital for companies worldwide.

Data Ingestion 52

Data Ingestion Pipeline-centric Google Cloud Media 52

Ascend.io

SEPTEMBER 14, 2023

Data engineers can find one for almost any need, from data extraction to complex transformations, ensuring that they’re not reinventing the wheel by writing code that’s already been written. compute() Data Storage Python extends its mastery to data storage, boasting smooth integrations with both SQL and NoSQL databases.

Data Engineering 52

Data Engineering Data Engineer Python Engineering 52

Monte Carlo

JULY 15, 2021

As data pipelines become increasingly complex, investing in a data quality solution is becoming an increasingly important priority for modern data teams. There are 4 key challenges, opportunities, and trade-offs when considering building or buying a data observability or data quality solution.

Building 40

Building Pipeline-centric Data Engineering Data Engineer 40