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Centralize Your Data Processes With a DataOps Process Hub

DataKitchen

Data organizations often have a mix of centralized and decentralized activity. 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.

Process 98
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What is a Data Mesh?

DataKitchen

The data mesh design pattern breaks giant, monolithic enterprise data architectures into subsystems or domains, each managed by a dedicated team. DataOps helps the data mesh deliver greater business agility by enabling decentralized domains to work in concert. . But first, let’s define the data mesh design pattern.

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Developing Global Labor Market Intelligence at SkyHive Using Rockset and Databricks

Rockset

SkyHive platform Challenges with MongoDB for Analytical Queries 16 TB of raw text data from our web crawlers and other data feeds is dumped daily into our S3 data lake. That data was processed and then loaded into our analytics and serving database, MongoDB.

MongoDB 59
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The Top 25 Data Engineering Influencers and Content Creators on LinkedIn

Databand.ai

Bob also hosts The Engineering Side of Data podcast , which is dedicated to discussions around data engineering and features a variety of guests from the data engineering space. His specialties include Microsoft SQL Server, Azure Databricks, Azure Data Factory, SQL Server Integration Services (SSIS), and Azure Data Lake.

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The Good and the Bad of Databricks Lakehouse Platform

AltexSoft

But what do the gas and oil corporation, the computer software giant, the luxury fashion house, the top outdoor brand, and the multinational pharmaceutical enterprise have in common? The answer is simple: They use the same technology to make the most of data. Databricks lakehouse platform architecture.

Scala 64