Knowledge Hut

NOVEMBER 2, 2023

These Azure data engineer projects provide a wonderful opportunity to enhance your data engineering skills, whether you are a beginner, an intermediate-level engineer, or an advanced practitioner. Who is Azure Data Engineer? Azure SQL Database, Azure Data Lake Storage). Azure SQL Database, Azure Data Lake Storage).

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Ascend.io

DECEMBER 19, 2023

Snowflake’s Data Marketplace : Enriches data pipelines with external data sources, providing access to a diverse range of datasets and services that can be seamlessly integrated into your analytics and data processing workflows. that you can combine to create custom data workflows.

ETL Tools 52

ETL Tools IT Data Pipeline Data Warehouse 52

Monte Carlo

JULY 27, 2023

Collaborate with data engineering and development teams to implement data quality best practices and optimize data workflows. Document data quality issues, testing procedures, and resolutions for future reference and knowledge sharing. Assist in developing and maintaining data governance policies and standards.

Engineering 52

Engineering Healthcare Scala Data Warehouse 52

Databand.ai

DECEMBER 29, 2022

Follow Ravit on LinkedIn 5) Priya Krishnan Head of Product Management, Data and AI at IBM Priya is an innovative, customer-focused, data-driven product executive with over 16 years of experience in global product management, strategy, and GTM roles to commercialize and monetize in-demand enterprise solutions.

BI 52

BI Consulting Data Science Data Governance 52

Cloudera

AUGUST 21, 2020

The governance aspect is perhaps even more important and businesses need to be able to understand where the data comes from. Data lineage, personally identifiable information or PPI and metadata all fall under a broad data governance banner which is critically important in terms of what needs to be protected and mapped out.

Banking 61

Banking Kafka Cloud Storage Government 61

Monte Carlo

JUNE 14, 2023

5 Data pipeline architecture designs and their evolution The Hadoop era , roughly 2011 to 2017, arguably ushered in big data processing capabilities to mainstream organizations. Data then, and even today for some organizations, was primarily hosted in on-premises databases with non-scalable storage.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

DataKitchen

APRIL 13, 2021

Process Analytics. We have also included vendors for the specific use cases of ModelOps, MLOps, DataGovOps and DataSecOps which apply DataOps principles to machine learning, AI, data governance, and data security operations. . Reflow — A system for incremental data processing in the cloud.

Consulting 123

Consulting Machine Learning Data Science Data Pipeline 123

phData: Data Engineering

JANUARY 3, 2022

Data Quality and Validation This is one of the trickiest parts of a DataOps strategy and requires a lot of input from those responsible for data governance. We recommend identifying sync points that align with your information architecture so that data currency expectations are known at a governance level.

IT 52

IT AWS Software Engineer Software Engineering 52

AltexSoft

MARCH 14, 2023

As the volume and complexity of data continue to grow, organizations seek faster, more efficient, and cost-effective ways to manage and analyze data. In recent years, cloud-based data warehouses have revolutionized data processing with their advanced massively parallel processing (MPP) capabilities and SQL support.

IT 59

IT Data Warehouse Data Governance Data Lake 59