ProjectPro

AUGUST 11, 2021

“Data Lake vs Data Warehouse = Load First, Think Later vs Think First, Load Later” The terms data lake and data warehouse are frequently stumbled upon when it comes to storing large volumes of data. Data Warehouse Architecture What is a Data lake?

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

Data Engineering Podcast

MAY 22, 2022

Signup for the SaaS product at dataengineeringpodcast.com/acryl RudderStack helps you build a customer data platform on your warehouse or data lake. Their SDKs make event streaming from any app or website easy, and their state-of-the-art reverse ETL pipelines enable you to send enriched data to any cloud tool.

Machine Learning 130

Machine Learning Data Engineering Data Engineer Cloud 130

Towards Data Science

FEBRUARY 9, 2024

In truth, the synergy between batch and streaming pipelines is essential for tackling the diverse challenges posed to your data platform at scale. The key to seamlessly addressing these challenges lies, unsurprisingly, in data orchestration. This metadata is then utilized to manage, monitor, and foster the growth of the platform.

Building 79

Building Transportation Data Lake Metadata 79

François Nguyen

MARCH 22, 2021

TL;DR After setting up and organizing the teams, we are describing 4 topics to make data mesh a reality. With this 3rd platform generation, you have more real time data analytics and a cost reduction because it is easier to manage this infrastructure in the cloud thanks to managed services. What you have to code is this workflow !

Technology 130

Technology Architecture Google Cloud Metadata 130

Data Engineering Podcast

NOVEMBER 20, 2022

RudderStack helps you build a customer data platform on your warehouse or data lake. Instead of trapping data in a black box, they enable you to easily collect customer data from the entire stack and build an identity graph on your warehouse, giving you full visibility and control.

Data Lake 130

Data Lake Data Ingestion MongoDB Scala 130

Data Engineering Podcast

AUGUST 21, 2022

Atlan is the metadata hub for your data ecosystem. Instead of locking your metadata into a new silo, unleash its transformative potential with Atlan’s active metadata capabilities. RudderStack helps you build a customer data platform on your warehouse or data lake.

Metadata 100

Metadata MongoDB MySQL Data Lake 100

Snowflake

AUGUST 31, 2023

Catalog Integration: Our newly developed Catalog Integration feature allows you to seamlessly plug Snowflake into other Iceberg catalogs tracking table metadata. Since 2021, Snowflake has had External Tables for the purpose of read-only querying external data lakes.

Metadata 85

Metadata AWS Data Lake Datasets 85

Data Engineering Podcast

AUGUST 28, 2022

Atlan is the metadata hub for your data ecosystem. Instead of locking your metadata into a new silo, unleash its transformative potential with Atlan’s active metadata capabilities. RudderStack helps you build a customer data platform on your warehouse or data lake.

Data Engineering 100

Data Engineering Data Engineer MongoDB Metadata 100

ProjectPro

FEBRUARY 8, 2023

It offers a simple and efficient solution for data processing in organizations. It offers users a data integration tool that organizes data from many sources, formats it, and stores it in a single repository, such as data lakes, data warehouses, etc., where it can be used to facilitate business decisions.

AWS 98

AWS Scala Metadata Data Lake 98

Data Engineering Podcast

MARCH 27, 2022

Signup for the SaaS product at dataengineeringpodcast.com/acryl RudderStack helps you build a customer data platform on your warehouse or data lake. Their SDKs make event streaming from any app or website easy, and their state-of-the-art reverse ETL pipelines enable you to send enriched data to any cloud tool.

Data Governance 130

Data Governance Government Cloud Building 130

Ascend.io

APRIL 22, 2024

This initiative is more than just an upgrade; it’s a reimagining of what a Data Automation Platform can be: dynamic, extensible, and highly intelligent. A unified platform that combines a powerful metadata core, an extensible plugin architecture, DataAware automation, and multiple AI Assistants.

Project 52

Project Metadata Data Pipeline Data Engineering 52

Data Engineering Podcast

FEBRUARY 27, 2022

Visit them today at dataengineeringpodcast.com/timescale RudderStack helps you build a customer data platform on your warehouse or data lake. Their SDKs make event streaming from any app or website easy, and their state-of-the-art reverse ETL pipelines enable you to send enriched data to any cloud tool.

Designing 100

Designing Metadata Data Lake Relational Database 100

Data Engineering Podcast

SEPTEMBER 4, 2022

Atlan is the metadata hub for your data ecosystem. Instead of locking your metadata into a new silo, unleash its transformative potential with Atlan’s active metadata capabilities. RudderStack helps you build a customer data platform on your warehouse or data lake.

IT 100

IT Metadata MongoDB MySQL 100

Precisely

JANUARY 25, 2024

There are three potential approaches to mainframe modernization: Data Replication creates a duplicate copy of mainframe data in a cloud data warehouse or data lake, enabling high-performance analytics virtually in real time, without negatively impacting mainframe performance. Best Practice 2. Best Practice 3.

Metadata 67

Metadata Data Governance Relational Database Government 67

Data Engineering Podcast

APRIL 24, 2022

Signup for the SaaS product at dataengineeringpodcast.com/acryl RudderStack helps you build a customer data platform on your warehouse or data lake. Their SDKs make event streaming from any app or website easy, and their state-of-the-art reverse ETL pipelines enable you to send enriched data to any cloud tool.

Machine Learning 100

Machine Learning Systems Data Lake Metadata 100

Cloudera

JUNE 16, 2022

The DevOps/app dev team wants to know how data flows between such entities and understand the key performance metrics (KPMs) of these entities. For governance and security teams, the questions revolve around chain of custody, audit, metadata, access control, and lineage.

Kafka 86

Kafka Manufacturing Data Lake SQL 86

AltexSoft

AUGUST 22, 2022

A data fabric is an architecture design presented as an integration and orchestration layer built on top of multiple disjointed data sources like relational databases , data warehouses , data lakes, data marts , IoT , legacy systems, etc., to provide a unified view of all enterprise data.

Architecture 52

Architecture Metadata Data Lake Machine Learning 52

Silectis

FEBRUARY 3, 2021

Below we’ll cover the basics of data lineage, why it is important, and how Magpie enables teams to trust their data with this important new release. What is Data Lineage? Data lineage refers to the entire lifecycle of a dataset from its sources of origin all the way to its current state.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Rockset

APRIL 26, 2023

Offline feature store : Detecting anomalies requires historical data in order to have a baseline for comparisons. This data tends to be slow changing and is stored in an offline feature store. This could be a cloud data warehouse, a data lake, or a database. The database has two primary jobs.

Architecture 52

Architecture Transportation Data Lake Insurance 52

Workfall

JUNE 12, 2023

Moreover, it facilitates the implementation of microservices architectures and event-driven systems, automating reactions to data changes without manual intervention. It captures incremental changes from transactional databases or other sources, efficiently loading them into data warehouses or data lakes.

Telecommunication 80

Telecommunication Metadata Healthcare Finance 80

Monte Carlo

MAY 18, 2023

We’ve been open about this work, providing very technical deep dives into how we developed column-level lineage and even some of our failures in building Spark data lineage for data lakes. The Spark data lake lineage example is helpful for context here. These features make it useful for managing data lineage.

Metadata 64

Metadata Data Lake Government Data Governance 64

Cloudera

SEPTEMBER 23, 2020

Access audits are mastered centrally in Apache Ranger which provides comprehensive non-repudiable audit log for every access event to every resource with rich access event metadata such as: IP. Both fine-grained access control of database objects and access to metadata is provided. Sensitive data identification.

Database 82

Database Data Lake Metadata Java 82

Cloudera

OCTOBER 7, 2021

Those decentralization efforts appeared under different monikers through time, e.g., data marts versus data warehousing implementations (a popular architectural debate in the era of structured data) then enterprise-wide data lakes versus smaller, typically BU-Specific, “data ponds”.

Architecture 124

Architecture Metadata Government Kafka 124

Data Engineering Podcast

MARCH 22, 2021

It builds your customer data warehouse and your identity graph on your data warehouse, with support for Snowflake, Google BigQuery, Amazon Redshift, and more. Their SDKs and plugins make event streaming easy, and their integrations with cloud applications like Salesforce and ZenDesk help you go beyond event streaming.

Data Warehouse 100

Data Warehouse Metadata Data Lake Hadoop 100

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. For example, grouping the ones about metadata, discoverability, and column naming might have made a lot of sense.

Data Engineering 52

Data Engineering Data Engineer Engineering Pipeline-centric 52

AltexSoft

SEPTEMBER 23, 2021

One of the innovative ways to address this problem is to build a data hub — a platform that unites all your information sources under a single umbrella. This article explains the main concepts of a data hub, its architecture, and how it differs from data warehouses and data lakes. What is Data Hub?

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

Cloudera

JANUARY 21, 2021

With CDW, as an integrated service of CDP, your line of business gets immediate resources needed for faster application launches and expedited data access, all while protecting the company’s multi-year investment in centralized data management, security, and governance. Proprietary file formats mean no one else is invited in!

IT 93

IT Data Lake Data Warehouse Cloud Storage 93

Data Engineering Podcast

AUGUST 6, 2022

RudderStack helps you build a customer data platform on your warehouse or data lake. Instead of trapping data in a black box, they enable you to easily collect customer data from the entire stack and build an identity graph on your warehouse, giving you full visibility and control.

Machine Learning 100

Machine Learning Database MySQL PostgreSQL 100

Data Engineering Weekly

DECEMBER 4, 2022

The article highlights the challenges of maintaining data models in a world where SQL data warehouses are no longer the primary data platform. The author discusses the need for richer metadata to support complex data lineage and evolving privacy requirements.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Monte Carlo

AUGUST 16, 2022

With Monte Carlo, data engineering teams can proactively manage the health of their data across the entire data stack — including data warehouses, data lakes, BI tools, data orchestration tools, and of course dbt — on a single platform.

Engineering 52

Engineering Data Lake Retail BI 52

Hepta Analytics

FEBRUARY 14, 2022

This week, we got to think about our data ingestion design. We looked at the following: How do we ingest – ETL vs ELT Where do we store the data – Data lake vs data warehouse Which tool to we use to ingest – cronjob vs workflow engine NOTE : This weeks task requires good internet speed and good compute.

Data Ingestion 52

Data Ingestion Data Engineering Data Engineer Engineering 52

Cloudera

SEPTEMBER 15, 2022

July brings summer vacations, holiday gatherings, and for the first time in two years, the return of the Massachusetts Institute of Technology (MIT) Chief Data Officer symposium as an in-person event. A key area of focus for the symposium this year was the design and deployment of modern data platforms.

Data Lake 81

Data Lake Analytics Application Cloud Storage Architecture 81

Data Engineering Weekly

JANUARY 15, 2023

SiliconANGLE theCUBE: Analyst Predictions 2023 - The Future of Data Management By far one of the best analyses of trends in Data Management. 2023 predictions from the panel are; Unified metadata becomes kingmaker. The author walked through various strategies, from sync to async job submission and batch job submission strategy.

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

Netflix Tech

MARCH 7, 2024

Data: Fast Data Our main data lake is hosted on S3, organized as Apache Iceberg tables. For ETL and other heavy lifting of data, we mainly rely on Apache Spark. Explainer flow is event-triggered by an upstream flow, such Model A, B, C flows in the illustration. ETL workflows), as well as downstream (e.g.

Systems 90

Systems Media Machine Learning Data Warehouse 90

AltexSoft

MARCH 14, 2023

Built around a cloud data warehouse, data lake, or data lakehouse. Modern data stack tools are designed to integrate seamlessly with cloud data warehouses such as Redshift, Bigquery, and Snowflake, as well as data lakes or even the child of the first two — a data lakehouse.

IT 59

IT Data Warehouse Data Governance Data Lake 59

Snowflake

MARCH 29, 2023

When using a compute engine external to Snowflake, Snowflake compute is not required to read the data. After making an initial connection to Snowflake via the Iceberg Catalog SDK, Spark can read Iceberg metadata and Parquet files directly from the customer-managed storage account. © 2023 Snowflake Inc. All rights reserved.

Metadata 96

Metadata Scala Hadoop Relational Database 96

Monte Carlo

AUGUST 10, 2023

Data lineage provides the answer by telling you which upstream sources and downstream ingestors were impacted, as well as which teams are generating the data and who is accessing it. At its core, there are three pillars of observability data : Metrics refer to a numeric representation of data measured over time.

Data Pipeline 98

Data Pipeline Software Engineer Software Engineering Machine Learning 98