AltexSoft

AUGUST 29, 2023

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data. What is a data lake?

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Data Engineering Podcast

NOVEMBER 20, 2022

Datafold integrates with all major data warehouses as well as frameworks such as Airflow & dbt and seamlessly plugs into CI workflows. RudderStack helps you build a customer data platform on your warehouse or data lake. runs natively on data lakes and warehouses and in AWS, Google Cloud and Microsoft Azure.

Data Lake 130

Data Lake Data Ingestion MongoDB MySQL 130

Snowflake

OCTOBER 16, 2024

The company quickly realized maintaining 10 years’ worth of production data while enabling real-time data ingestion led to an unscalable situation that would have necessitated a data lake. Data scientists also benefited from a scalable environment to build machine learning models without fear of system crashes.

Digital Media 102

Digital Media Media Data Lake Data Warehouse 102

Sync Computing

NOVEMBER 7, 2024

While data warehouses are still in use, they are limited in use-cases as they only support structured data. Data lakes add support for semi-structured and unstructured data, and data lakehouses add further flexibility with better governance in a true hybrid solution built from the ground-up.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Unstructured Data 52

Data Engineering Weekly

JULY 7, 2024

Learn More → Notion: Building and scaling Notion’s data lake Notion writes about scaling the data lake by bringing critical data ingestion operations in-house. Hudi seems to be a de facto choice for CDC data lake features.

Data Engineer 98

Data Engineer Data Engineering Engineering Data Lake 98

Hevo

JULY 17, 2024

Every data-centric organization uses a data lake, warehouse, or both data architectures to meet its data needs. Data Lakes bring flexibility and accessibility, whereas warehouses bring structure and performance to the data architecture.

Data Ingestion 52

Data Ingestion Data Lake Data Architecture Architecture 52

Striim

SEPTEMBER 11, 2024

Data pipelines are the backbone of your business’s data architecture. Implementing a robust and scalable pipeline ensures you can effectively manage, analyze, and organize your growing data. Benjamin Kennedy, Cloud Solutions Architect at Striim, emphasizes the outcome-driven nature of data pipelines.

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

Monte Carlo

MARCH 14, 2023

Data ingestion is the process of collecting data from various sources and moving it to your data warehouse or lake for processing and analysis. It is the first step in modern data management workflows. Table of Contents What is Data Ingestion? Decision making would be slower and less accurate.

Data Ingestion 52

Data Ingestion Data Warehouse Lambda Architecture Raw Data 52

Cloudera

APRIL 22, 2021

Apache Ozone is one of the major innovations introduced in CDP, which provides the next generation storage architecture for Big Data applications, where data blocks are organized in storage containers for larger scale and to handle small objects. Lower software licensing and support cost.

Pipeline-centric 101

Pipeline-centric Data Lake Hadoop Big Data 101

Data Engineering Weekly

SEPTEMBER 18, 2024

The Rise of Data Observability Data observability has become increasingly critical as companies seek greater visibility into their data processes. This growing demand has found a natural synergy with the rise of the data lake. As a result, monitoring data in real time was often an afterthought.

Data Lake 98

Data Lake Data Pipeline Unstructured Data Data 98

Monte Carlo

APRIL 24, 2023

Data lakes are useful, flexible data storage repositories that enable many types of data to be stored in its rawest state. Traditionally, after being stored in a data lake, raw data was then often moved to various destinations like a data warehouse for further processing, analysis, and consumption.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

DareData

JULY 5, 2023

Learn how we build data lake infrastructures and help organizations all around the world achieving their data goals. In today's data-driven world, organizations are faced with the challenge of managing and processing large volumes of data efficiently.

Data Lake 52

Data Lake Building Raw Data ETL Tools 52

Data Engineering Podcast

OCTOBER 16, 2022

Summary The "data lakehouse" architecture balances the scalability and flexibility of data lakes with the ease of use and transaction support of data warehouses. Mention the podcast to get a free "In Data We Trust World Tour" t-shirt. That’s where our friends at Ascend.io

Data Lake 100

Data Lake Food MongoDB MySQL 100

Data Engineering Podcast

JUNE 12, 2022

Acryl Data provides DataHub as an easy to consume SaaS product which has been adopted by several companies. Signup for the SaaS product at dataengineeringpodcast.com/acryl RudderStack helps you build a customer data platform on your warehouse or data lake. That’s where our friends at Ascend.io

Unstructured Data 130

Unstructured Data MongoDB MySQL Scala 130

Data Engineering Podcast

JUNE 19, 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.

Metadata 130

Metadata MongoDB MySQL Scala 130

Monte Carlo

JANUARY 5, 2024

You know what they always say: data lakehouse architecture is like an onion. …ok, Data lakehouse architecture combines the benefits of data warehouses and data lakes, bringing together the structure and performance of a data warehouse with the flexibility of a data lake.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Cloudera

AUGUST 13, 2021

Whether it is consuming log files, sensor metrics, and other unstructured data, most enterprises manage and deliver data to the data lake and leverage various applications like ETL tools, search engines, and databases for analysis. What should IT leaders consider when planning their data needs?

Data Pipeline 111

Data Pipeline Data Lake ETL Tools Unstructured Data 111

Data Engineering Podcast

NOVEMBER 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.

MongoDB 130

MongoDB MySQL Scala Machine Learning 130

Christophe Blefari

JANUARY 20, 2024

The main difference between both is the fact that your computation resides in your warehouse with SQL rather than outside with a programming language loading data in memory. In this category I recommend also to have a look at data ingestion (Airbyte, Fivetran, etc.), workflows (Airflow, Prefect, Dagster, etc.)

Data Engineer 130

Data Engineer Data Engineering Engineering Hadoop 130

Monte Carlo

JANUARY 5, 2024

You know what they always say: data lakehouse architecture is like an onion. …ok, Data lakehouse architecture combines the benefits of data warehouses and data lakes, bringing together the structure and performance of a data warehouse with the flexibility of a data lake.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Snowflake

JUNE 4, 2024

Snowflake provides a strong data foundation anchored on unified data, optimal TCO and universal governance. The Snowflake platform eliminates silos to enable any architectural pattern, while supporting all data types and workloads. Getting data ingested now only takes a few clicks, and the data is encrypted.

Government 105

Government Data Ingestion Data PostgreSQL 105

Cloudera

JUNE 30, 2022

Over the past decade, Cloudera has enabled multi-function analytics on data lakes through the introduction of the Hive table format and Hive ACID. Companies, on the other hand, have continued to demand highly scalable and flexible analytic engines and services on the data lake, without vendor lock-in.

Data Lake 88

Data Lake Business Intelligence Metadata Data Warehouse 88

Knowledge Hut

JULY 3, 2023

This is where real-time data ingestion comes into the picture. Data is collected from various sources such as social media feeds, website interactions, log files and processing. This refers to Real-time data ingestion. To achieve this goal, pursuing Data Engineer certification can be highly beneficial.

Data Ingestion 52

Data Ingestion Google Cloud Pipeline-centric Media 52

Monte Carlo

JUNE 14, 2023

In this post, we will help you quickly level up your overall knowledge of data pipeline architecture by reviewing: Table of Contents What is data pipeline architecture? Why is data pipeline architecture important? What is data pipeline architecture? Why is data pipeline architecture important?

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Databand.ai

AUGUST 30, 2023

DataOps Architecture: 5 Key Components and How to Get Started Ryan Yackel August 30, 2023 What Is DataOps Architecture? DataOps is a collaborative approach to data management that combines the agility of DevOps with the power of data analytics. As a result, they can be slow, inefficient, and prone to errors.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

Rockset

OCTOBER 11, 2022

The flow of data often involves complex ETL tooling as well as self-managing integrations to ensure that high volume writes, including updates and deletes, do not rack up CPU or impact performance of the end application. That’s because Elasticsearch can only write data to one index.

Data Ingestion 52

Data Ingestion Kafka Relational Database PostgreSQL 52

Rockset

AUGUST 4, 2021

Organizations that depend on data for their success and survival need robust, scalable data architecture, typically employing a data warehouse for analytics needs. Snowflake is often their cloud-native data warehouse of choice. Data ingestion must be performant to handle large amounts of data.

Data Ingestion 40

Data Ingestion Cloud Storage Data Warehouse Architecture 40

Data Engineering Podcast

SEPTEMBER 25, 2022

Mention the podcast to get a free "In Data We Trust World Tour" t-shirt. RudderStack helps you build a customer data platform on your warehouse or data lake. The Ascend Data Automation Cloud provides a unified platform for data ingestion, transformation, orchestration, and observability.

Food 100

Food MongoDB MySQL Scala 100

Data Engineering Podcast

NOVEMBER 13, 2022

Datafold integrates with all major data warehouses as well as frameworks such as Airflow & dbt and seamlessly plugs into CI workflows. RudderStack helps you build a customer data platform on your warehouse or data lake. What are some of the characteristics of the data that you work with?

MongoDB 100

MongoDB MySQL Google Cloud Scala 100

Data Engineering Podcast

SEPTEMBER 11, 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 Pipeline 130

Data Pipeline Building MongoDB MySQL 130

Cloudera

MARCH 31, 2021

With the addition of Google Cloud, we deliver on our vision of providing a hybrid and multi-cloud architecture to support our customer’s analytics needs regardless of deployment platform. . Data Preparation (Apache Spark and Apache Hive) .

Google Cloud 94

Google Cloud Cloud Amazon Web Services Cloud Storage 94

Cloudera

AUGUST 26, 2020

Hello Dinesh, thank you for joining us for Part II of our Q&A on streaming data. Can you talk a bit about how businesses best use Flink within a streaming architecture and what is it about the solution that promotes low latency processing of high-volume streaming data?

Banking 84

Banking Data Ingestion Kafka Data Lake 84

Data Engineering Podcast

OCTOBER 9, 2022

Mention the podcast to get a free "In Data We Trust World Tour" t-shirt. RudderStack helps you build a customer data platform on your warehouse or data lake. The Ascend Data Automation Cloud provides a unified platform for data ingestion, transformation, orchestration, and observability.

Food 100

Food MongoDB MySQL Scala 100

Edureka

AUGUST 19, 2024

The Azure Databricks architecture is designed to become an incredibly robust framework in data analytics on the Microsoft Azure platform. High-level Architecture Conclusion Frequently Asked Questions Azure Databricks simplifies the data engineering and data science workflows.

Architecture 40

Architecture Data Lake Machine Learning Data Ingestion 40

Data Engineering Podcast

JULY 17, 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 Engineer 100

Data Engineer Data Engineering Engineering MongoDB 100

ProjectPro

DECEMBER 7, 2021

Data pipelines are a significant part of the big data domain, and every professional working or willing to work in this field must have extensive knowledge of them. As data is expanding exponentially, organizations struggle to harness digital information's power for different business use cases. What is a Big Data Pipeline?

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

ProjectPro

JULY 22, 2016

For the same cost, organizations can now store 50 times as much data as in a Hadoop data lake than in a data warehouse. Data lake is gaining momentum across various organizations and everyone wants to know how to implement a data lake and why.

Data Lake 40

Data Lake Data Warehouse Hadoop Unstructured Data 40