Monte Carlo

MAY 28, 2024

A data ingestion architecture is the technical blueprint that ensures that every pulse of your organization’s data ecosystem brings critical information to where it’s needed most. Data Transformation : Clean, format, and convert extracted data to ensure consistency and usability for both batch and real-time processing.

Data Ingestion 52

Data Ingestion Architecture Designing Hadoop 52

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

Monte Carlo

SEPTEMBER 25, 2024

A data lake is essentially a vast digital dumping ground where companies toss all their raw data, structured or not. A modern data stack can be built on top of this data storage and processing layer, or a data lakehouse or data warehouse, to store data and process it before it is later transformed and sent off for analysis.

Data Lake 52

Data Lake Food Google Cloud AWS 52

Edureka

APRIL 9, 2025

Imagine being in charge of creating an intelligent data universe where collaboration, analytics, and artificial intelligence all work together harmoniously. Programming Languages: Hands-on experience with SQL, Kusto Query Language (KQL), and Data Analysis Expressions ( DAX ). That’s what a Microsoft Fabric Engineer does.

Engineering 40

Engineering Data Ingestion Data Lake Programming Language 40

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 105

Digital Media Media Data Lake Data Warehouse 105

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

phData: Data Engineering

SEPTEMBER 19, 2023

With the amount of data companies are using growing to unprecedented levels, organizations are grappling with the challenge of efficiently managing and deriving insights from these vast volumes of structured and unstructured data. What is a Data Lake? Consistency of data throughout the data lake.

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

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

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

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

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

Striim

SEPTEMBER 11, 2024

Data Collection/Ingestion The next component in the data pipeline is the ingestion layer, which is responsible for collecting and bringing data into the pipeline. By efficiently handling data ingestion, this component sets the stage for effective data processing and analysis.

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

Rockset

OCTOBER 11, 2022

In this blog, we’ll compare and contrast how Elasticsearch and Rockset handle data ingestion as well as provide practical techniques for using these systems for real-time analytics. That’s because Elasticsearch can only write data to one index.

Data Ingestion 52

Data Ingestion Kafka Relational Database PostgreSQL 52

Towards Data Science

MAY 3, 2023

One such tool is the Versatile Data Kit (VDK), which offers a comprehensive solution for controlling your data versioning needs. VDK helps you easily perform complex operations, such as data ingestion and processing from different sources, using SQL or Python. Use VDK to build a data lake and merge multiple sources.

Data Lake 98

Data Lake SQL Data Data Warehouse 98

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

NOVEMBER 14, 2023

In this piece, we break down popular Iceberg use cases, advantages and disadvantages, and its impact on data quality so you can make the table format decision that’s right for your team. Is your data lake a good fit for Iceberg? Let’s dive in.

Data Lake 64

Data Lake Metadata Data Warehouse SQL 64

Cloudera

AUGUST 13, 2021

Every enterprise is trying to collect and analyze data to get better insights into their business. 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.

Data Pipeline 111

Data Pipeline Data Lake ETL Tools Unstructured Data 111

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. In fact, while only 3.5% That’s where our friends at Ascend.io

Unstructured Data 130

Unstructured Data MongoDB MySQL Scala 130

Cloudera

OCTOBER 11, 2021

Modak’s Nabu is a born in the cloud, cloud-neutral integrated data engineering platform designed to accelerate the journey of enterprises to the cloud. The platform converges data cataloging, data ingestion, data profiling, data tagging, data discovery, and data exploration into a unified platform, driven by metadata.

Data Engineering 95

Data Engineering Data Engineer Cloud Engineering 95

Snowflake

JUNE 4, 2024

This includes pipelines and transformations with Snowpark, Streams, Tasks and Dynamic Tables (public preview soon); extending AI and ML to Iceberg with Snowflake Cortex AI; performing storage maintenance with capabilities like automatic clustering and compaction; as well as securely collaborating on live data shares.

Government 113

Government Data Ingestion Data PostgreSQL 113

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. In fact, while only 3.5%

MongoDB 130

MongoDB MySQL Scala Machine Learning 130

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. In fact, while only 3.5% That’s where our friends at Ascend.io

Data Lake 100

Data Lake Food MongoDB MySQL 100

Cloudera

MAY 30, 2024

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission-critical, large-scale data analytics and AI use cases—including enterprise data warehouses.

Data Lake 74

Data Lake Data Warehouse Programming Language Data Ingestion 74

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. Apache Ozone brings the best of both HDFS and Object Store: Overcomes HDFS limitations.

Pipeline-centric 101

Pipeline-centric Data Lake Hadoop Big Data 101

Snowflake

SEPTEMBER 14, 2023

Unbound by the limitations of a legacy on-premises solution, its multi-cluster shared data architecture separates compute from storage, allowing data teams to easily scale up and down based on their needs. Now, the team is on an ongoing mission to use Snowflake’s data platform to simplify the complexity of its tech stack.

Data Architecture 122

Data Architecture Architecture Hadoop Data Warehouse 122

Rockset

AUGUST 4, 2021

With Snowflake, organizations get the simplicity of data management with the power of scaled-out data and distributed processing. Although Snowflake is great at querying massive amounts of data, the database still needs to ingest this data. Data ingestion must be performant to handle large amounts of data.

Data Ingestion 40

Data Ingestion Cloud Storage Data Warehouse Architecture 40

Cloudera

DECEMBER 14, 2021

Then, the company used Cloudera’s Data Platform as a foundation to build its own Network Real-time Analytics Platform (NRAP) and created the proper infrastructure to collect and analyze large-scale big data in real-time. . For this, the RTA transformed its data ingestion and management processes. .

Transportation 111

Transportation Telecommunication Banking Data Lake 111

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 Engineering 130

Data Engineering Data Engineer Engineering Hadoop 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. In fact, while only 3.5%

Metadata 130

Metadata MongoDB MySQL Scala 130

Cloudera

MAY 19, 2021

Data Ingestion. The raw data is in a series of CSV files. We will firstly convert this to parquet format as most data lakes exist as object stores full of parquet files. RAPIDS is only supported on Pascal or newer NVIDIA GPUs. For AWS this means at least P3 instances. P2 GPU instances are not supported.

Machine Learning 137

Machine Learning Data Science Datasets Raw Data 137

Christophe Blefari

MARCH 4, 2023

Data ingestion pipeline with Operation Management — At Netflix they annotate video which can lead to thousand of annotation but they need to manage the annotation lifecycle each time the annotation algorithm runs. Some company also call it a lakehouse or a data lake, but the word shift is enough interesting to notice.

Machine Learning 130

Machine Learning AWS Data Data Lake 130

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

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. In fact, while only 3.5%

Data Pipeline 130

Data Pipeline Building MongoDB MySQL 130

Cloudera

MARCH 31, 2021

Customers who have chosen Google Cloud as their cloud platform can now use CDP Public Cloud to create secure governed data lakes in their own cloud accounts and deliver security, compliance and metadata management across multiple compute clusters. Data Preparation (Apache Spark and Apache Hive) .

Google Cloud 94

Google Cloud Cloud Amazon Web Services Cloud Storage 94

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. In fact, while only 3.5%

Data Engineering 100

Data Engineering Data Engineer Engineering MongoDB 100

Cloudera

AUGUST 26, 2020

All of these happen continuously and repetitively on a daily basis, amounting to petabytes worth of information and data. This requires massive amounts of data ingestion, messaging, and processing within a data-in-motion context. From a data ingestion standpoint, NiFi is designed for this purpose.

Banking 84

Banking Data Ingestion Kafka Data Lake 84