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

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. What is the workflow for someone getting Sifflet integrated into their data stack?

Data Lake 130

Data Lake Data Ingestion MongoDB Google Cloud 130

Monte Carlo

JANUARY 5, 2024

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. Metadata layer 4. …ok, so maybe they don’t say that. But they should! Storage layer 3. API layer 5.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Monte Carlo

JANUARY 5, 2024

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. Metadata layer 4. …ok, so maybe they don’t say that. But they should! Storage layer 3. API layer 5.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Snowflake

NOVEMBER 11, 2024

Data stewards can also set up Request for Access (private preview) by setting a new visibility property on objects along with contact details so the right person can easily be reached to grant access. Support for auto-refresh and Iceberg metadata generation is coming soon to Delta Lake Direct.

Data Architecture 79

Data Architecture Architecture Data Lake Kafka 79

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

Data Engineering Weekly

MARCH 24, 2024

Dive into Spyne's experience with: - Their search for query acceleration with pre-aggregations and caching - Developing new functionality with Open AI - Optimizing query cost with their data warehouse [link] Suresh Hasuni: Cost Optimization Strategies for Scalable Data Lakehouse Cost is the major concern as the adoption of data lakes increases.

Data Engineer 62

Data Engineer Data Engineering Engineering Metadata 62

Cloudera

JUNE 30, 2022

With Cloudera’s vision of hybrid data , enterprises adopting an open data lakehouse can easily get application interoperability and portability to and from on premises environments and any public cloud without worrying about data scaling. Why integrate Apache Iceberg with Cloudera Data Platform?

Data Lake 87

Data Lake Business Intelligence Metadata Data Warehouse 87

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 86

Government Data Ingestion Data PostgreSQL 86

Cloudera

DECEMBER 15, 2022

Since we announced the general availability of Apache Iceberg in Cloudera Data Platform (CDP), Cloudera customers, such as Teranet , have built open lakehouses to future-proof their data platforms for all their analytical workloads. Only metadata will be regenerated. Data quality using table rollback.

Cloud 78

Cloud Metadata Google Cloud Data Warehouse 78

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. Collects and aggregates metadata from components and present cluster state.

Pipeline-centric 100

Pipeline-centric Data Lake Hadoop 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., being data exactly matches the classifier, and 0.0

AWS 98

AWS Scala Metadata Data Lake 98

Towards Data Science

JULY 24, 2023

Closely related to this is how those same platforms are bundling or unbundling related data services from data ingestion and transformation to data governance and monitoring. Why are these things related, and more importantly, why should data leaders care? Of course, there are always exceptions to the rule.

Metadata 94

Metadata Data Warehouse Data Lake Data Science 94

Cloudera

SEPTEMBER 9, 2022

analyst Sumit Pal, in “Exploring Lakehouse Architecture and Use Cases,” published January 11, 2022: “Data lakehouses integrate and unify the capabilities of data warehouses and data lakes, aiming to support AI, BI, ML, and data engineering on a single platform.” Iceberg handles massive data born in the cloud.

Architecture 101

Architecture Metadata Machine Learning Unstructured Data 101

Databand.ai

AUGUST 30, 2023

DataOps is a collaborative approach to data management that combines the agility of DevOps with the power of data analytics. It aims to streamline data ingestion, processing, and analytics by automating and integrating various data workflows.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

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. In fact, while only 3.5%

Machine Learning 100

Machine Learning Database MySQL PostgreSQL 100

Edureka

AUGUST 19, 2024

Workspace Storage Account: System data, notebooks, and logs are stored here. This storage account contains files and metadata associated with user workspaces, notebooks, and logs. It provides data versioning and transaction support. What are the three layers of the data reference architecture in Azure Databricks?

Architecture 40

Architecture Data Lake Machine Learning Data Ingestion 40

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 93

Google Cloud Cloud Amazon Web Services Cloud Storage 93

Data Engineering Weekly

OCTOBER 30, 2022

link] Dagster: Build a poor man’s data lake from scratch with DuckDB The value of the data is directly proportional to the recency of the data. The modern data stack is trying to address this problem in a silo; the org eventually has to tie everything to make it work.

Data Engineer 52

Data Engineer Data Engineering Engineering Data Ingestion 52

Monte Carlo

JUNE 14, 2023

Why is data pipeline architecture important? The modern data stack era , roughly 2017 to present data, saw the widespread adoption of cloud computing and modern data repositories that decoupled storage from compute such as data warehouses, data lakes, and data lakehouses.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

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. Parquet also stores type metadata which makes reading back and processing the files later slightly easier.

Machine Learning 136

Machine Learning Datasets Data Science Raw Data 136

LinkedIn Engineering

JULY 27, 2023

The landing page lists all the resource recommendations along with metadata around resource owners (Azure security groups), recommendation message, current lifecycle status of the recommendation, due date, assigned engineer, last action message in terms of comments, and a history modal option to check the timeline of actions taken.

Metadata 75

Metadata Utilities Cloud Database 75

Silectis

JANUARY 3, 2021

Data Catalog An organized inventory of data assets relying on metadata to help with data management. Data Engineering Data engineering is a process by which data engineers make data useful. Data Integration Combining data from various, disparate sources into one unified view.

Data Engineer 40

Data Engineer Data Engineering Engineering Hadoop 40

AltexSoft

JUNE 26, 2023

Read our article on Hotel Data Management to have a full picture of what information can be collected to boost revenue and customer satisfaction in hospitality. While all three are about data acquisition, they have distinct differences. The difference between data warehouses, lakes, and marts.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Cloudera

FEBRUARY 16, 2022

In the case of CDP Public Cloud, this includes virtual networking constructs and the data lake as provided by a combination of a Cloudera Shared Data Experience (SDX) and the underlying cloud storage. Each project consists of a declarative series of steps or operations that define the data science workflow.

Machine Learning 83

Machine Learning Algorithm Government Metadata 83

AltexSoft

JULY 29, 2022

a runtime environment (sandbox) for classic business intelligence (BI), advanced analysis of large volumes of data, predictive maintenance , and data discovery and exploration; a store for raw data; a tool for large-scale data integration ; and. a suitable technology to implement data lake architecture.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

Ascend.io

MARCH 14, 2023

In this article, you’re going to learn the following: What a data mesh is Why it gained momentum The five core features of data mesh Why a company might consider building one Let’s dive in! What Is a Data Mesh? Now that you know a little more about data mesh architecture, let’s talk about why it’s picking up momentum.

Government 52

Government Architecture Data Lake Data 52

Ascend.io

MARCH 14, 2023

In this article, you’re going to learn the following: What a data mesh is Why it gained momentum The five core features of data mesh Why a company might consider building one Let’s dive in! What Is a Data Mesh? Now that you know a little more about data mesh architecture, let’s talk about why it’s picking up momentum.

Government 52

Government Architecture Data Lake Data 52

Cloudera

JANUARY 22, 2019

Forrester describes Big Data Fabric as, “A unified, trusted, and comprehensive view of business data produced by orchestrating data sources automatically, intelligently, and securely, then preparing and processing them in big data platforms such as Hadoop and Apache Spark, data lakes, in-memory, and NoSQL.”.

Big Data 44

Big Data NoSQL Hadoop Data Lake 44

Rockset

NOVEMBER 28, 2022

These will help users more easily configure the correct transformations on top of CDC data. The full list of templates and platforms we’re announcing support for includes the following: Template Support Debezium : An open source distributed platform for change data capture.

Data Warehouse 52

Data Warehouse PostgreSQL MongoDB SQL 52

Cloudera

AUGUST 21, 2020

Over time, additional use cases and functions expanded from original EDW and Data Lake related functions to support increasing demands from the business. More sources, data, and functionality were added to these platforms, expanding their value but adding to the complexity, such as: Streaming data ingestion. .

Hadoop 76

Hadoop Big Data Cloud Kafka 76

ProjectPro

NOVEMBER 15, 2021

Apache Zeppelin Source: Github Apache Zeppelin is a multi-purpose notebook that supports Data Ingestion, Data Discovery, Data Analytics , Data Visualization , and Data Collaboration. Calcite has chosen to stay out of the data storage and processing business.

Big Data 52

Big Data Project Metadata Programming Language 52

ProjectPro

AUGUST 24, 2021

Data Engineering Project for Beginners If you are a newbie in data engineering and are interested in exploring real-world data engineering projects, check out the list of data engineering project examples below. This big data project discusses IoT architecture with a sample use case.

Data Engineer 52

Data Engineer Data Engineering Coding Project 52

Cloudera

JUNE 4, 2018

The solution to this massive data challenge embedded the Aspire Content Processing Framework into the Cloudera Enterprise Data Hub as a Cloudera Parcel – a binary distribution format containing the program files, along with additional metadata used by Cloudera Manager.

Pharmaceutical 45

Pharmaceutical Unstructured Data Electronics Metadata 45

ProjectPro

JANUARY 31, 2023

There are three steps involved in the deployment of a big data model: Data Ingestion: This is the first step in deploying a big data model - Data ingestion, i.e., extracting data from multiple data sources. NameNode is often given a large space to contain metadata for large-scale files.

Big Data 52

Big Data Hadoop Relational Database AWS 52

Snowflake

MARCH 30, 2023

3EJHjvm Once a business need is defined and a minimal viable product ( MVP ) is scoped, the data management phase begins with: Data ingestion: Data is acquired, cleansed, and curated before it is transformed. Feature engineering: Data is transformed to support ML model training. ML workflow, ubr.to/3EJHjvm

Engineering 86

Engineering Raw Data Data Science Machine Learning 86

ProjectPro

AUGUST 21, 2015

What are the steps involved in deploying a big data solution? JSON stores both data and schema together in a record and also enables complete schema evolution and splitability. Avro files store metadata with data and also let you specify independent schema for reading the files. This requires two separate machines.

Hadoop 40

Hadoop Big Data Metadata Java 40