Cloudera

JUNE 25, 2021

This blog post outlines detailed step by step instructions to perform Hive Replication from an on-prem CDH cluster to a CDP Public Cloud Data Lake. CDP Data Lake cluster versions – CM 7.4.0, Configure the required ports to enable connectivity from CDH to CDP Public Cloud (see docs for details).

Cloud 74

Cloud Data Lake Cloud Storage Metadata 74

Monte Carlo

AUGUST 25, 2023

That’s why it’s essential for teams to choose the right architecture for the storage layer of their data stack. But, the options for data storage are evolving quickly. So let’s get to the bottom of the big question: what kind of data storage layer will provide the strongest foundation for your data platform?

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Data Engineering Weekly

AUGUST 11, 2024

link] Uber: Enabling Security for Hadoop Data Lake on Google Cloud Storage Uber writes about securing a Hadoop-based data lake on Google Cloud Platform (GCP) by replacing HDFS with Google Cloud Storage (GCS) while maintaining existing security models like Kerberos-based authentication.

Data Engineering 57

Data Engineering Data Engineer Google Cloud Engineering 57

phData: Data Engineering

NOVEMBER 8, 2024

Note : Cloud Data warehouses like Snowflake and Big Query already have a default time travel feature. However, this feature becomes an absolute must-have if you are operating your analytics on top of your data lake or lakehouse. It can also be integrated into major data platforms like Snowflake.

Architecture 52

Architecture Systems Data Lake Google Cloud 52

Cloudera

SEPTEMBER 15, 2020

Cloudera Data Platform 7.2.1 introduces fine-grained authorization for access to Azure Data Lake Storage using Apache Ranger policies. Cloudera and Microsoft have been working together closely on this integration, which greatly simplifies the security administration of access to ADLS-Gen2 cloud storage.

Accessible 79

Accessible Accessibility Cloud Cloud Storage 79

Towards Data Science

APRIL 26, 2023

An open-source implementation of a Data Lake with DuckDB and AWS Lambdas A duck in the cloud. Photo by László Glatz on Unsplash In this post we will show how to build a simple end-to-end application in the cloud on a serverless infrastructure. The cloud is better.

Engineering 65

Engineering Data Lake AWS BI 65

AltexSoft

FEBRUARY 11, 2023

It serves as a foundation for the entire data management strategy and consists of multiple components including data pipelines; , on-premises and cloud storage facilities – data lakes , data warehouses , data hubs ;, data streaming and Big Data analytics solutions ( Hadoop , Spark , Kafka , etc.);

Data Architect 87

Data Architect Certification Generalist Big Data 87

Rockset

AUGUST 25, 2021

With this release , Rockset users have the capability to continuously aggregate and transform data at the time of ingest, using SQL, from any data source (data streams, databases and data lakes). This is a first in the industry and frees users from managing slow, expensive ETL pipelines for their streaming data.

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Aggregated Data Hadoop SQL Data Lake 52

Knowledge Hut

APRIL 25, 2023

Data modeling: Data engineers should be able to design and develop data models that help represent complex data structures effectively. Data processing: Data engineers should know data processing frameworks like Apache Spark, Hadoop, or Kafka, which help process and analyze data at scale.

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

Knowledge Hut

SEPTEMBER 26, 2023

Key connectivity features include: Data Ingestion: Databricks supports data ingestion from a variety of sources, including data lakes, databases, streaming platforms, and cloud storage. This flexibility allows organizations to ingest data from virtually anywhere.

Data Lake 52

Data Lake Database-centric Pipeline-centric Machine Learning 52

Confluent

OCTOBER 16, 2019

Along with using Postgres (or KSQL as shown above) for analytics, the data can be streamed using Kafka Connect into S3, from where it can serve multiple roles. In S3, it can be seen as the “cold storage”, or the data lake, against which as-yet-unknown applications and processes may be run.

Kafka 19

Kafka Building Data Coding 19

Edureka

FEBRUARY 9, 2023

In this blog on “Azure data engineer skills”, you will discover the secrets to success in Azure data engineering with expert tips, tricks, and best practices Furthermore, a solid understanding of big data technologies such as Hadoop, Spark, and SQL Server is required.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Mining 52

ProjectPro

DECEMBER 7, 2021

Generally, data pipelines are created to store data in a data warehouse or data lake or provide information directly to the machine learning model development. Keeping data in data warehouses or data lakes helps companies centralize the data for several data-driven initiatives.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

ProjectPro

AUGUST 24, 2021

Then, the Yelp dataset downloaded in JSON format is connected to Cloud SDK, following connections to Cloud storage which is then connected with Cloud Composer. Cloud composer and PubSub outputs are Apache Beam and connected to Google Dataflow. Understand the importance of Qubole in powering up Hadoop and Notebooks.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Ascend.io

MAY 18, 2023

The growing complexity drove a proliferation of software and data innovations, which in turn demanded highly trained data engineers to build code-based data pipelines that ensured data quality, consistency, and stability. Because data pipelines were coded from scratch, they started breaking down under the complexity.

Data Warehouse 52

Data Warehouse Data Pipeline Data Lake Data Engineering 52

ProjectPro

JANUARY 24, 2023

BigQuery enables users to store data in tables, allowing them to quickly and easily access their data. It supports structured and unstructured data, allowing users to work with various formats. BigQuery also supports many data sources, including Google Cloud Storage, Google Drive, and Sheets.

Bytes 52

Bytes Google Cloud Data Warehouse Cloud Storage 52

ProjectPro

JANUARY 19, 2022

ETL (extract, transform, and load) techniques move data from databases and other systems into a single hub, such as a data warehouse. Different methods are used to store different types of data. It is better to know when to employ a data lake vs. a data warehouse to create data solutions for an organization.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Storage 52

ProjectPro

NOVEMBER 30, 2021

Cloud: Technology advancements, information security threats, faster internet speeds, and a push to prevent data loss have contributed to the move toward cloud-native storage and processing. It is the most feasible option when the data size is huge.

Process 52

Process Data Pipeline Data Warehouse AWS 52

ProjectPro

FEBRUARY 16, 2023

According to the 8,786 data professionals participating in Stack Overflow's survey, SQL is the most commonly-used language in data science. Despite the buzz surrounding NoSQL , Hadoop , and other big data technologies, SQL remains the most dominant language for data operations among all tech companies.

Data Engineering 52

Data Engineering Data Engineer SQL Engineering 52

AltexSoft

MAY 12, 2023

Without a fixed schema, the data can vary in structure and organization. File systems, data lakes, and Big Data processing frameworks like Hadoop and Spark are often utilized for managing and analyzing unstructured data. Amazon S3, Google Cloud Storage, Microsoft Azure Blob Storage), NoSQL databases (e.g.,

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

AltexSoft

MARCH 30, 2023

What is Databricks Databricks is an analytics platform with a unified set of tools for data engineering, data management , data science, and machine learning. It combines the best elements of a data warehouse, a centralized repository for structured data, and a data lake used to host large amounts of raw data.

Scala 64

Scala Data Lake BI Machine Learning 64