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

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? What is a Data lake?

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

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 idea is to start from a Data Lake where our data are stored.

Engineering 67

Engineering Data Lake AWS BI 67

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. What are the mechanisms that you use for categorizing data assets?

Unstructured Data 130

Unstructured Data MongoDB Scala MySQL 130

Cloudera

JUNE 25, 2021

Many Cloudera customers are making the transition from being completely on-prem to cloud by either backing up their data in the cloud, or running multi-functional analytics on CDP Public cloud in AWS or Azure. CDP Data Lake cluster versions – CM 7.4.0, Pre-Check: Data Lake Cluster.

Cloud 73

Cloud Data Lake Cloud Storage Metadata 73

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) . Analyze static (Apache Impala) and streaming (Apache Flink) data.

Google Cloud 94

Google Cloud Cloud Amazon Web Services Cloud Storage 94

DareData

JANUARY 30, 2023

Some examples are: Apache Airflow: An open-source data orchestrator that enables users to define, schedule, and monitor workflows. AWS Glue: A fully managed data orchestrator service offered by Amazon Web Services (AWS). Some examples include Amazon Redshift, Azure SQL Data Warehouse, and Google BigQuery.

Data Engineering 52

Data Engineering Data Engineer NoSQL Engineering 52

Data Engineering Podcast

SEPTEMBER 22, 2019

Summary Object storage is quickly becoming the unifying layer for data intensive applications and analytics. Modern, cloud oriented data warehouses and data lakes both rely on the durability and ease of use that it provides. How do you approach project governance and sustainability?

AWS 100

AWS Google Cloud Cloud Storage Data Lake 100

Cloudera

JANUARY 21, 2021

Of high value to existing customers, Cloudera’s Data Warehouse service has a unique, separated architecture. . Separate storage. Cloudera’s Data Warehouse service allows raw data to be stored in the cloud storage of your choice (S3, ADLSg2). Proprietary file formats mean no one else is invited in!

IT 93

IT Data Lake Data Warehouse Cloud Storage 93

Ascend.io

AUGUST 31, 2023

Secondly , the rise of data lakes that catalyzed the transition from ELT to ELT and paved the way for niche paradigms such as Reverse ETL and Zero-ETL. Still, these methods have been overshadowed by EtLT — the predominant approach reshaping today’s data landscape.

Data Lake 52

Data Lake ETL Tools Data Warehouse Data Pipeline 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

Towards Data Science

DECEMBER 15, 2023

Even the best of us sometimes demonize the parts of our organization whose primary goals are in the privacy and security area and conflict with our wishes to splash around in the data lake. In reality, data scientists are not always the heroes and IT and security teams are not the villains. You’re using the data, of course!

Machine Learning 90

Machine Learning Data Science Data Security Data Storage 90

Knowledge Hut

SEPTEMBER 21, 2023

Sometimes, considering the three leading players in the cloud market, businesses search for the right cloud among the three to adopt. Questions such as which is better and easier to learn—AWS, Azure, or GCP— are often asked by organization leaders before starting out on their cloud journey.

Cloud 52

Cloud Google Cloud Cloud Computing Cloud Storage 52

ProjectPro

DECEMBER 7, 2021

The Importance of a Data Pipeline What is an ETL Data Pipeline? What is a Big Data Pipeline? Features of a Data Pipeline Data Pipeline Architecture How to Build an End-to-End Data Pipeline from Scratch? While data warehouses contain transformed data, data lakes contain unfiltered and unorganized raw data.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Knowledge Hut

APRIL 25, 2023

Here, we'll take a look at the top data engineer tools in 2023 that are essential for data professionals to succeed in their roles. These tools include both open-source and commercial options, as well as offerings from major cloud providers like AWS, Azure, and Google Cloud. What are Data Engineering Tools?

Data Engineering 52

Data Engineering Data Engineer Engineering 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.

Accessibility 79

Accessibility Accessible Cloud Cloud Storage 79

WeCloudData

OCTOBER 19, 2021

Conclusion WeCloudData helped a client build a flexible data pipeline to address the needs from multiple business units requiring different sets, views and timelines of job market data.

Consulting 52

Consulting Raw Data Data Lake Data Pipeline 52

WeCloudData

OCTOBER 19, 2021

Conclusion WeCloudData helped a client build a flexible data pipeline to address the needs from multiple business units requiring different sets, views and timelines of job market data.

Consulting 52

Consulting Raw Data Data Lake Data Pipeline 52

Rockset

MAY 24, 2021

Of AWS users, over half have adopted Lambda , but serverless isn't just Lambda functions. Serverless computing (often just called "serverless") is a model where a cloud provider, like AWS, abstracts away the concept of servers from the user. As serverless gains popularity, so does AWS Lambda. What Is Serverless?

Database 40

Database Google Cloud AWS Cloud Storage 40

AltexSoft

FEBRUARY 11, 2023

Data architecture is the organization and design of how data is collected, transformed, integrated, stored, and used by a company. The Big Data Science Certified Professional ( BDSCP ) program includes 15 course modules and exams covering such topics as Big Data analysis, engineering, architecture, governance, and more.

Data Architect 87

Data Architect Certification Generalist Big Data 87

ProjectPro

OCTOBER 6, 2021

Also, Cloud Endpoints are used, which help speed up the development, making smoother API calls for mobile app development. Data Lake using Google Cloud Platform What is a Data Lake? Data Lake is a centralized area or repository for data storage.

Google Cloud 52

Google Cloud Project Data Lake Healthcare 52

ProjectPro

AUGUST 24, 2021

Salary of Data Engineers Data Engineering Tools Skills Required to Become a Data Engineer Responsibilities of a Data Engineer FAQS on Data Engineering Projects Data Engineering Projects List There are a few data-related skills that most data engineering practitioners must possess.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Data Science Blog: Data Engineering

DECEMBER 23, 2022

Das Profil des Data Engineers: Big Data High-Tech Auch wenn Data Engineering von Hochschulen und Fortbildungsanbietern gerade noch etwas stiefmütterlich behandelt werden, werden der Einsatz und das daraus resultierende Anforderungsprofil eines Data Engineers am Markt recht eindeutig skizziert.

Data Engineering 52

Data Engineering Data Engineer Engineering Business Intelligence 52

Edureka

FEBRUARY 9, 2023

This demonstrates the high demand for Microsoft Azure Data Engineers. Every year, Azure’s usage graph grows, bringing it closer to AWS. These businesses are transferring their data and servers from on-premises to the Azure Cloud. To store various types of data, various methods are used.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Mining 52

ProjectPro

JANUARY 24, 2023

These benefits compel businesses to adopt cloud data warehousing and take their success to the next level. Some excellent cloud data warehousing platforms are available in the market- AWS Redshift, Google BigQuery , Microsoft Azure , Snowflake , etc. What is Google BigQuery Used for?

Bytes 52

Bytes Google Cloud Data Warehouse Datasets 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

Knowledge Hut

JUNE 26, 2023

Since there are numerous ways to approach this task, it encourages originality in one's approach to data analysis. Moreover, this project concept should highlight the fact that there are many interesting datasets already available on services like GCP and AWS. Source: Use Stack Overflow Data for Analytic Purposes 4.

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

ProjectPro

JANUARY 19, 2022

This indicates that Microsoft Azure Data Engineers are in high demand. Azure's usage graph grows every year, bringing it closer to AWS. These companies are migrating their data and servers from on-premises to Azure Cloud. Different methods are used to store different types of data.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Storage 52

AltexSoft

MAY 12, 2023

Unstructured data , on the other hand, is unpredictable and has no fixed schema, making it more challenging to analyze. Without a fixed schema, the data can vary in structure and organization. There are several widely used unstructured data storage solutions such as data lakes (e.g., Hadoop, Apache Spark).

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

Monte Carlo

AUGUST 19, 2023

With companies moving their data platforms to the cloud, the emergence of cloud-native solutions ( data warehouse vs data lake or even a data lakehouse ) have taken over the market, offering more accessible and affordable options for storing data relative to many on-premises solutions.

Building 52

Building BI Data Lake Data Governance 52