Seattle Data Guy

FEBRUARY 10, 2024

Photo by Tiger Lily Data warehouses and data lakes play a crucial role for many businesses. It gives businesses access to the data from all of their various systems. As well as often integrating data so that end-users can answer business critical questions.

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Data Lake Data Warehouse Data Accessible 162

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

AUGUST 31, 2020

Summary Data warehouse technology has been around for decades and has gone through several generational shifts in that time. The current trends in data warehousing are oriented around cloud native architectures that take advantage of dynamic scaling and the separation of compute and storage.

Data Warehouse 100

Data Warehouse Cloud Building Data Lake 100

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?

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Data Lake Architecture IT Amazon Web Services 52

Data Engineering Podcast

JULY 22, 2019

Summary The current trend in data management is to centralize the responsibilities of storing and curating the organization’s information to a data engineering team. This organizational pattern is reinforced by the architectural pattern of data lakes as a solution for managing storage and access.

Data Lake 100

Data Lake Hadoop Data Architecture 100

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

Christophe Blefari

JANUARY 20, 2024

Data engineering inherits from years of data practices in US big companies. Hadoop initially led the way with Big Data and distributed computing on-premise to finally land on Modern Data Stack — in the cloud — with a data warehouse at the center.

Data Engineering 130

Data Engineering Data Engineer Engineering Hadoop 130

Confessions of a Data Guy

JANUARY 12, 2023

Anyone who’s been roaming around the forest of Data Engineering has probably run into many of the newish tools that have been growing rapidly around the concepts of Data Warehouses, Data Lakes, and Lake Houses … the merging of the old relational database functionality with TB and PB level cloud-based file storage systems.

Data Lake 162

Data Lake Relational Database Data Warehouse Data Engineering 162

Knowledge Hut

MARCH 28, 2024

Role Level Intermediate Responsibilities Design and develop data pipelines to ingest, process, and transform data. Implemented and managed data storage solutions using Azure services like Azure SQL Database , Azure Data Lake Storage, and Azure Cosmos DB.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Cloudera

JUNE 18, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes.

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Data Lake Data Warehouse BI SQL 89

ProjectPro

SEPTEMBER 26, 2021

Big Data Engineer is one of the most popular job profiles in the data industry. This blog on Big Data Engineer salary gives you a clear picture of the salary range according to skills, countries, industries, job titles, etc. Big Data gets over 1.2 What does a big data engineer do?

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Big Data Data Engineering Data Engineer Engineering 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.

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Data Lake Data SQL Data Warehouse 87

Data Science Blog: Data Engineering

SEPTEMBER 24, 2021

Data Warehousing is applied Big Data Management and a key success factor in almost every company. Without a data warehouse, no company today can control its processes and make the right decisions on a strategic level as there would be a lack of data transparency for all decision makers.

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Data Lake Data Warehouse Data Transparency Database 52

Analytics Vidhya

FEBRUARY 27, 2023

Introduction Enterprises here and now catalyze vast quantities of data, which can be a high-end source of business intelligence and insight when used appropriately. Delta Lake allows businesses to access and break new data down in real time.

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Data Lake Business Intelligence Designing Accessible 215

Data Engineering Podcast

FEBRUARY 9, 2020

Summary Designing the structure for your data warehouse is a complex and challenging process. As businesses deal with a growing number of sources and types of information that they need to integrate, they need a data modeling strategy that provides them with flexibility and speed.

Data Lake 100

Data Lake Data Warehouse Hadoop NoSQL 100

Knowledge Hut

NOVEMBER 17, 2023

To provide end users with a variety of ready-made models, Azure Data engineers collaborate with Azure AI services built on top of Azure Cognitive Services APIs. Database Knowledge Data warehousing ideas like the star and snowflake schema, as well as how to design and develop a data warehouse, should be well understood by you.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

Data Engineering Podcast

SEPTEMBER 23, 2018

Using the metaphor of a museum curator carefully managing the precious resources on display and in the vaults, he discusses the various layers of an enterprise data strategy. What are some of the common mistakes that are made when designing a data architecture and how do they lead to failure?

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Data Lake Data Warehouse Data Architecture Architecture 100

François Nguyen

MARCH 22, 2021

With this 3rd platform generation, you have more real time data analytics and a cost reduction because it is easier to manage this infrastructure in the cloud thanks to managed services. The core idea of Data Mesh is how you can develop the data usages and remove the centralized and monolitich data warehouse where you have very less access.

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Architecture Technology Google Cloud Metadata 130

Knowledge Hut

JUNE 30, 2023

Key Benefits and Takeaways: Understand data intake strategies and data transformation procedures by learning data engineering principles with Python. Investigate alternative data storage solutions, such as databases and data lakes. Key Benefits and Takeaways: Learn the core concepts of big data systems.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Knowledge Hut

SEPTEMBER 26, 2023

Data is necessary for everything, including analytics and traffic monitoring. Businesses require an infrastructure that educates their staff to sort and analyze this volume of data to handle such big data. Data engineering services can be used in this situation.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Knowledge Hut

JANUARY 18, 2024

Data Science is an amalgamation of several disciplines, including computer science, statistics, and machine learning. As the world on the internet is becoming our second home, Big Data has exploded. Data Science is the study of this big data to derive a meaningful pattern.

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Data Science Amazon Web Services Finance Big Data 98

Knowledge Hut

NOVEMBER 2, 2023

Azure Data Ingestion Pipeline Create an Azure Data Factory data ingestion pipeline to extract data from a source (e.g., Azure SQL Database, Azure Data Lake Storage). Data Aggregation Working with a sample of big data allows you to investigate real-time data processing, big data project design, and data flow.

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Data Engineering Data Engineer Coding Project 52

Knowledge Hut

SEPTEMBER 25, 2023

They are moving their servers and on-premises data to Azure Cloud. What does all of this mean for Data Engineering professionals? In order to manage big data and other operational services, businesses are continuously in need of data engineers. Azure Data Engineers work with these and other solutions.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

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. Table of Contents What is a Data Pipeline? The Importance of a Data Pipeline What is an ETL Data Pipeline? What is a Big Data Pipeline?

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Data Pipeline Architecture Kafka AWS 52

Monte Carlo

JUNE 28, 2022

To help organizations realize the full potential of their data lake and lakehouse investments, Monte Carlo, the data observability leader, is proud to announce integrations with Delta Lake and Databricks’ Unity Catalog for full data observability coverage. billion in 2020 to 17.60 billion in 2020 to 17.60

Data Lake 52

Data Lake Metadata AWS Data Warehouse 52

Knowledge Hut

NOVEMBER 29, 2023

Exam 70-475: Designing and Implementing Big Data Analytics Solutions This exam is for data developers, data architects, data management professionals, and data scientists who use the Microsoft Azure to design big data analytics. Design and implement Azure SQL Data Warehouse Solutions.

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Certification Big Data Machine Learning Data Lake 52

Data Engineering Podcast

NOVEMBER 18, 2019

Summary With the constant evolution of technology for data management it can seem impossible to make an informed decision about whether to build a data warehouse, or a data lake, or just leave your data wherever it currently rests. How does it influence the relevancy of data warehouses or data lakes?

Data Lake 100

Data Lake Scala Data Warehouse Hadoop 100

Hepta Analytics

FEBRUARY 14, 2022

This week, we got to think about our data ingestion design. We looked at the following: How do we ingest – ETL vs ELT Where do we store the data – Data lake vs data warehouse Which tool to we use to ingest – cronjob vs workflow engine NOTE : This weeks task requires good internet speed and good compute.

Data Ingestion 52

Data Ingestion Data Engineering Data Engineer Engineering 52

ProjectPro

JANUARY 24, 2023

With over 20 pre-built connectors and 40 pre-built transformers, AWS Glue is an extract, transform, and load (ETL) service that is fully managed and allows users to easily process and import their data for analytics. You can leverage AWS Glue to discover, transform, and prepare your data for analytics. If yes, which ones and how?

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AWS Data Lake ETL Tools Scala 52

Data Engineering Podcast

MARCH 16, 2020

Your team will get the most complete, accurate and ready-to-use behavioral web and mobile data, delivered into your data warehouse, data lake and real-time streams. Setting up and managing a data warehouse for your business analytics is a huge task.

Building 100

Building Data Warehouse NoSQL Data Lake 100

Knowledge Hut

APRIL 25, 2023

The tremendous growth in data generation, then the rise in data engineer jobs - there’s no arguing the fact that the big data industry is at its best pace and you, as an aspiring data engineer, have a lot to learn and make out of it - including some tools!

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

Data Engineering Podcast

MAY 19, 2019

Summary In recent years the traditional approach to building data warehouses has shifted from transforming records before loading, to transforming them afterwards. The data build tool (dbt) is designed to bring battle tested engineering practices to your analytics pipelines.

Data Analytics 100

Data Analytics Building Engineering Data Warehouse 100

Knowledge Hut

NOVEMBER 28, 2023

Data Engineers are professionals who bridge the gap between the working capacity of software engineering and programming. They are people equipped with advanced analytical skills, robust programming skills, statistical knowledge, and a clear understanding of big data technologies.

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Data Engineering Data Engineer Engineering Generalist 52

Grouparoo

OCTOBER 6, 2021

This provided a nice overview of the breadth of topics that are relevant to data engineering including data warehouses/lakes, pipelines, metadata, security, compliance, quality, and working with other teams. This was the first book I have read in this series and I liked the format. What would that look like?

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Data Engineering Data Engineer Engineering Pipeline-centric 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?

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Data Lake Data Warehouse Cloud Hadoop 52

Databand.ai

DECEMBER 13, 2022

We’d be remiss not to share that Joseph was a recent guest on Databand’s MAD Data Podcast , where he discussed ways to keep data systems from becoming unwieldy and shared tips for data teams to manage their data warehouses and keep data pipelines running reliably. You can also watch the video recording.

Data Engineering 52

Data Engineering Data Engineer Engineering AWS 52

Knowledge Hut

DECEMBER 29, 2023

Data scientists may improve their knowledge and response to crucial business demands by opting to specialize in a subfield of their subject. It's possible they'll zero down on a certain data kind, like Big Data, or a computer language. One of the primary focuses of a Data Engineer's work is on the Hadoop data lakes.

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Data Science Data Mining Deep Learning Programming Language 98