AltexSoft

MAY 12, 2023

In today’s data-driven world, organizations amass vast amounts of information that can unlock significant insights and inform decision-making. A staggering 80 percent of this digital treasure trove is unstructured data, which lacks a pre-defined format or organization. What is unstructured data?

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

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

Propel Data

OCTOBER 11, 2022

The main difference between data lakes and data warehouses is data lakes allow unstructured data, but data warehouses need structured data.

Data Lake 40

Data Lake Data Warehouse Unstructured Data Data Analytics 40

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

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.

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Data Lake Process Metadata Data Warehouse 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

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. And what is the reason for that?

Data Lake 52

Data Lake Building Raw Data ETL Tools 52

Data Engineering Podcast

AUGUST 14, 2021

In this episode Davit Buniatyan, founder and CEO of Activeloop, explains why he is spending his time and energy on building a platform to simplify the work of getting your unstructured data ready for machine learning. Are you bored with writing scripts to move data into SaaS tools like Salesforce, Marketo, or Facebook Ads?

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Unstructured Data Machine Learning Data Lake SQL 100

Monte Carlo

JANUARY 23, 2023

When it comes to the data community, there’s always a debate broiling about something— and right now “data mesh vs data lake” is right at the top of that list. In this post we compare and contrast the data mesh vs data lake to illustrate the benefits of each and help discover what’s right for your data platform.

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Data Lake Business Intelligence Unstructured Data Architecture 52

Towards Data Science

DECEMBER 4, 2023

A robust data infrastructure is a must-have to compete in the F1 business. We’ll build a data architecture to support our racing team starting from the three canonical layers : Data Lake, Data Warehouse, and Data Mart. Data Marts There is a thin line between Data Warehouses and Data Marts.

Data Engineering 88

Data Engineering Data Engineer Engineering Data Lake 88

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. Image courtesy of Databricks.

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. Image courtesy of Databricks.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Monte Carlo

APRIL 1, 2021

Over the past few years, data lakes have emerged as a must-have for the modern data stack. But while the technologies powering our access and analysis of data have matured, the mechanics behind understanding this data in a distributed environment have lagged behind. Data discovery tools and platforms can help.

Data Lake 52

Data Lake Unstructured Data Data Warehouse Metadata 52

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.

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Data Lake Data Warehouse Hadoop Unstructured Data 40

Monte Carlo

JANUARY 16, 2024

At the center of it all is the data warehouse, the lynchpin of any modern data stack. In this blog post, we’ll look at six innovations that are shaping the future of the data warehousing, as well as challenges and considerations that organizations should keep in mind. Data lake and data warehouse convergence 2.

Data Lake 52

Data Lake Data Warehouse Unstructured Data AWS 52

Monte Carlo

JANUARY 25, 2023

When it comes to the question of building or buying your data stack, there’s never a one-size-fits-all solution for every data team—or every component of your data stack. Data storage and compute are very much the foundation of your data platform. Let’s jump in! So, let’s take a look at each in a bit more detail.

Data Warehouse 40

Data Warehouse Building Data Lake Data Storage 40

Monte Carlo

JUNE 2, 2021

With the new Databricks integration from Monte Carlo, teams working in data lakes can finally trust their data through end-to-end data observability and automated lineage of their entire data ecosystem. Over the last few years, data lakes have emerged as a must-have for the modern data stack.

Data Lake 52

Data Lake Machine Learning Unstructured Data Datasets 52

Monte Carlo

MAY 31, 2022

Metadata from the data warehouse/lake and from the BI tool of record can then be used to map the dependencies between the tables and dashboards. It also becomes outdated virtually the moment it’s mapped as your environment continues to ingest more data and you continue to layer on additional solutions.

Data Lake 52

Data Lake Building Scala Metadata 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. This feature allows for a more flexible exploration of data.

Data Management 52

Data Management Data Lake Management Data Governance 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. This feature allows for a more flexible exploration of data.

Data Management 52

Data Management Data Lake Management Data Governance 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. This feature allows for a more flexible exploration of data.

Data Management 52

Data Management Data Lake Management Data Governance 52

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

MARCH 17, 2023

When implementing a data lakehouse, the table format is a critical piece because it acts as an abstraction layer, making it easy to access all the structured, unstructured data in the lakehouse by any engine or tool, concurrently. Some of the popular table formats are Apache Iceberg, Delta Lake, Hudi, and Hive ACID.

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Education Unstructured Data Data Lake Data Warehouse 60

The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. Data lakes offer a scalable and cost-effective solution.

Data Management 52

Data Management Management Data Lake Data Warehouse 52

The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. Data lakes offer a scalable and cost-effective solution.

Data Management 52

Data Management Management Data Lake Data Warehouse 52

The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. Data lakes offer a scalable and cost-effective solution.

Data Management 52

Data Management Management Data Lake Data Warehouse 52

Towards Data Science

MAY 3, 2023

VDK helps you easily perform complex operations, such as data ingestion and processing from different sources, using SQL or Python. You can use VDK to build data lakes and ingest raw data extracted from different sources, including structured, semi-structured, and unstructured data.

Data Lake 88

Data Lake Data SQL Data Warehouse 88

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

Towards Data Science

FEBRUARY 9, 2024

Data Store Another significant change from 2021 to 2024 lies in the shift from “Data Warehouse” to “Data Store,” acknowledging the expanding database horizon, including the rise of Data Lakes. Their robust core offering seamlessly integrates data warehouses with data-hungry applications.

Building 84

Building Transportation Data Lake Metadata 84

U-Next

MARCH 1, 2023

Morgan Stanley Data Engineer Interview Questions As a data engineer at Morgan Stanley, you will be responsible for creating and maintaining the infrastructure for their data warehouse. Analyzing this data often involves Machine Learning, a part of Data Science. What is a data warehouse?

Data Engineering 75

Data Engineering Data Engineer Non-relational Database Engineering 75

Data Engineering Podcast

NOVEMBER 27, 2022

Trusted by the data teams at Fox, JetBlue, and PagerDuty, Monte Carlo solves the costly problem of broken data pipelines. Monte Carlo also gives you a holistic picture of data health with automatic, end-to-end lineage from ingestion to the BI layer directly out of the box. images, documents, etc.) images, documents, etc.)

Data Process 100

Data Process Process Metadata Business Intelligence 100

DareData

JANUARY 30, 2023

Here are a couple of resources to learn more: Data Talks Club Data Ingestion Week Coder2J Airflow Tutorial Data Storage In the context of data engineering, data storage refers to the systems and technologies that are used to store and manage data within an organization.

Data Engineering 52

Data Engineering Data Engineer NoSQL Engineering 52

Monte Carlo

JUNE 14, 2023

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

Knowledge Hut

SEPTEMBER 26, 2023

We as Azure Data Engineers should have extensive knowledge of data modelling and ETL (extract, transform, load) procedures in addition to extensive expertise in creating and managing data pipelines, data lakes, and data warehouses. ETL activities are also the responsibility of data engineers.

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Certification Data Engineering Data Engineer Engineering 52

AltexSoft

SEPTEMBER 23, 2021

One of the innovative ways to address this problem is to build a data hub — a platform that unites all your information sources under a single umbrella. This article explains the main concepts of a data hub, its architecture, and how it differs from data warehouses and data lakes. What is Data Hub?

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

AltexSoft

JUNE 26, 2023

From the perspective of data science, all miscellaneous forms of data fall into three large groups: structured, semi-structured, and unstructured. Key differences between structured, semi-structured, and unstructured data. Unstructured data represents up to 80-90 percent of the entire datasphere.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

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.

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Building BI Data Lake Data Governance 52