Precisely

MARCH 9, 2023

Data warehouse vs. data lake, each has their own unique advantages and disadvantages; it’s helpful to understand their similarities and differences. In this article, we’ll focus on a data lake vs. data warehouse. Read Many of the preferred platforms for analytics fall into one of these two categories.

Data Lake 59

Data Lake Data Warehouse Hadoop Raw Data 59

Snowflake

APRIL 22, 2025

To pile onto the challenge, the vast majority of any companys data is unstructured think PDFs, videos and images. So to capitalize on AI's potential, you need a platform that supports structured and unstructured data without compromising accuracy, quality and governance.

IT 59

IT Unstructured Data Government Cloud 59

Knowledge Hut

APRIL 23, 2024

Two popular approaches that have emerged in recent years are data warehouse and big data. While both deal with large datasets, but when it comes to data warehouse vs big data, they have different focuses and offer distinct advantages.

Data Warehouse 52

Data Warehouse Big Data Unstructured Data Hadoop 52

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

Sync Computing

NOVEMBER 7, 2024

Data volume and velocity, governance, structure, and regulatory requirements have all evolved and continue to. Despite these limitations, data warehouses, introduced in the late 1980s based on ideas developed even earlier, remain in widespread use today for certain business intelligence and data analysis applications.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Unstructured Data 52

Data Engineering Podcast

JUNE 26, 2022

Datafold integrates with all major data warehouses as well as frameworks such as Airflow & dbt and seamlessly plugs into CI workflows. Unstruk is the DataOps platform for your unstructured data. The options for ingesting, organizing, and curating unstructured files are complex, expensive, and bespoke.

Datasets 130

Datasets Unstructured Data Metadata MongoDB 130

Grouparoo

JANUARY 11, 2022

This article looks at the options available for storing and processing big data, which is too large for conventional databases to handle. There are two main options available, a data lake and a data warehouse. What is a Data Warehouse? What is a Data Lake?

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Data Engineering Weekly

FEBRUARY 9, 2025

[link] QuantumBlack: Solving data quality for gen AI applications Unstructured data processing is a top priority for enterprises that want to harness the power of GenAI. It brings challenges in data processing and quality, but what data quality means in unstructured data is a top question for every organization.

Data Engineering 57

Data Engineering Data Engineer Engineering Unstructured Data 57

U-Next

SEPTEMBER 7, 2022

The terms “ Data Warehouse ” and “ Data Lake ” may have confused you, and you have some questions. Structuring data refers to converting unstructured data into tables and defining data types and relationships based on a schema. What is Data Warehouse? .

Data Lake 52

Data Lake Data Warehouse Unstructured Data Amazon Web Services 52

Analytics Vidhya

FEBRUARY 25, 2023

Introduction A data lake is a centralized and scalable repository storing structured and unstructured data. The need for a data lake arises from the growing volume, variety, and velocity of data companies need to manage and analyze.

Cloud Storage 162

Cloud Storage Data Lake Cloud Unstructured Data 162

phData: Data Engineering

NOVEMBER 8, 2024

Versioning also ensures a safer experimentation environment, where data scientists can test new models or hypotheses on historical data snapshots without impacting live data. Note : Cloud Data warehouses like Snowflake and Big Query already have a default time travel feature. FAQs What is a Data Lakehouse?

Architecture 52

Architecture Systems Data Lake Google Cloud 52

Cloudera

NOVEMBER 25, 2020

Sample and treatment history data is mostly structured, using analytics engines that use well-known, standard SQL. Interview notes, patient information, and treatment history is a mixed set of semi-structured and unstructured data, often only accessed using proprietary, or less known, techniques and languages.

Data Warehouse 59

Data Warehouse Unstructured Data Medical Pharmaceutical 59

Data Engineering Podcast

JUNE 19, 2022

Datafold integrates with all major data warehouses as well as frameworks such as Airflow & dbt and seamlessly plugs into CI workflows. Unstruk is the DataOps platform for your unstructured data. The options for ingesting, organizing, and curating unstructured files are complex, expensive, and bespoke.

Metadata 130

Metadata Unstructured Data MongoDB MySQL 130

Cloudera

JUNE 11, 2024

By leveraging an organization’s proprietary data, GenAI models can produce highly relevant and customized outputs that align with the business’s specific needs and objectives. Structured data is highly organized and formatted in a way that makes it easily searchable in databases and data warehouses.

Unstructured Data 93

Unstructured Data Pharmaceutical Banking Manufacturing 93

Monte Carlo

AUGUST 25, 2023

Different vendors offering data warehouses, data lakes, and now data lakehouses all offer their own distinct advantages and disadvantages for data teams to consider. 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

Cloudera

SEPTEMBER 10, 2018

Among the many reasons that a majority of large enterprises have adopted Cloudera Data Warehouse as their modern analytic platform of choice is the incredible ecosystem of partners that have emerged over recent years. Informatica’s Big Data Manager and Qlik’s acquisition of Podium Data are just 2 examples.

Data Warehouse 43

Data Warehouse BI Unstructured Data Data 43

Snowflake

FEBRUARY 13, 2025

Interoperable storage: Snowflake enables customers to access and process structured, semi-structured and unstructured data seamlessly, without silos or delays. Unique automations and optimizations include encryption by default, built-in storage compression and fast access to data even at petabyte scale.

Management 93

Management Government Cloud Unstructured Data 93

Cloudera

SEPTEMBER 17, 2018

These trends and demands lead to stress for existing data warehouse solutions – scale, efficiency, security integrations, IT budgets, ease of access. Cloudera recently launched Cloudera Data Warehouse, a modern data warehousing solution.

Data Warehouse 53

Data Warehouse SQL Portfolio MySQL 53

Data Engineering Weekly

OCTOBER 11, 2024

This centralized model mirrors early monolithic data warehouse systems like Teradata, Oracle Exadata, and IBM Netezza. These systems provided centralized data storage and processing at the cost of agility. Data engineering followed a similar path.

Manufacturing 109

Manufacturing Transportation Data Warehouse Unstructured Data 109

Monte Carlo

MARCH 3, 2025

Prior to data powering valuable data products like machine learning models and real-time marketing applications, data warehouses were mainly used to create charts in binders that sat off to the side of board meetings. In other words, the four ways data + AI products break: in the data, system, code, or model.

Unstructured Data 52

Unstructured Data Data Cloud Computing Banking 52

Cloudera

OCTOBER 29, 2020

Adding to these innovations, we most recently released CDP Data Visualization (DV) — A native visualization tool built from our acquisition of Arcadia Data that augments data exploration and analytics across the lifecycle to more effectively share insights across the business. Accelerate Collaboration Across The Lifecycle.

Machine Learning 111

Machine Learning Data Warehouse Unstructured Data Government 111

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?

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

Data Engineering Weekly

JULY 21, 2024

[link] Manuel Faysse: ColPali - Efficient Document Retrieval with Vision Language Models 👀 80% of enterprise data exists in difficult-to-use formats like HTML, PDF, CSV, PNG, PPTX, and more. In the data warehouse, the programming abstraction standard is around SQL and dataframes.

Data Engineering 117

Data Engineering Data Engineer Engineering Generalist 117

Data Engineering Weekly

MARCH 5, 2025

Major data warehouse providers (Snowflake, Databricks) have released their flavors of REST catalogs, leading to compatibility issues and potential vendor lock-in. The Catalog Conundrum: Beyond Structured Data The role of the catalog is evolving. If not handled correctly, managing this metadata can become a bottleneck.

Hadoop 57

Hadoop Metadata Data Ingestion Data Governance 57

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 98

Data Engineering Data Engineer Engineering Data Lake 98

Cloudera

APRIL 1, 2024

We scored the highest in hybrid, intercloud, and multi-cloud capabilities because we are the only vendor in the market with a true hybrid data platform that can run on any cloud including private cloud to deliver a seamless, unified experience for all data, wherever it lies.

Cloud 105

Cloud Unstructured Data Metadata Government 105

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

Data Engineering Podcast

JUNE 12, 2022

Datafold integrates with all major data warehouses as well as frameworks such as Airflow & dbt and seamlessly plugs into CI workflows. Unstruk is the DataOps platform for your unstructured data. The options for ingesting, organizing, and curating unstructured files are complex, expensive, and bespoke.

Metadata 100

Metadata Unstructured Data Business Intelligence MongoDB 100

Monte Carlo

FEBRUARY 12, 2024

Today, this first-party data mostly lives in two types of data repositories. If it is structured data then it’s often stored in a table within a modern database, data warehouse or lakehouse. If it’s unstructured data, then it’s often stored as a vector in a namespace within a vector database.

Database 72

Database Unstructured Data Data Pipeline Metadata 72

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

Snowflake

MAY 9, 2024

From its start with efficient batch processing with data warehouses for descriptive analytics, and the inclusion of streaming data in real time to build recommendations, we find ourselves at the forefront of a new stage of evolution: generative AI (gen AI).

Unstructured Data 121

Unstructured Data Manufacturing Retail Data Warehouse 121

Cloudera

JANUARY 28, 2022

Are you seeking to improve the speed of regulatory reporting, enhance credit decisioning, personalize the customer journey, reduce false positives, reduce data warehouse costs? What data do I need to achieve these objectives? What are your business goals, what are you trying to achieve?

Cloud 115

Cloud Banking Data Governance Government 115

Striim

SEPTEMBER 11, 2024

The approach to this processing depends on the data pipeline architecture, specifically whether it employs ETL (Extract, Transform, Load) or ELT (Extract, Load, Transform) processes. This method is advantageous when dealing with structured data that requires pre-processing before storage. In what format will the final data be stored?

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

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

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.

Education 64

Education Unstructured Data Data Lake Data Warehouse 64

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

Data Engineering Podcast

JULY 31, 2022

Summary Data lineage is the roadmap for your data platform, providing visibility into all of the dependencies for any report, machine learning model, or data warehouse table that you are working with. What is involved in integrating Manta with an organization’s data systems?

IT 100

IT Metadata MongoDB MySQL 100