AWS Big Data

AUGUST 15, 2024

Unlocking the true value of data often gets impeded by siloed information. Traditional data management—wherein each business unit ingests raw data in separate data lakes or warehouses—hinders visibility and cross-functional analysis. Business units access clean, standardized data.

Data Lake 102

Data Lake Data Warehouse Data Governance Publishing 102

Smart Data Collective

AUGUST 28, 2021

Data lakes and data warehouses are probably the two most widely used structures for storing data. Data Warehouses and Data Lakes in a Nutshell. A data warehouse is used as a central storage space for large amounts of structured data coming from various sources.

Data Lake 140

Data Lake Data Warehouse Unstructured Data Structured Data 140

KDnuggets

OCTOBER 30, 2023

A comparative overview of data warehouses, data lakes, and data marts to help you make informed decisions on data storage solutions for your data architecture.

Data Lake 129

Data Lake Data Warehouse Data Architecture 129

AWS Big Data

OCTOBER 19, 2023

Data lakes and data warehouses are two of the most important data storage and management technologies in a modern data architecture. Data lakes store all of an organization’s data, regardless of its format or structure.

Data Lake 115

Data Lake Data Warehouse Visualization Snapshot 115

Smart Data Collective

SEPTEMBER 23, 2020

The market for data warehouses is booming. While there is a lot of discussion about the merits of data warehouses, not enough discussion centers around data lakes. We talked about enterprise data warehouses in the past, so let’s contrast them with data lakes. Data Warehouse.

Data Lake 106

Data Lake Data Warehouse Unstructured Data Big Data 106

AWS Big Data

NOVEMBER 8, 2024

Amazon Redshift is a fast, fully managed cloud data warehouse that makes it cost-effective to analyze your data using standard SQL and business intelligence tools. Customers use data lake tables to achieve cost effective storage and interoperability with other tools.

Data Lake 90

Data Lake Data Warehouse Optimization Testing 90

ScienceSoft

JULY 8, 2024

Learn about the difference between a data lake and a data warehouse, and define how to structure your big data solution in accordance with your business needs.

Data Lake 52

Data Lake Data Warehouse Big Data 52

Data Virtualization

APRIL 21, 2022

Reading Time: 3 minutes First we had data warehouses, then came data lakes, and now the new kid on the block is the data lakehouse. But what is a data lakehouse and why should we develop one? In a way, the name describes what.

Data Lake 59

Data Lake Data Warehouse Data Integration Management 59

TDAN

SEPTEMBER 14, 2021

Data lake is a newer IT term created for a new category of data store. But just what is a data lake? According to IBM, “a data lake is a storage repository that holds an enormous amount of raw or refined data in native format until it is accessed.” That makes sense. I think the […].

Data Lake 91

Data Lake Data Warehouse IT Data Strategy 91

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.

Data Lake 178

Data Lake Unstructured Data Management Analytics 178

Sisense

APRIL 9, 2021

Until then though, they don’t necessarily want to spend the time and resources necessary to create a schema to house this data in a traditional data warehouse. Instead, businesses are increasingly turning to data lakes to store massive amounts of unstructured data. The rise of data warehouses and data lakes.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Structured Data 52

Analytics Vidhya

JULY 29, 2022

This article was published as a part of the Data Science Blogathon. Introduction We are all pretty much familiar with the common modern cloud data warehouse model, which essentially provides a platform comprising a data lake (based on a cloud storage account such as Azure Data Lake Storage Gen2) AND a data warehouse compute engine […].

Data Lake 388

Data Lake Data Warehouse Analytics Data Science 388

AWS Big Data

OCTOBER 1, 2024

Amazon Redshift enables you to efficiently query and retrieve structured and semi-structured data from open format files in Amazon S3 data lake without having to load the data into Amazon Redshift tables. Amazon Redshift extends SQL capabilities to your data lake, enabling you to run analytical queries.

Data Lake 98

Data Lake Statistics Broadcasting Optimization 98

ScienceSoft

JULY 8, 2024

What is a data warehouse? Definition and purpose| DWH vs big data warehouse vs a data lake | DWH trends to consider for your business | DWH pricing

Data Warehouse 52

Data Warehouse Data Lake Big Data 52

AWS Big Data

AUGUST 31, 2023

Amazon Redshift is a fast, fully managed petabyte-scale cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools. Amazon Redshift also supports querying nested data with complex data types such as struct, array, and map.

Data Lake 100

Data Lake Data Warehouse Metadata Data Architecture 100

IBM Big Data Hub

NOVEMBER 15, 2018

If you’ve heard the debate among IT professionals about data lakes versus data warehouses, you might be wondering which is better for your organization. You might even be wondering how these two approaches are different at all.

Data Lake 90

Data Lake Data Warehouse IT 90

AWS Big Data

MAY 30, 2024

Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data. Solution overview Amazon Redshift is an industry-leading cloud data warehouse.

Data Warehouse 92

Data Warehouse Data Lake Cost-Benefit Structured Data 92

David Menninger's Analyst Perspectives

OCTOBER 31, 2024

I previously wrote about the importance of open table formats to the evolution of data lakes into data lakehouses. The concept of the data lake was initially proposed as a single environment where data could be combined from multiple sources to be stored and processed to enable analysis by multiple users for multiple purposes.

Data Lake 130

Data Lake Unstructured Data Data Warehouse Software 130

AWS Big Data

APRIL 3, 2024

licensed, 100% open-source data table format that helps simplify data processing on large datasets stored in data lakes. Data engineers use Apache Iceberg because it’s fast, efficient, and reliable at any scale and keeps records of how datasets change over time.

Data Lake 100

Data Lake Snapshot Metadata Data Architecture 100

AWS Big Data

JULY 31, 2024

In the current industry landscape, data lakes have become a cornerstone of modern data architecture, serving as repositories for vast amounts of structured and unstructured data. Maintaining data consistency and integrity across distributed data lakes is crucial for decision-making and analytics.

Data Lake 107

Data Lake Marketing Data Processing Management 107

Data Virtualization

OCTOBER 18, 2022

The post The Data Warehouse is Dead, Long Live the Data Warehouse, Part I appeared first on Data Virtualization blog - Data Integration and Modern Data Management Articles, Analysis and Information. In times of potentially troublesome change, the apparent paradox and inner poetry of these.

Data Warehouse 98

Data Warehouse ROI Data Integration Internet of Things 98

Smart Data Collective

MARCH 30, 2022

Azure Data Lake Storage Gen2 is based on Azure Blob storage and offers a suite of big data analytics features. If you don’t understand the concept, you might want to check out our previous article on the difference between data lakes and data warehouses. Determine your preparedness.

Data Lake 106

Data Lake Cost-Benefit Data Warehouse Big Data 106

ScienceSoft

FEBRUARY 28, 2020

Learn about the difference between a data lake and a big data warehouse, and define how to structure your big data solution in accordance with your business needs.

Data Lake 64

Data Lake Data Warehouse Big Data 64

AWS Big Data

JUNE 10, 2024

One of the key challenges in modern big data management is facilitating efficient data sharing and access control across multiple EMR clusters. Organizations have multiple Hive data warehouses across EMR clusters, where the metadata gets generated. Test access using SageMaker Studio in the consumer account.

Data Lake 90

Data Lake Metadata Data Warehouse Data Processing 90

AWS Big Data

JUNE 21, 2023

These types of queries are suited for a data warehouse. The goal of a data warehouse is to enable businesses to analyze their data fast; this is important because it means they are able to gain valuable insights in a timely manner. Amazon Redshift is fully managed, scalable, cloud data warehouse.

Data Warehouse 84

Data Warehouse Data Lake OLAP Cost-Benefit 84

AWS Big Data

JUNE 10, 2024

Solving the small file problem and improving query performance In modern data architectures, stream processing engines such as Amazon EMR are often used to ingest continuous streams of data into data lakes using Apache Iceberg. They decided to focus on four runtime engines. 5 seconds $0.08 8 seconds $0.07 8 seconds $0.02

Data Lake 116

Data Lake Metadata Snapshot Analytics 116

AWS Big Data

MARCH 10, 2023

Since the deluge of big data over a decade ago, many organizations have learned to build applications to process and analyze petabytes of data. Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats.

Data Lake 110

Data Lake Sales Data Warehouse Snapshot 110

David Menninger's Analyst Perspectives

JANUARY 22, 2021

Organizations are dealing with exponentially increasing data that ranges broadly from customer-generated information, financial transactions, edge-generated data and even operational IT server logs. A combination of complex data lake and data warehouse capabilities are required to leverage this data.

Data Lake 269

Data Lake IT Data Warehouse Data Governance 269

DataCamp

JANUARY 6, 2020

Understand the differences between the two most popular options for storing big data.

Data Warehouse 134

Data Warehouse Data Lake Big Data 134

AWS Big Data

APRIL 19, 2023

In this post, we look at three key challenges that customers face with growing data and how a modern data warehouse and analytics system like Amazon Redshift can meet these challenges across industries and segments. This performance innovation allows Nasdaq to have a multi-use data lake between teams.

Data Warehouse 59

Data Warehouse Data Lake Unstructured Data Optimization 59

BI-Survey

AUGUST 21, 2020

But what are the right measures to make the data warehouse and BI fit for the future? Can the basic nature of the data be proactively improved? The following insights came from a global BARC survey into the current status of data warehouse modernization. What role do technology and IT infrastructure play?

Data Warehouse 98

Data Warehouse Data Lake Data Governance Data Architecture 98

David Menninger's Analyst Perspectives

SEPTEMBER 16, 2021

It has a drag and drop visual interface and can connect to databases, enterprise data warehouses, data lakes, cloud storage, business applications and social media. The platform also supports push-down processing for data prep and ETL inside databases to minimize data movement and optimize performance.

Data Science 341

Data Science Data Lake Data mining Deep Learning 341

AWS Big Data

AUGUST 22, 2024

In this post, we discuss how the Kaplan data engineering team implemented data integration from the Salesforce application to Amazon Redshift. Solution overview The high-level data flow starts with the source data stored in Amazon S3 and then integrated into Amazon Redshift using various AWS services.

Data Warehouse 104

Data Warehouse Data Lake Data Integration Management 104

Jet Global

NOVEMBER 5, 2020

OLAP reporting has traditionally relied on a data warehouse. Again, this entails creating a copy of the transactional data in the ERP system, but it also involves some preprocessing of data into so-called “cubes” so that you can retrieve aggregate totals and present them much faster. Option 3: Azure Data Lakes.

Data Lake 98

Data Lake OLAP Data Warehouse Unstructured Data 98