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 117

Data Lake Data Warehouse Metadata Data Architecture 117

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 125

Data Lake Snapshot Metadata Data Architecture 125

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 113

Data Warehouse Data Lake Cost-Benefit Structured Data 113

BI-Survey

AUGUST 21, 2020

Especially in times of rapidly changing markets, decision-support systems should promote the quickest possible knowledge growth. Advanced analytics and new ways of working with data also create new requirements that surpass the traditional concepts. But what are the right measures to make the data warehouse and BI fit for the future?

Data Warehouse 98

Data Warehouse Data Lake Data Governance Data Architecture 98

Jet Global

NOVEMBER 5, 2020

The company’s market power is based largely on its ability to promote the “stack”—that is, to position the entire suite of Microsoft products as a holistic solution to customer problems. OLAP reporting has traditionally relied on a data warehouse. Option 3: Azure Data Lakes. Data lakes are not a mature technology.

Data Lake 98

Data Lake OLAP Data Warehouse Unstructured Data 98

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 113

Data Lake Marketing Data Processing Management 113

Jet Global

SEPTEMBER 4, 2020

For more sophisticated multidimensional reporting functions, however, a more advanced approach to staging data is required. The Data Warehouse Approach. Data warehouses gained momentum back in the early 1990s as companies dealing with growing volumes of data were seeking ways to make analytics faster and more accessible.

Data Lake 88

Data Lake OLAP Data Warehouse Unstructured Data 88

AWS Big Data

JUNE 9, 2023

A modern data architecture enables companies to ingest virtually any type of data through automated pipelines into a data lake, which provides highly durable and cost-effective object storage at petabyte or exabyte scale.

Data Lake 128

Data Lake Metadata Statistics Optimization 128

AWS Big Data

JULY 21, 2023

This leads to having data across many instances of data warehouses and data lakes using a modern data architecture in separate AWS accounts. We recently announced the integration of Amazon Redshift data sharing with AWS Lake Formation.

Data Lake 98

Data Lake Data Warehouse Marketing Management 98

AWS Big Data

MARCH 27, 2023

Amazon Redshift Serverless makes it simple to run and scale analytics without having to manage your data warehouse infrastructure. Solution overview Let’s say that your company has two departments: marketing and finance. Choose Remove next to the marketing tag. Choose Save changes.

Data Warehouse 98

Data Warehouse Management Snapshot Data Lake 98

AWS Big Data

APRIL 6, 2023

In this post, Morningstar’s Data Lake Team Leads discuss how they utilized tag-based access control in their data lake with AWS Lake Formation and enabled similar controls in Amazon Redshift. We realized we needed a data warehouse to cater to all of these consumer requirements, so we evaluated Amazon Redshift.

Data Warehouse 98

Data Warehouse Data Lake Management Data-driven 98

CIO Business Intelligence

AUGUST 18, 2022

Previously, Walgreens was attempting to perform that task with its data lake but faced two significant obstacles: cost and time. Those challenges are well-known to many organizations as they have sought to obtain analytical knowledge from their vast amounts of data. Lakehouses redeem the failures of some data lakes.

Data Lake 140

Data Lake Data Warehouse Unstructured Data Business Intelligence 140

AWS Big Data

JUNE 23, 2023

Events and many other security data types are stored in Imperva’s Threat Research Multi-Region data lake. Imperva harnesses data to improve their business outcomes. As part of their solution, they are using Amazon QuickSight to unlock insights from their data.

Data Lake 95

Data Lake Dashboards Cost-Benefit Data Warehouse 95

Jet Global

JULY 2, 2019

The sheer scale of data being captured by the modern enterprise has necessitated a monumental shift in how that data is stored. From the humble database through to data warehouses , data stores have grown both in scale and complexity to keep pace with the businesses they serve, and the data analysis now required to remain competitive.

Data Lake 73

Data Lake Data Warehouse Big Data Machine Learning 73

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

DataKitchen

DECEMBER 7, 2021

This book is not available until January 2022, but considering all the hype around the data mesh, we expect it to be a best seller. In the book, author Zhamak Dehghani reveals that, despite the time, money, and effort poured into them, data warehouses and data lakes fail when applied at the scale and speed of today’s organizations.

Data-driven 246

Data-driven Data Governance Big Data Data Science 246

DataKitchen

AUGUST 27, 2021

During the product launch, everyone in the sales and marketing organizations is hyper-focused on business development. Marketing invests heavily in multi-level campaigns, primarily driven by data analytics. The data team must be able to respond rapidly and with a high degree of quality and certainty to user requests.

Analytics 246

Analytics Sales Testing Cost-Benefit 246

AWS Big Data

JANUARY 6, 2025

Amazon AppFlow automatically encrypts data in motion, and allows you to restrict data from flowing over the public internet for SaaS applications that are integrated with AWS PrivateLink , reducing exposure to security threats. He has worked with building data warehouses and big data solutions for over 13 years.

Analytics 98

Analytics Data Warehouse Big Data Metrics 98

CIO Business Intelligence

NOVEMBER 25, 2022

Today, more than 90% of its applications run in the cloud, with most of its data is housed and analyzed in a homegrown enterprise data warehouse. Like many CIOs, Carhartt’s top digital leader is aware that data is the key to making advanced technologies work. Today, we backflush our data lake through our data warehouse.

Data Lake 128

Data Lake Data Warehouse Unstructured Data Data Architecture 128

AWS Big Data

NOVEMBER 29, 2023

In 2013, Amazon Web Services revolutionized the data warehousing industry by launching Amazon Redshift , the first fully-managed, petabyte-scale, enterprise-grade cloud data warehouse. Amazon Redshift made it simple and cost-effective to efficiently analyze large volumes of data using existing business intelligence tools.

Data Warehouse 129

Data Warehouse Analytics Data Lake Machine Learning 129

AWS Big Data

JANUARY 15, 2025

cycle_end"', "sagemakedatalakeenvironment_sub_db", ctas_approach=False) A similar approach is used to connect to shared data from Amazon Redshift, which is also shared using Amazon DataZone. AWS Database Migration Service (AWS DMS) is used to securely transfer the relevant data to a central Amazon Redshift cluster.

IoT 109

IoT Machine Learning Metadata Data-driven 109

AWS Big Data

JUNE 25, 2024

In today’s data-driven business landscape, organizations collect a wealth of data across various touch points and unify it in a central data warehouse or a data lake to deliver business insights. This external DLO acts as a storage container, housing metadata for your federated Redshift data.

Data Lake 120

Data Lake Cost-Benefit Data-driven Data Warehouse 120

CIO Business Intelligence

JUNE 9, 2022

Lately, however, the term has been adopted by marketing teams, and many of the data management platforms vendors currently offer are tuned to their needs. In these instances, data feeds come largely from various advertising channels, and the reports they generate are designed to help marketers spend wisely.

Management 144

Management Advertising Data Lake Sales 144

CIO Business Intelligence

JUNE 29, 2022

Azure Data Factory. Azure Data Explorer is used to store and query data in services such as Microsoft Purview, Microsoft Defender for Endpoint, Microsoft Sentinel, and Log Analytics in Azure Monitor. Azure Data Lake Analytics.

Data Lake 116

Data Lake Analytics Data Warehouse Machine Learning 116

Cloudera

JANUARY 11, 2021

Requests to Central IT for data warehousing services can take weeks or months to deliver. Central IT teams at large organizations face a proliferation of IT projects arising from the complexities of markets and from the needs of internal lines of business (LoBs). Cloudera customers have described the data challenges they face.

Data Warehouse 63

Data Warehouse Data Lake Cost-Benefit Machine Learning 63

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 57

Data Warehouse Data Lake Unstructured Data Optimization 57

Sisense

NOVEMBER 12, 2020

Data warehouse vs. databases Traditional vs. Cloud Explained Cloud data warehouses in your data stack A data-driven future powered by the cloud. We live in a world of data: There’s more of it than ever before, in a ceaselessly expanding array of forms and locations. Data warehouse vs. databases.

Data Warehouse 52

Data Warehouse Data Lake OLAP Data-driven 52

Boris Evelson

JUNE 14, 2023

No matter what technology foundation you’re using – a data lake, a data warehouse, data fabric, data mesh, etc. – BI applications are where business users consume data and turn it into actionable insights and decisions. The BI market has […]

Business Intelligence 98

Business Intelligence Data Lake Data Warehouse Data-driven 98

Smart Data Collective

OCTOBER 27, 2021

The data is ever-increasing, and getting the deepest analytics about their business activities requires technical tools, analysts, and data scientists to explore and gain insight from large data sets. Interactive analytics applications make it easy to get and build reports from large unstructured data sets fast and at scale.

Interactive 130

Interactive Analytics Unstructured Data Data Warehouse 130

CIO Business Intelligence

APRIL 25, 2024

Currently, a handful of startups offer “reverse” extract, transform, and load (ETL), in which they copy data from a customer’s data warehouse or data platform back into systems of engagement where business users do their work. Sharing Customer 360 insights back without data replication.

Data Integration 119

Data Integration Data Lake Data Warehouse Metadata 119

IBM Big Data Hub

FEBRUARY 2, 2023

In today’s world, data warehouses are a critical component of any organization’s technology ecosystem. The rise of cloud has allowed data warehouses to provide new capabilities such as cost-effective data storage at petabyte scale, highly scalable compute and storage, pay-as-you-go pricing and fully managed service delivery.

Data Warehouse 56

Data Warehouse Cost-Benefit Unstructured Data Data Architecture 56

IBM Big Data Hub

JULY 5, 2023

Data Lakes have been around for well over a decade now, supporting the analytic operations of some of the largest world corporations. Such data volumes are not easy to move, migrate or modernize. The challenges of a monolithic data lake architecture Data lakes are, at a high level, single repositories of data at scale.

Data Lake 60

Data Lake Metadata Cost-Benefit Data Warehouse 60

AWS Big Data

DECEMBER 21, 2023

smava believes in and takes advantage of data-driven decisions in order to become the market leader. The Data Platform team is responsible for supporting data-driven decisions at smava by providing data products across all departments and branches of the company.

Data Lake 113

Data Lake Data Warehouse Data-driven B2B 113

CIO Business Intelligence

APRIL 25, 2022

The data lakehouse is a relatively new data architecture concept, first championed by Cloudera, which offers both storage and analytics capabilities as part of the same solution, in contrast to the concepts for data lake and data warehouse which, respectively, store data in native format, and structured data, often in SQL format.

Recreation/Entertainment 119

Recreation/Entertainment Data Lake Data Warehouse Unstructured Data 119

CIO Business Intelligence

MARCH 29, 2024

“Generative AI is becoming the virtual knowledge worker with the ability to connect different data points, summarize and synthesize insights in seconds, allowing us to focus on more high-value-add tasks,” says Ritu Jyoti, group vice president of worldwide AI and automation market research and advisory services at IDC. “It

Data Lake 134

Data Lake Machine Learning Data Warehouse Unstructured Data 134

IBM Big Data Hub

APRIL 24, 2023

Data is reported from one central repository, enabling management to draw more meaningful business insights and make faster, better decisions. By running reports on historical data, a data warehouse can clarify what systems and processes are working and what methods need improvement.

Data Warehouse 88

Data Warehouse Data Lake Cost-Benefit Big Data 88

Sisense

JULY 8, 2020

Dealing with Data is your window into the ways Data Teams are tackling the challenges of this new world to help their companies and their customers thrive. In recent years we’ve seen data become vastly more available to businesses. This has allowed companies to become more and more data driven in all areas of their business.

Data Warehouse 90

Data Warehouse Data Lake Data-driven Cost-Benefit 90