AWS Big Data

NOVEMBER 16, 2023

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

Enterprise 83

Enterprise Data Warehouse Snapshot Cost-Benefit 83

AWS Big Data

MARCH 2, 2023

Iceberg has become very popular for its support for ACID transactions in data lakes and features like schema and partition evolution, time travel, and rollback. and later supports the Apache Iceberg framework for data lakes. AWS Glue 3.0 The following diagram illustrates the solution architecture.

Data Lake 116

Data Lake Data Processing Metadata Snapshot 116

AWS Big Data

MAY 24, 2023

When you build your transactional data lake using Apache Iceberg to solve your functional use cases, you need to focus on operational use cases for your S3 data lake to optimize the production environment. This property is set to true by default. availability.

Data Lake 81

Data Lake Snapshot Metadata Optimization 81

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

IBM Big Data Hub

APRIL 25, 2023

We also made the case that query and reporting, provided by big data engines such as Presto, need to work with the Spark infrastructure framework to support advanced analytics and complex enterprise data decision-making. To do so, Presto and Spark need to readily work with existing and modern data warehouse infrastructures.

Optimization 57

Optimization Strategy Data Warehouse Cost-Benefit 57

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. What was at first a data stream has morphed into a data river as enterprise businesses are harvesting reams of data from every conceivable input across every conceivable business function.

Data Lake 73

Data Lake Data Warehouse Big Data Machine Learning 73

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 100

Data Warehouse Data Lake Analytics Machine Learning 100

DataKitchen

AUGUST 19, 2021

Data mesh and DataOps provide the organization, enterprise architecture, and workflow automation that together enable a relatively small data team to address the analytics needs of hundreds of active business users. Figure 1: Data requirements for phases of the drug product lifecycle. The new Recipes run, and BOOM!

Data Warehouse 246

Data Warehouse Data Lake Manufacturing Testing 246

erwin

SEPTEMBER 3, 2020

Why should you integrate data governance (DG) and enterprise architecture (EA)? Two of the biggest challenges in creating a successful enterprise architecture initiative are: collecting accurate information on application ecosystems and maintaining the information as application ecosystems change.

Data Governance 144

Data Governance Enterprise Risk Data Lake 144

AWS Big Data

NOVEMBER 10, 2023

This integration expands the possibilities for AWS analytics and machine learning (ML) solutions, making the data warehouse accessible to a broader range of applications. Your applications can seamlessly read from and write to your Amazon Redshift data warehouse while maintaining optimal performance and transactional consistency.

Data Processing 91

Data Processing Data Lake Data Warehouse Optimization 91

erwin

JUNE 7, 2022

Designing databases for data warehouses or data marts is intrinsically much different than designing for traditional OLTP systems. Accordingly, data modelers must embrace some new tricks when designing data warehouses and data marts. Figure 1: Pricing for a 4 TB data warehouse in AWS.

Data Warehouse 52

Data Warehouse Modeling Sales Data Lake 52

Cloudera

JUNE 2, 2022

Since 2015, the Cloudera DataFlow team has been helping the largest enterprise organizations in the world adopt Apache NiFi as their enterprise standard data movement tool. What is the modern data stack? In the modern data stack, there is a diverse set of destinations where data needs to be delivered.

Enterprise 102

Enterprise Data Lake Data Collection Data-driven 102

AWS Big Data

FEBRUARY 16, 2024

Many customers are extending their data warehouse capabilities to their data lake with Amazon Redshift. They are looking to further enhance their security posture where they can enforce access policies on their data lakes based on Amazon Simple Storage Service (Amazon S3).

Data Lake 97

Data Lake Data Warehouse Testing Business Objectives 97

CIO Business Intelligence

JUNE 23, 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.

Data Lake 97

Data Lake Data Warehouse Machine Learning Cost-Benefit 97

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.

Data Lake 92

Data Lake Data Warehouse Machine Learning Cost-Benefit 92

CIO Business Intelligence

JULY 13, 2022

Since 2015, the Cloudera DataFlow team has been helping the largest enterprise organizations in the world adopt Apache NiFi as their enterprise standard data movement tool. What is the modern data stack? In the modern data stack, there is a diverse set of destinations where data needs to be delivered.

Enterprise 73

Enterprise Data Lake Data Collection Data-driven 73

AWS Big Data

MAY 3, 2023

In today’s data-driven business environment, organizations face the challenge of efficiently preparing and transforming large amounts of data for analytics and data science purposes. Businesses need to build data warehouses and data lakes based on operational data.

Data Lake 80

Data Lake Data Warehouse Data-driven Optimization 80

AWS Big Data

NOVEMBER 29, 2023

dbt is an open source, SQL-first templating engine that allows you to write repeatable and extensible data transforms in Python and SQL. dbt is predominantly used by data warehouses (such as Amazon Redshift ) customers who are looking to keep their data transform logic separate from storage and engine.

Data Lake 102

Data Lake Management Metrics Data Warehouse 102

AWS Big Data

MARCH 7, 2024

At the same time, they need to optimize operational costs to unlock the value of this data for timely insights and do so with a consistent performance. With this massive data growth, data proliferation across your data stores, data warehouse, and data lakes can become equally challenging.

Data Lake 112

Data Lake Analytics Dashboards Metrics 112

CIO Business Intelligence

OCTOBER 13, 2023

Data architect role Data architects are senior visionaries who translate business requirements into technology requirements and define data standards and principles, often in support of data or digital transformations. Data architects are frequently part of a data science team and tasked with leading data system projects.

Data Architecture 132

Data Architecture Data Warehouse Statistics Visualization 132

DataKitchen

NOVEMBER 4, 2021

It expands beyond tools and data architecture and views the data organization from the perspective of its processes and workflows. The DataKitchen Platform is a “ process hub” that masters and optimizes those processes. Cloud computing has made it much easier to integrate data sets, but that’s only the beginning.

Data Processing 246

Data Processing Data Lake Cost-Benefit Testing 246

AWS Big Data

NOVEMBER 13, 2023

KEY003 | Swami Sivasubramanian (Vice President, Data and AI at AWS) | Nov. 29 | 8:30 AM – 10:30 AM (PDT) A powerful relationship between humans, data, and AI is unfolding right before us. 11:30 AM – 12:30 PM (PDT) Ceasars Forum ANT318 | Accelerate innovation with end-to-end serverless data architecture.

Analytics 112

Analytics Data Lake Data Warehouse Data-driven 112

AWS Big Data

OCTOBER 20, 2023

Today, we are pleased to announce new AWS Glue connectors for Azure Blob Storage and Azure Data Lake Storage that allow you to move data bi-directionally between Azure Blob Storage, Azure Data Lake Storage, and Amazon Simple Storage Service (Amazon S3). option("header","true").load("wasbs://yourblob@youraccountname.blob.core.windows.net/loadingtest-input/100mb")

Data Lake 83

Data Lake Big Data Consulting Data Warehouse 83

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

AWS Big Data

JANUARY 17, 2024

With Amazon EMR 6.15, we launched AWS Lake Formation based fine-grained access controls (FGAC) on Open Table Formats (OTFs), including Apache Hudi, Apache Iceberg, and Delta lake. Many large enterprise companies seek to use their transactional data lake to gain insights and improve decision-making.

Data Lake 92

Data Lake Snapshot Big Data Data-driven 92

Cloudera

OCTOBER 13, 2020

On September 24, 2019, Cloudera launched CDP Public Cloud (CDP-PC) as the first step in delivering the industry’s first Enterprise Data Cloud. CDP Machine Learning: a kubernetes-based service that allows data scientists to deploy collaborative workspaces with secure, self-service access to enterprise data.

Data Warehouse 94

Data Warehouse Machine Learning Visualization Data Lake 94

AWS Big Data

NOVEMBER 29, 2023

Knowledge Bases works with popular vector databases and engines including Amazon OpenSearch Serverless , Redis Enterprise Cloud, and Pinecone, with support for Amazon Aurora and MongoDB coming soon. You also need services to store data for analysis and machine learning (ML) like Amazon Simple Storage Service (Amazon S3).

Data Warehouse 111

Data Warehouse Data Lake Data Integration Dashboards 111

AWS Big Data

MARCH 7, 2023

Flexible and easy to use – The solutions should provide less restrictive, easy-to-access, and ready-to-use data. They should also provide optimal performance with low or no tuning. A data hub contains data at multiple levels of granularity and is often not integrated.

Analytics 69

Analytics Data Warehouse Data Lake Metadata 69

AWS Big Data

FEBRUARY 21, 2023

Data warehouses play a vital role in healthcare decision-making and serve as a repository of historical data. A healthcare data warehouse can be a single source of truth for clinical quality control systems. What is a dimensional data model? What is a dimensional data model? What is a data vault?

Data Warehouse 63

Data Warehouse Data Lake Cost-Benefit Modeling 63

CDW Research Hub

JULY 27, 2021

Data volumes are growing exponentially, and traditional, on-premises data warehouses are constrained, overly complex, and costly to scale. This enables organizations to connect to any data source and combine any type of data. Build the foundation for a logical data warehouse or logical data lake.

Data Warehouse 52

Data Warehouse Data Lake Data Architecture Consulting 52

CIO Business Intelligence

FEBRUARY 16, 2023

Selling the value of data transformation Iyengar and his team are 18 months into a three- to five-year journey that started by building out the data layer — corralling data sources such as ERP, CRM, and legacy databases into data warehouses for structured data and data lakes for unstructured data.

Unstructured Data 105

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 105

Ontotext

MAY 2, 2024

Storage-centric approach In the storage-centric approach, people try to address data silos by throwing everything in a data lake or a data warehouse. But, although, this helps somewhat in terms of architecture, soon these data lakes become unwieldy. The best way to drive value is through use cases.

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

Timo Elliott

DECEMBER 14, 2022

The future is enabled by technology, but it’s not about the technical infrastructures: it’s about optimizing end-to-end processes, business capabilities, and business ecosystems. You lose the roots: the metadata, the hierarchies, the security, the business context of the data. So how do organizations do that? Business Process.

Data Lake 105

Data Lake Recreation/Entertainment Metadata Data Warehouse 105

AWS Big Data

MARCH 26, 2024

The AWS modern data architecture shows a way to build a purpose-built, secure, and scalable data platform in the cloud. Learn from this to build querying capabilities across your data lake and the data warehouse. Let’s find out what role each of these components play in the context of C360.

Data Strategy 69

Data Strategy Strategy Data Warehouse Prescriptive Analytics 69

AWS Big Data

NOVEMBER 20, 2023

Use case A typical workload for AWS Glue for Apache Spark jobs is to load data from a relational database to a data lake with SQL-based transformations. The end benefit for you is more effective and optimized AWS Glue for Apache Spark workloads. The metrics are available in all AWS Glue supported Regions. Check it out!

Metrics 95

Metrics Data Lake Cost-Benefit Dashboards 95

Cloudera

OCTOBER 6, 2022

Gartner : “Digital transformation can refer to anything from IT modernization (for example, cloud computing), to digital optimization, to the invention of new digital business models.”. For example, we have some customers using their data platform originally established for compliance initiatives to drive new use cases.

Digital Transformation 87

Digital Transformation Cost-Benefit Data Lake Machine Learning 87

AWS Big Data

NOVEMBER 8, 2023

Join us as we delve into the world of real-time streaming data at re:Invent 2023 and discover how you can use real-time streaming data to build new use cases, optimize existing projects and processes, and reimagine what’s possible. High-quality data is not just about accuracy; it’s also about timeliness.

Data-driven 87

Data-driven Data Lake Machine Learning Cost-Benefit 87