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

Sisense

SEPTEMBER 3, 2019

This blog is intended to give an overview of the considerations you’ll want to make as you build your Redshift data warehouse to ensure you are getting the optimal performance. Amazon describes the dense storage nodes (DS2) as optimized for large data workloads and use hard disk drives (HDD) for storage.

Data Warehouse 78

Data Warehouse OLAP Statistics Cost-Benefit 78

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 Data Lake Optimization 83

AWS Big Data

JANUARY 24, 2023

In his spare time, he loves reading and finds areas for home automation Raza Hafeez is a Senior Data Architect within the Shared Delivery Practice of AWS Professional Services. He specializes in migrating enterprise data warehouses to AWS Modern Data Architecture.

Data Architecture 64

Data Architecture Metadata Data Lake Snapshot 64

AWS Big Data

NOVEMBER 14, 2023

Amazon Redshift is a fast, fully managed cloud data warehouse that makes it straightforward and cost-effective to analyze all your data at petabyte scale, using standard SQL and your existing business intelligence (BI) tools. Their cluster size of the provisioned data warehouse didn’t change.

Data Warehouse 60

Data Warehouse Analytics Testing Cost-Benefit 60

AWS Big Data

NOVEMBER 28, 2023

As customers become more data driven and use data as a source of competitive advantage, they want to easily run analytics on their data to better understand their core business drivers to grow sales, reduce costs, and optimize their businesses. ETL is the process data engineers use to combine data from different sources.

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Data Warehouse Data-driven Machine Learning B2B 92

AWS Big Data

FEBRUARY 1, 2024

Trade quality and optimization – In order to monitor and optimize trade quality, you need to continually evaluate market characteristics such as volume, direction, market depth, fill rate, and other benchmarks related to the completion of trades. This will be your OLTP data store for transactional data. version cluster.

Data Warehouse 122

Data Warehouse Dashboards Risk Management Risk 122

BizAcuity

NOVEMBER 22, 2022

In today’s world that is largely data-driven, organizations depend on data for their success and survival, and therefore need robust, scalable data architecture to handle their data needs. This typically requires a data warehouse for analytics needs that is able to ingest and handle real time data of huge volumes.

Data Warehouse 98

Data Warehouse Cost-Benefit Data Lake Internet of Things 98

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 92

Data Lake Data Warehouse Metadata Data Architecture 92

AWS Big Data

APRIL 29, 2024

Example permission configuration In a practical application within a company, permissions for tables and fields in the data warehouse are divided based on business departments, isolating sensitive data for different business units. This provides data security and orderly conduct of daily business operations.

Management 95

Management Big Data Metadata Data Warehouse 95

CIO Business Intelligence

JUNE 23, 2022

These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. In recent years, the term “data lakehouse” was coined to describe this architectural pattern of tabular analytics over data in the data lake.

Data Lake 91

Data Lake Data Warehouse Machine Learning Cost-Benefit 91

AWS Big Data

NOVEMBER 13, 2023

Amazon Redshift is a fully managed data warehousing service that offers both provisioned and serverless options, making it more efficient to run and scale analytics without having to manage your data warehouse. These upstream data sources constitute the data producer components.

Data Warehouse 90

Data Warehouse Data Lake Analytics Data Science 90

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

APRIL 25, 2022

The other 10% represents the effort of initial deployment, data-loading, configuration and the setup of administrative tasks and analysis that is specific to the customer, the Henschen said. Partner solutions to boost functionality, adoption. The company’s collaboration with Lovelytics is focused on baseball.

Recreation/Entertainment 116

Recreation/Entertainment Data Lake Data Warehouse Unstructured Data 116

AWS Big Data

MAY 17, 2023

During that same time, AWS has been focused on helping customers manage their ever-growing volumes of data with tools like Amazon Redshift , the first fully managed, petabyte-scale cloud data warehouse. One group performed extract, transform, and load (ETL) operations to take raw data and make it available for analysis.

Data Warehouse 111

Data Warehouse Cost-Benefit Sales Data-driven 111

Cloudera

JUNE 18, 2022

These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. In recent years, the term “data lakehouse” was coined to describe this architectural pattern of tabular analytics over data in the data lake.

Data Lake 91

Data Lake Data Warehouse Machine Learning Cost-Benefit 91

CIO Business Intelligence

JUNE 24, 2022

Forrester believes that enterprise architecture teams across APAC can drive more value and increase their chances of success by linking business capability modelling (BCM) with customer journey mapping and by using value stream management (VSM) to drive effective change. Digital Transformation

Modeling 102

Modeling Digital Transformation Data Architecture Data-driven 102

BizAcuity

APRIL 1, 2023

Introduction In today’s world that is largely data-driven, organizations depend on data for their success and survival, and therefore need robust, scalable data architecture to handle their data needs. For this reason, Snowflake is often the cloud-native data warehouse of choice.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Lake Internet of Things 52

AWS Big Data

NOVEMBER 15, 2023

BMW Group uses 4,500 AWS Cloud accounts across the entire organization but is faced with the challenge of reducing unnecessary costs, optimizing spend, and having a central place to monitor costs. The ultimate goal is to raise awareness of cloud efficiency and optimize cloud utilization in a cost-effective and sustainable manner.

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Dashboards Analytics Metadata Data Warehouse 94

CIO Business Intelligence

SEPTEMBER 14, 2023

What is a data engineer? Data engineers design, build, and optimize systems for data collection, storage, access, and analytics at scale. They create data pipelines that convert raw data into formats usable by data scientists, data-centric applications, and other data consumers.

Analytics 134

Analytics Data Science Unstructured Data Data mining 134

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. In this way, the Cloud Data Warehouse Accelerator enables a seamless transition to Snowflake. Build the foundation for a logical data warehouse or logical data lake.

Data Warehouse 52

Data Warehouse Data Lake Data Architecture Consulting 52

AWS Big Data

OCTOBER 18, 2023

Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse that provides the flexibility to use provisioned or serverless compute for your analytical workloads. The decoupled compute and storage architecture of Amazon Redshift enables you to build highly scalable, resilient, and cost-effective workloads.

Analytics 95

Analytics Data Warehouse Testing Dashboards 95

AWS Big Data

NOVEMBER 13, 2023

11:30 AM – 12:30 PM (PDT) Ceasars Forum ANT318 | Accelerate innovation with end-to-end serverless data architecture. 4:30 PM – 5:30 PM (PDT) Wynn ANT207 | Understand your data with business context. 1:00 PM – 2:00 PM (PDT) Venetian ANT201 | Accelerate innovation with real-time data.

Analytics 112

Analytics Data Lake Data Warehouse Data-driven 112

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

AWS Big Data

APRIL 3, 2023

Tens of thousands of customers run business-critical workloads on Amazon Redshift , AWS’s fast, petabyte-scale cloud data warehouse delivering the best price-performance. With Amazon Redshift, you can query data across your data warehouse, operational data stores, and data lake using standard SQL.

Data Warehouse 97

Data Warehouse Testing Data Lake Data-driven 97

BI-Survey

NOVEMBER 23, 2021

However, the operational data stored in data silos was not suitable for this task. Many companies therefore built a data warehouse to consolidate their operational data silos. Data-based insights are being used to automate decisions. Data black holes: the high cost of supposed flexibility.

Digital Transformation 52

Digital Transformation Data Warehouse Data Lake Data-driven 52

AWS Big Data

MARCH 10, 2023

They enable transactions on top of data lakes and can simplify data storage, management, ingestion, and processing. These transactional data lakes combine features from both the data lake and the data warehouse. Data can be organized into three different zones, as shown in the following figure.

Data Lake 102

Data Lake Sales Data Warehouse Snapshot 102

Cloudera

SEPTEMBER 12, 2022

Combining and analyzing both structured and unstructured data is a whole new challenge to come to grips with, let alone doing so across different infrastructures. Both obstacles can be overcome using modern data architectures, specifically data fabric and data lakehouse. Unified data fabric.

Unstructured Data 73

Unstructured Data Data Architecture Data Lake Snapshot 73

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. The following screenshot shows an example C360 dashboard built on QuickSight.

Data Strategy 69

Data Strategy Strategy Data Warehouse Prescriptive Analytics 69

Cloudera

FEBRUARY 22, 2021

The Cloudera Data Platform (CDP) represents a paradigm shift in modern data architecture by addressing all existing and future analytical needs. Infrastructure cost optimization. reduce technology costs, accelerate organic growth initiatives). Business value acceleration. Technology cost reduction / avoidance.

Cost-Benefit 79

Cost-Benefit Data Warehouse Data Processing Data Governance 79

CIO Business Intelligence

AUGUST 9, 2022

What is a data engineer? Data engineers design, build, and optimize systems for data collection, storage, access, and analytics at scale. They create data pipelines used by data scientists, data-centric applications, and other data consumers. Data engineer job description.

Analytics 128

Analytics Data Science Statistics Unstructured Data 128

Cloudera

DECEMBER 19, 2018

The most common big data use case is data warehouse optimization. Big data architecture is used to augment different applications, operating alongside or in a discrete fashion with a data warehouse. A big data implementation may even replace a data warehouse entirely with a data lake.

Data Warehouse 52

Data Warehouse Analytics Big Data Data Architecture 52

DataKitchen

NOVEMBER 4, 2021

DataOps concerns itself with the complex flow of data across teams, data centers and organizational boundaries. It expands beyond tools and data architecture and views the data organization from the perspective of its processes and workflows. When the tests pass, the orchestration admits the data to a data catalog.

Data Processing 246

Data Processing Data Lake Cost-Benefit Testing 246

IBM Big Data Hub

JULY 5, 2022

In today’s world of complex data architectures and emerging technologies, databases can sometimes be undervalued and unrecognized. Nedbank builds a scalable data warehouse architecture . Endless data but your queries aren’t fast enough. To learn more, visit IBM Db2 and our IBM data management page. .

Data Lake 97

Data Lake Data Warehouse Publishing Structured Data 97

AWS Big Data

MAY 18, 2023

It’s even harder when your organization is dealing with silos that impede data access across different data stores. Seamless data integration is a key requirement in a modern data architecture to break down data silos. The upgrade also offers support for Bloom filters and skew optimization.

Testing 75

Testing Data Lake Cost-Benefit Data Integration 75

Cloudera

NOVEMBER 27, 2023

3: Efforts to simplify deployment architectures are expected to help further accelerate adoption Many organizations are moving their Flink deployments to Kubernetes. This will help accelerate deployment across environments and to optimize performance and resource utilization on an ongoing basis. Takeaway No.

Data Lake 81

Data Lake Advertising ROI Data Warehouse 81

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 113

Data Lake Metadata Optimization Statistics 113