AWS Big Data

AUGUST 1, 2024

Large-scale data warehouse migration to the cloud is a complex and challenging endeavor that many organizations undertake to modernize their data infrastructure, enhance data management capabilities, and unlock new business opportunities. This makes sure the new data platform can meet current and future business goals.

Data Warehouse 115

Data Warehouse KPI Optimization Cost-Benefit 115

DataKitchen

JANUARY 3, 2022

Data scientists derive insights from data while business analysts work closely with and tend to the data needs of business units. Business analysts sometimes perform data science, but usually, they integrate and visualize data and create reports and dashboards from data supplied by other groups.

Business Analytics 245

Business Analytics Analytics Testing Dashboards 245

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. dashboards), it can leave your consumers frustrated with their experience. Modeling Your Data for Performance. Data architecture.

Data Warehouse 78

Data Warehouse OLAP Statistics Cost-Benefit 78

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. Nasdaq’s massive data growth meant they needed to evolve their data architecture to keep up.

Data Warehouse 59

Data Warehouse Data Lake Unstructured Data Optimization 59

AWS Big Data

FEBRUARY 26, 2025

Amazon SageMaker Lakehouse provides an open data architecture that reduces data silos and unifies data across Amazon Simple Storage Service (Amazon S3) data lakes, Redshift data warehouses, and third-party and federated data sources. AWS Glue 5.0 Finally, AWS Glue 5.0

Analytics 61

Analytics Data Lake Metadata Data Warehouse 61

AWS Big Data

NOVEMBER 28, 2023

To run analytics on their operational data, customers often build solutions that are a combination of a database, a data warehouse, and an extract, transform, and load (ETL) pipeline. ETL is the process data engineers use to combine data from different sources.

Data Warehouse 125

Data Warehouse Data-driven Machine Learning B2B 125

DataKitchen

NOVEMBER 4, 2021

Data organizations often have a mix of centralized and decentralized activity. 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.

Data Processing 246

Data Processing Data Lake Cost-Benefit Testing 246

AWS Big Data

JANUARY 30, 2025

Diagram 1: Overall architecture of the solution, using AWS Step Functions, Amazon Redshift and Amazon S3 The following AWS services were used to shape our new ETL architecture: Amazon Redshift A fully managed, petabyte-scale data warehouse service in the cloud.

Data Warehouse 54

Data Warehouse Data Architecture Machine Learning Data Transformation 54

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 130

Data Warehouse Analytics Data Lake Machine Learning 130

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 111

Data Warehouse Analytics Data Lake Data Science 111

AWS Big Data

NOVEMBER 15, 2023

The CLEA dashboards were built on the foundation of the Well-Architected Lab. For more information on this foundation, refer to A Detailed Overview of the Cost Intelligence Dashboard. The difference lies in when and where data transformation takes place. In ETL, data is transformed before it’s loaded into the data warehouse.

Dashboards 111

Dashboards Analytics Metadata Data Warehouse 111

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 126

Data Warehouse Cost-Benefit Sales Data-driven 126

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 111

Analytics Data Warehouse Dashboards Testing 111

Jen Stirrup

MARCH 29, 2023

Organisations are looking at ways of simplifying data; for example, through simple rebranding efforts to disguise the complexity. However, SAP Datasphere goes much deeper deeper than a simple rebranding; it is the next generation of SAP Data Warehouse Cloud. They fail to get a grip on their data.

Data Warehouse 121

Data Warehouse Metadata Data Integration Business Intelligence 121

AWS Big Data

NOVEMBER 9, 2023

The aim was to bolster their analytical capabilities and improve data accessibility while ensuring a quick time to market and high data quality, all with low total cost of ownership (TCO) and no need for additional tools or licenses. It’s raw, unprocessed data straight from the source.

Data Warehouse 126

Data Warehouse Testing Data Quality Reporting 126

CIO Business Intelligence

APRIL 12, 2023

After walking his executive team through the data hops, flows, integrations, and processing across different ingestion software, databases, and analytical platforms, they were shocked by the complexity of their current data architecture and technology stack. It isn’t easy.

Machine Learning 145

Machine Learning Cost-Benefit Data-driven Strategy 145

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 111

Enterprise Data Warehouse Data Lake Optimization 111

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 131

Data Lake Analytics Dashboards Metrics 131

CIO Business Intelligence

NOVEMBER 29, 2022

A sea of complexity For years, data ecosystems have gotten more complex due to discrete (and not necessarily strategic) data-platform decisions aimed at addressing new projects, use cases, or initiatives. Layering technology on the overall data architecture introduces more complexity.

Data Architecture 111

Data Architecture Data Integration IoT Data-driven 111

Cloudera

OCTOBER 18, 2022

Like all of our customers, Cloudera depends on the Cloudera Data Platform (CDP) to manage our day-to-day analytics and operational insights. Many aspects of our business live within this modern data architecture, providing all Clouderans the ability to ask, and answer, important questions for the business.

IT 89

IT Data Warehouse Dashboards Visualization 89

Smarten

JUNE 1, 2022

An integrated solution provides single sign-on access to data sources and data warehouses.’. Your clients have access to embedded BI objects from within the application with scalable integration APIs and objects including dashboards, crosstab, tabular, KPIs, graphs, reports etc. Rapid Deployment.

Data Warehouse 78

Data Warehouse Software Data Architecture Dashboards 78

Cloudera

JUNE 30, 2022

Companies, on the other hand, have continued to demand highly scalable and flexible analytic engines and services on the data lake, without vendor lock-in. Organizations want modern data architectures that evolve at the speed of their business and we are happy to support them with the first open data lakehouse. .

Data Lake 88

Data Lake Data Warehouse Data Architecture Metadata 88

CIO Business Intelligence

SEPTEMBER 14, 2023

They’re often responsible for building algorithms for accessing raw data, too, but to do this, they need to understand a company’s or client’s objectives, as aligning data strategies with business goals is important, especially when large and complex datasets and databases are involved.

Analytics 135

Analytics Data Science Unstructured Data Data mining 135

CIO Business Intelligence

JUNE 23, 2023

There are also no-code data engineering and AI/ML platforms so regular business users, as well as data engineers, scientists and DevOps staff, can rapidly develop, deploy, and derive business value.

Data Strategy 116

Data Strategy Strategy Visualization Consulting 116

CIO Business Intelligence

AUGUST 9, 2022

Data engineers are often responsible for building algorithms for accessing raw data, but to do this, they need to understand a company’s or client’s objectives, as aligning data strategies with business goals is important, especially when large and complex datasets and databases are involved. Data engineer job description.

Analytics 131

Analytics Data Science Statistics Unstructured Data 131

AWS Big Data

JUNE 6, 2023

In this post, we highlight the seamless integration of Amazon Athena and Amazon QuickSight , which enables the visualization of operational metrics for AWS Glue Data Quality rule evaluation in an efficient and effective manner. The following architecture diagram shows an overview of the complete pipeline. Choose Visualize.

Data Quality 97

Data Quality Metrics Visualization Dashboards 97

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 diagram shows a sample C360 dashboard built on Amazon QuickSight.

Data Strategy 99

Data Strategy Strategy Data Warehouse Prescriptive Analytics 99

AWS Big Data

SEPTEMBER 5, 2024

Federated queries allow querying data across Amazon RDS for MySQL and PostgreSQL data sources without the need for extract, transform, and load (ETL) pipelines. If storing operational data in a data warehouse is a requirement, synchronization of tables between operational data stores and Amazon Redshift tables is supported.

IoT 111

IoT Data Warehouse Cost-Benefit Reporting 111

AWS Big Data

JANUARY 8, 2024

In this post, we will review the common architectural patterns of two use cases: Time Series Data Analysis and Event Driven Microservices. All these architecture patterns are integrated with Amazon Kinesis Data Streams. Refer to Amazon Kinesis Data Streams integrations for additional details.

Analytics 134

Analytics IoT Data-driven Snapshot 134

Peter James Thomas

AUGUST 18, 2018

From 2000 to 2015, I had some success [5] with designing and implementing Data Warehouse architectures much like the following: As a lot of my work then was in Insurance or related fields, the Analytical Repositories tended to be Actuarial Databases and / or Exposure Management Databases, developed in collaboration with such teams.

Data Lake 63

Data Lake Data Warehouse Data mining Statistics 63

Cloudera

NOVEMBER 29, 2021

eMAG , a Romania-based retailer seen as a pioneer in e-commerce, was struggling to manage the tremendously large amount of data coming in every second. The company needed a modern data architecture to manage the growing traffic effectively. . Now the team’s data scientists can better analyze data with dashboard access.

Data Lake 77

Data Lake Data Warehouse Data Architecture Reporting 77

AWS Big Data

MARCH 6, 2025

Tens of thousands of customers use Amazon Redshift for modern data analytics at scale, delivering up to three times better price-performance and seven times better throughput than other cloud data warehouses. On the Amazon Redshift console, navigate to the Redshift Serverless dashboard. Choose Create workgroup.

Visualization 63

Visualization Sales Data Warehouse Management 63

AWS Big Data

FEBRUARY 15, 2024

You might be modernizing your data architecture using Amazon Redshift to enable access to your data lake and data in your data warehouse, and are looking for a centralized and scalable way to define and manage the data access based on IdP identities. sales_datashare_schema"."sales_schema.store_sales";

Management 115

Management Data Lake Sales Data Warehouse 115

AWS Big Data

APRIL 20, 2023

In a modern data architecture, unified analytics enable you to access the data you need, whether it’s stored in a data lake or a data warehouse. In this case, the ETL developer would choose TRUNCATE to ensure the data is fully refreshed but the table schema is guaranteed not to change.

Visualization 98

Visualization Data Warehouse Big Data Data Lake 98

IBM Big Data Hub

SEPTEMBER 19, 2023

How effectively and efficiently an organization can conduct data analytics is determined by its data strategy and data architecture , which allows an organization, its users and its applications to access different types of data regardless of where that data resides.

Data Science 76

Data Science Data Analytics Prescriptive Analytics Analytics 76

Jedox

OCTOBER 22, 2020

The goal in addressing these pain points is to empower your stakeholders (both within Finance/FP&A and your business partners) to be able to deliver: Consistent reporting and dashboards. Typically, we take our multiple data sources and perform some level of ETL on the data. Self-service reporting. Drill-down capability.

Data Analytics 69

Data Analytics Analytics Unstructured Data Data mining 69

Peter James Thomas

APRIL 3, 2020

Some espouse the opinion that the term is synonymous with Dashboards. Jane opened up her personal dashboard, which already showed the headline figures the CFO had been citing. Some charts or tables may be replicated across a number of dashboards, but others with be specific to a particular area of the business.

Dashboards 61

Dashboards Reporting Sales Data Lake 61