CIO Business Intelligence

JUNE 23, 2022

We live in a hybrid data world. In the past decade, the amount of structured data created, captured, copied, and consumed globally has grown from less than 1 ZB in 2011 to nearly 14 ZB in 2020. Impressive, but dwarfed by the amount of unstructured data, cloud data, and machine data – another 50 ZB.

IT 97

IT Data Architecture Unstructured Data Big Data 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. Features focus on media and entertainment firms.

Recreation/Entertainment 118

Recreation/Entertainment Data Lake Data Warehouse Unstructured Data 118

CDW Research Hub

JULY 22, 2019

These old and inefficient systems were designed for a different era, when data was a side project and access to analytics was limited to the executive team. To do so, these companies need a modern data warehouse, such as Snowflake. With Snowflake, you can store, transform and analyze structured and semi-structured data together.

Data Warehouse 54

Data Warehouse Business Intelligence Structured Data Data-driven 54

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 115

Data Warehouse Data Lake Cost-Benefit Structured Data 115

AWS Big Data

DECEMBER 21, 2023

Overview of solution As a data-driven company, smava relies on the AWS Cloud to power their analytics use cases. smava ingests data from various external and internal data sources into a landing stage on the data lake based on Amazon Simple Storage Service (Amazon S3). This is the Data Mart stage.

Data Lake 115

Data Lake Data Warehouse Data-driven B2B 115

IBM Big Data Hub

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

Data Science 76

Data Science Data Analytics Prescriptive Analytics Analytics 76

AWS Big Data

NOVEMBER 9, 2023

Data ingestion, whether real time or batch, forms the basis of any effective data analysis, enabling organizations to gather information from diverse sources and use it for insightful decision-making. It’s raw, unprocessed data straight from the source.

Data Warehouse 126

Data Warehouse Testing Data Quality Reporting 126

AWS Big Data

JANUARY 22, 2024

The majority of data produced by these accounts is used downstream for business intelligence (BI) purposes and in Amazon Athena , by hundreds of business users every day. The solution Acast implemented is a data mesh, architected on AWS.

Data-driven 117

Data-driven Advertising Metadata Data Architecture 117

Ontotext

JULY 26, 2019

Examples of such continuous improvement are technological giants like Google and Amazon who use semantic technology principles to build better data architectures for better user experiences. Take, for instance, the domain of business intelligence and the problem of discoverability.

Technology 75

Technology Enterprise Data Integration Structured Data 75

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. Key considerations Gameskraft embraces a modern data architecture, with the data lake residing in Amazon S3.

Data Warehouse 111

Data Warehouse Analytics Data Lake Data Science 111

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.

Analytics 61

Analytics Data Lake Metadata Data Warehouse 61

IBM Big Data Hub

JANUARY 18, 2023

Data platform architecture has an interesting history. Towards the turn of millennium, enterprises started to realize that the reporting and business intelligence workload required a new solution rather than the transactional applications. It required a different data platform solution. It was Datawarehouse.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

Ontotext

JULY 26, 2019

Examples of such continuous improvement are technological giants like Google and Amazon who use semantic technology principles to build better data architectures for better user experiences. Take, for instance, the domain of business intelligence and the problem of discoverability.

Technology 40

Technology Data Integration Enterprise Structured Data 40

CIO Business Intelligence

APRIL 4, 2023

In order to move AI forward, we need to first build and fortify the foundational layer: data architecture. This architecture is important because, to reap the full benefits of AI, it must be built to scale across an enterprise versus individual AI applications. Constructing the right data architecture cannot be bypassed.

Data Architecture 52

Data Architecture Data Lake Data Warehouse Cost-Benefit 52

Jet Global

OCTOBER 1, 2024

Trino has quickly emerged as one of the most formidable SQL query engines, widely recognized for its ability to connect to diverse data sources and execute complex queries with remarkable efficiency. This is particularly valuable for teams that require instant answers from their data. Ready to Transform Your Data Strategy?

Dashboards 52

Dashboards Data Lake Reporting Cost-Benefit 52

AWS Big Data

OCTOBER 30, 2024

This is the final part of a three-part series where we show how to build a data lake on AWS using a modern data architecture. This post shows how to process data with Amazon Redshift Spectrum and create the gold (consumption) layer. In our use case, we use Redshift Query Editor to create data marts using SQL code.

Data Lake 92

Data Lake Machine Learning Data Architecture Data-driven 92