AWS Big Data

MARCH 11, 2024

Amazon Redshift is a fully managed, scalable cloud data warehouse that accelerates your time to insights with fast, straightforward, and secure analytics at scale. Tens of thousands of customers rely on Amazon Redshift to analyze exabytes of data and run complex analytical queries, making it the most widely used cloud data warehouse.

Analytics 72

Analytics Data Warehouse Optimization Metrics 72

AWS Big Data

SEPTEMBER 4, 2024

With the AWS Glue Salesforce connector, you can ingest and transform your CRM data to any of the AWS Glue supported destinations, including Amazon Simple Storage Service (Amazon S3), in your preferred format, including Apache Iceberg, Apache Hudi, and Linux Foundation Delta Lake; data warehouses such as Amazon Redshift and Snowflake; and many more.

Data Integration 86

Data Integration Data Lake Data-driven Cost-Benefit 86

AWS Big Data

DECEMBER 13, 2023

A CDC-based approach captures the data changes and makes them available in data warehouses for further analytics in real-time. usually a data warehouse) needs to reflect those changes in near real-time. This post showcases how to use streaming ingestion to bring data to Amazon Redshift.

Data Warehouse 108

Data Warehouse Snapshot Data Processing Internet of Things 108

AWS Big Data

NOVEMBER 30, 2023

This integration simplifies the authentication and authorization process for Amazon Redshift users using Query Editor V2 or Amazon Quicksight , making it easier for them to securely access your data warehouse. Note: Your organization’s IdC instance must be in the same region as the Amazon Redshift data warehouse you’re connecting to.

Data Warehouse 90

Data Warehouse Finance Sales Management 90

AWS Big Data

MAY 4, 2023

Amazon Redshift Serverless makes it easy to run and scale analytics in seconds without the need to set up and manage data warehouse clusters. Customers use their preferred SQL clients to analyze their data in Redshift Serverless. An Redshift Serverless data warehouse. If you don’t have one, you can sign up for one.

Finance 85

Finance Data Warehouse Sales Metadata 85

datapine

MAY 9, 2019

Business intelligence concepts refer to the usage of digital computing technologies in the form of data warehouses, analytics and visualization with the aim of identifying and analyzing essential business-based data to generate new, actionable corporate insights. The data warehouse. 1) The raw data.

Business Intelligence 270

Business Intelligence Dashboards Data Warehouse Sales 270

AWS Big Data

APRIL 19, 2023

Many customers run big data workloads such as extract, transform, and load (ETL) on Apache Hive to create a data warehouse on Hadoop. json ) to DynamoDB (for more information, refer to Write data to a table using the console or AWS CLI ): { "name": "step1.q", Amol Guldagad is a Data Analytics Consultant based in India.

Metadata 84

Metadata Testing Data Lake Consulting 84

AWS Big Data

AUGUST 27, 2024

His background is in data warehouse/data lake – architecture, development and administration. He is in data and analytical field for over 14 years. Ramesh Raghupathy is a Senior Data Architect with WWCO ProServe at AWS. He specializes in building and modernising analytical solutions.

Metrics 85

Metrics Dashboards Data Lake Optimization 85

AWS Big Data

JUNE 6, 2023

Founded in 2012, SumUp is the financial partner for more than 4 million small merchants in over 35 markets worldwide, helping them start, run and grow their business. Unless, of course, the rest of their data also resides in the Google Cloud. This is a guest blog post by Mira Daniels and Sean Whitfield from SumUp.

Analytics 59

Analytics Data Lake Testing Optimization 59

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.

Management 100

Management Data Lake Sales Data Warehouse 100

AWS Big Data

AUGUST 5, 2024

These business units have varying landscapes, where a data lake is managed by Amazon Simple Storage Service (Amazon S3) and analytics workloads are run on Amazon Redshift , 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.

Data Lake 86

Data Lake Finance Sales Management 86

AWS Big Data

APRIL 20, 2023

Apache Spark enables you to build applications in a variety of languages, such as Java, Scala, and Python, by accessing the data in your Amazon Redshift data warehouse. Amazon Redshift integration for Apache Spark helps developers seamlessly build and run Apache Spark applications on Amazon Redshift data.

Data Lake 81

Data Lake Data Warehouse Sales Data-driven 81

BizAcuity

MAY 10, 2022

2012: Amazon Redshift, the first of its kind cloud-based data warehouse service comes into existence. Fact: IBM built the world’s first data warehouse in the 1980’s. Google launches BigQuery, its own data warehousing tool and Microsoft introduces Azure SQL Data Warehouse and Azure Data Lake Store.

Data-driven 52

Data-driven IoT Unstructured Data Data Lake 52

Domino Data Lab

APRIL 3, 2019

Most of the data management moved to back-end servers, e.g., databases. So we had three tiers providing a separation of concerns: presentation, logic, data. Note that data warehouse (DW) and business intelligence (BI) practices both emerged circa 1990. We keep feeding the monster data.

Data Governance 84

Data Governance Machine Learning Metadata Data Science 84

Jet Global

SEPTEMBER 22, 2023

You can create a query like this: “Please analyze this dataset and let me know interesting facts you see: Rows: (All) Quarter 1, 2012 Quarter 2, 2012 Quarter 3, 2012 … Cells: 4,117,344.28 You might have a dataset represented in a chart, and you want ChatGPT to analyze it.

Dashboards 52

Dashboards Data-driven Visualization Interactive 52