AWS Big Data

JUNE 28, 2023

For more details, refer to the What’s New Post. There are two broad approaches to analyzing operational data for these use cases: Analyze the data in-place in the operational database (e.g. The transactional data from this website is loaded into an Aurora MySQL 3.03.1 (or or higher version) database.

Data Warehouse 88

Data Warehouse Analytics Metrics Dashboards 88

AWS Big Data

MARCH 21, 2024

The extract, transform, and load (ETL) process has been a common pattern for moving data from an operational database to an analytics data warehouse. ELT is where the extracted data is loaded as is into the target first and then transformed. Refer to Zero-ETL integration costs (Preview) for further details.

Data Warehouse 91

Data Warehouse Metrics Statistics Optimization 91

AWS Big Data

JULY 27, 2023

Amazon Redshift is a widely used, fully managed, petabyte-scale cloud data warehouse. Tens of thousands of customers use Amazon Redshift to process exabytes of data every day to power their analytics workloads. Take a snapshot of the source Redshift data warehouse.

Testing 67

Testing Data Warehouse Data Processing Snapshot 67

AWS Big Data

OCTOBER 24, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud, providing up to five times better price-performance than any other cloud data warehouse, with performance innovation out of the box at no additional cost to you. The following table summarizes these metrics.

Metrics 89

Metrics Statistics Data Warehouse Cost-Benefit 89

AWS Big Data

SEPTEMBER 13, 2023

The Analytics specialty practice of AWS Professional Services (AWS ProServe) helps customers across the globe with modern data architecture implementations on the AWS Cloud. The company wanted the ability to continue processing operational data in the secondary Region in the rare event of primary Region failure.

Data Lake 94

Data Lake Data Processing Metadata Snapshot 94

AWS Big Data

JULY 19, 2023

Amazon Redshift is a fully managed and petabyte-scale cloud data warehouse that is used by tens of thousands of customers to process exabytes of data every day to power their analytics workload. You can structure your data, measure business processes, and get valuable insights quickly can be done by using a dimensional model.

Modeling 71

Modeling Sales Data Warehouse Snapshot 71

AWS Big Data

JANUARY 24, 2023

AWS Glue Data Catalog The AWS Glue Data Catalog is a central repository of metadata about data stored in your data lake. The Data Catalog organizes this information in the form of metadata tables and databases. He specializes in migrating enterprise data warehouses to AWS Modern Data Architecture.

Data Architecture 68

Data Architecture Metadata Data Lake Snapshot 68

CIO Business Intelligence

JANUARY 20, 2023

BI tools access and analyze data sets and present analytical findings in reports, summaries, dashboards, graphs, charts, and maps to provide users with detailed intelligence about the state of the business. The potential use cases for BI extend beyond the typical business performance metrics of improved sales and reduced costs.

Business Intelligence 144

Business Intelligence Dashboards Data mining OLAP 144

AWS Big Data

FEBRUARY 1, 2023

Architecturally, we chose a serverless model, and the data lake architecture action line refers to all the architectural gaps and challenging features we determined were part of the improvements. To query data from REST APIs and other data sources, we used PySpark and JDBC modules.

Optimization 52

Optimization Forecasting Data Lake Metadata 52

FineReport

NOVEMBER 25, 2020

Dashboard reporting refers to putting the relevant business metrics and KPIs in one interface, presenting them visually, dynamic, and in real-time, in the dashboard formats. The free version of Databox is limited to three data sources, three dashboards, and three users, and only provides one daily refresh. From Google.

Dashboards 98

Dashboards Reporting Visualization Snapshot 98

AWS Big Data

MAY 19, 2023

Organizations across all industries have complex data processing requirements for their analytical use cases across different analytics systems, such as data lakes on AWS , data warehouses ( Amazon Redshift ), search ( Amazon OpenSearch Service ), NoSQL ( Amazon DynamoDB ), machine learning ( Amazon SageMaker ), and more.

Machine Learning 86

Machine Learning Metrics Management Big Data 86

AWS Big Data

MARCH 3, 2023

Incremental data is generated in the PostgreSQL table by running custom SQL scripts. Data ingestion – Steps 1 and 2 use AWS DMS, which connects to the source database and moves full and incremental data (CDC) to Amazon S3 in Parquet format. Let’s refer to this S3 bucket as the raw layer. with Apache Spark version 3.3.0)

Data Lake 85

Data Lake Dashboards Metrics Metadata 85

Cloudera

SEPTEMBER 17, 2020

Because DE is fully integrated with the Cloudera Shared Data Experience (SDX), every stakeholder across your business gains end-to-end operational visibility, with comprehensive security and governance throughout. This is typically for application (e.g.jar,py files) and reference files, and not the data that the job run will operate on.

Visualization 102

Visualization Metrics Statistics Optimization 102

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. Clustering data for better data colocation using z-ordering.

Data Lake 117

Data Lake Metadata Optimization Statistics 117

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 107

Data Lake Management Metrics Data Warehouse 107