AWS Big Data

AUGUST 19, 2024

This allows business analysts and decision-makers to gain valuable insights, visualize key metrics, and explore the data in depth, enabling informed decision-making and strategic planning for pricing and promotional strategies. Use Amazon Route 53 to create a private hosted zone that resolves the Snowflake endpoint within your VPC.

Analytics 118

Analytics Data-driven Data Integration Data Lake 118

AWS Big Data

DECEMBER 21, 2023

To bring their customers the best deals and user experience, smava follows the modern data architecture principles with a data lake as a scalable, durable data store and purpose-built data stores for analytical processing and data consumption.

Data Lake 115

Data Lake Data Warehouse Data-driven B2B 115

Cloudera

NOVEMBER 22, 2021

In addition, data pipelines include more and more stages, thus making it difficult for data engineers to compile, manage, and troubleshoot those analytical workloads. As a result, alternative data integration technologies (e.g., Limited flexibility to use more complex hosting models (e.g., CRM platforms).

Data Processing 94

Data Processing Data Warehouse Enterprise Visualization 94

AWS Big Data

SEPTEMBER 5, 2024

Amazon Redshift , a warehousing service, offers a variety of options for ingesting data from diverse sources into its high-performance, scalable environment. This native feature of Amazon Redshift uses massive parallel processing (MPP) to load objects directly from data sources into Redshift tables. AWS Glue 4.0

IoT 110

IoT Data Warehouse Cost-Benefit Reporting 110

AWS Big Data

AUGUST 1, 2024

However, you might face significant challenges when planning for a large-scale data warehouse migration. Data engineers are crucial for schema conversion and data transformation, and DBAs can handle cluster configuration and workload monitoring. Platform architects define a well-architected platform.

Data Warehouse 114

Data Warehouse KPI Optimization Cost-Benefit 114

AWS Big Data

MARCH 3, 2023

Building data lakes from continuously changing transactional data of databases and keeping data lakes up to date is a complex task and can be an operational challenge. You can then apply transformations and store data in Delta format for managing inserts, updates, and deletes.

Data Lake 98

Data Lake Dashboards Metrics Metadata 98

IBM Big Data Hub

JULY 17, 2023

By supporting open-source frameworks and tools for code-based, automated and visual data science capabilities — all in a secure, trusted studio environment — we’re already seeing excitement from companies ready to use both foundation models and machine learning to accomplish key tasks.

Machine Learning 62

Machine Learning Data Warehouse Modeling Cost-Benefit 62

Jet Global

FEBRUARY 23, 2024

Why Data Mapping is Important Data mapping is a critical element of any data management initiative, such as data integration, data migration, data transformation, data warehousing, or automation. Data mapping is important for several reasons.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Visualization 52