AWS Big Data

APRIL 30, 2024

Amazon Q Developer can now generate complex data integration jobs with multiple sources, destinations, and data transformations. Generated jobs can use a variety of data transformations, including filter, project, union, join, and custom user-supplied SQL.

Data Integration 102

Data Integration Data Lake Data Warehouse Software 102

Alation

JANUARY 17, 2023

The modern data stack is a combination of various software tools used to collect, process, and store data on a well-integrated cloud-based data platform. It is known to have benefits in handling data due to its robustness, speed, and scalability. A typical modern data stack consists of the following: A data warehouse.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Business Intelligence 52

Cloudera

OCTOBER 7, 2022

We’re excited to announce the general availability of the open source adapters for dbt for all the engines in CDP — Apache Hive , Apache Impala , and Apache Spark, with added support for Apache Livy and Cloudera Data Engineering. The Open Data Lakehouse . Cloudera builds dbt adaptors for all engines in the open data lakehouse.

Data Warehouse 79

Data Warehouse Data Transformation Testing Data Lake 79

AWS Big Data

JULY 25, 2023

The integration of Talend Cloud and Talend Stitch with Amazon Redshift Serverless can help you achieve successful business outcomes without data warehouse infrastructure management. In this post, we demonstrate how Talend easily integrates with Redshift Serverless to help you accelerate and scale data analytics with trusted data.

Data Analytics 52

Data Analytics Data Warehouse Analytics Data Processing 52

Alation

OCTOBER 27, 2022

Few actors in the modern data stack have inspired the enthusiasm and fervent support as dbt. This data transformation tool enables data analysts and engineers to transform, test and document data in the cloud data warehouse. But what does this mean from a practitioner perspective?

Metrics 52

Metrics Dashboards Sales Reporting 52

IBM Big Data Hub

JULY 17, 2023

These encoder-only architecture models are fast and effective for many enterprise NLP tasks, such as classifying customer feedback and extracting information from large documents. While they require task-specific labeled data for fine tuning, they also offer clients the best cost performance trade-off for non-generative use cases.

Machine Learning 67

Machine Learning Data Warehouse Modeling Cost-Benefit 67

AWS Big Data

OCTOBER 27, 2023

Efficiency : Data transformation tasks that previously took weeks or months can now be accomplished within minutes, optimizing efficiency. Follow the documentation to clean up the Google resources. Cost efficiency : Building and maintaining custom connectors can be expensive.

Analytics 95

Analytics Visualization Data Integration Cost-Benefit 95

Alation

OCTOBER 18, 2022

Data analysts and engineers use dbt to transform, test, and document data in the cloud data warehouse. Yet every dbt transformation contains vital metadata that is not captured – until now. Data Transformation in the Modern Data Stack. How did the data transform exactly?

Metadata 52

Metadata Metrics Recreation/Entertainment Data Quality 52

AWS Big Data

MARCH 3, 2023

The weeks that followed the lab included go-to-market activities with specific customers, documentation, hardening, security reviews, performance testing, data integrity testing, and automation activities. The Amazon S3 sink connector further streams data into Amazon S3 in real time by partitioning data into fixed-sized files.

Software 52

Software Data Lake Testing Cost-Benefit 52

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 102

Data Lake Management Metrics Data Warehouse 102

CIO Business Intelligence

NOVEMBER 7, 2023

Given the importance of sharing information among diverse disciplines in the era of digital transformation, this concept is arguably as important as ever. The aim is to normalize, aggregate, and eventually make available to analysts across the organization data that originates in various pockets of the enterprise.

Data Warehouse 142

Data Warehouse Digital Transformation Data-driven Reporting 142

AWS Big Data

OCTOBER 5, 2023

Amazon AppFlow , a fully managed data integration service, has been at the forefront of streamlining data transfer between AWS services, software as a service (SaaS) applications, and now Google BigQuery. Architecture Let’s review the architecture to transfer data from Google BigQuery to Amazon S3 using Amazon AppFlow.

Data Warehouse 85

Data Warehouse Machine Learning Data Integration Data-driven 85

Rocket-Powered Data Science

MARCH 20, 2023

Data collections are the ones and zeroes that encode the actionable insights (patterns, trends, relationships) that we seek to extract from our data through machine learning and data science. This is where SAP Datasphere (the next generation of SAP Data Warehouse Cloud) comes in.

Data Warehouse 324

Data Warehouse Metadata Digital Transformation Unstructured Data 324

Jet Global

FEBRUARY 23, 2024

This field guide to data mapping will explore how data mapping connects volumes of data for enhanced decision-making. 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 Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

Jet Global

NOVEMBER 7, 2023

The answer depends on your specific business needs and the nature of the data you are working with. Both methods have advantages and disadvantages: Replication involves periodically copying data from a source system to a data warehouse or reporting database. Empower your team to add new data sources on the fly.

Enterprise 52

Enterprise Data Warehouse Operational Reporting Reporting 52

Jet Global

MAY 1, 2023

These sit on top of data warehouses that are strictly governed by IT departments. The role of traditional BI platforms is to collect data from various business systems. Modern Data Sources Painlessly connect with modern data such as streaming, search, big data, NoSQL, cloud, document-based sources.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

Jet Global

MARCH 14, 2024

This straightforward and user-friendly access to source data makes it easier for your business users to examine and extract insights from your core data systems. Data Lineage and Documentation Jet Analytics simplifies the process of documenting data assets and tracking data lineage in Fabric.

Analytics 52

Analytics Management Reporting Enterprise 52

Jet Global

AUGUST 9, 2023

Process Runner GLSU and Wands for SAP provide flexible, intuitive interfaces for SAP data entry and transaction posting directly from Microsoft Excel. Automate financial document posting processes resulting in a shorter month-end close. Increase data accuracy and improve audit processing while running a stress-free finance operation.

Finance 52

Finance Reporting Management Enterprise 52