Wayne Yaddow

MARCH 14, 2025

How dbt Core aids data teams test, validate, and monitor complex data transformations and conversions Photo by NASA on Unsplash Introduction dbt Core, an open-source framework for developing, testing, and documenting SQL-based data transformations, has become a must-have tool for modern data teams as the complexity of data pipelines grows.

Data Transformation 52

Data Transformation Testing Unstructured Data Data Quality 52

AWS Big Data

DECEMBER 5, 2023

HR&A has used Amazon Redshift Serverless and CARTO to process survey findings more efficiently and create custom interactive dashboards to facilitate understanding of the results. A combination of Amazon Redshift Spectrum and COPY commands are used to ingest the survey data stored as CSV files.

Measurement 105

Measurement Dashboards Data Warehouse Analytics 105

AWS Big Data

MARCH 9, 2023

Amazon QuickSight is a fully managed, cloud-native business intelligence (BI) service that makes it easy to connect to your data, create interactive dashboards and reports, and share these with tens of thousands of users, either within QuickSight or embedded in your application or website. SDK Feature overview The QuickSight SDK v2.0

Slice and Dice 98

Slice and Dice Dashboards Analytics Interactive 98

CIO Business Intelligence

APRIL 30, 2024

This feature enables users to save calculations from a Tableau dashboard directly to Tableau’s metrics layer so they can monitor and track the information over time. Einstein Copilot for Tableau remains in beta, but Tableau announced two new features for the AI assistant as well: AI-assisted data transformation.

Analytics 96

Analytics Metrics Visualization Dashboards 96

AWS Big Data

OCTOBER 11, 2023

Due to this low complexity, the solution uses AWS serverless services to ingest the data, transform it, and make it available for analytics. The Data Catalog now contains references to the machine-readable data. Use the Data Catalog and transform the hospital price transparency data.

Visualization 118

Visualization Dashboards Data-driven Gap analysis 118

Cloudera

OCTOBER 11, 2021

The platform converges data cataloging, data ingestion, data profiling, data tagging, data discovery, and data exploration into a unified platform, driven by metadata. Modak Nabu automates repetitive tasks in the data preparation process and thus accelerates the data preparation by 4x.

Data Lake 95

Data Lake Cost-Benefit Data-driven Dashboards 95

Cloudera

JUNE 30, 2022

These tools empower analysts and data scientists to easily collaborate on the same data, with their choice of tools and analytic engines. No more lock-in, unnecessary data transformations, or data movement across tools and clouds just to extract insights out of the data.

Data Lake 88

Data Lake Data Warehouse Data Architecture Metadata 88

IBM Big Data Hub

OCTOBER 16, 2023

It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. A data store lets a business connect existing data with new data and discover new insights with real-time analytics and business intelligence. Increase trust in AI outcomes.

Risk 70

Risk Modeling Management Metadata 70

AWS Big Data

MARCH 15, 2023

The API retrieves data at runtime from an Amazon Aurora PostgreSQL-Compatible Edition database for end-user consumption. To populate the database, the Infomedia team developed a data pipeline using Amazon Simple Storage Service (Amazon S3) for data storage, AWS Glue for data transformations, and Apache Hudi for CDC and record-level updates.

Cost-Benefit 96

Cost-Benefit Data Processing Optimization Data-driven 96

AWS Big Data

MARCH 3, 2023

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. Data transformation – Steps 3 and 4 represent an EMR Serverless Spark application (Amazon EMR 6.9 Let’s refer to this S3 bucket as the raw layer.

Data Lake 98

Data Lake Dashboards Metrics Metadata 98

Alation

APRIL 4, 2023

Now, joint users will get an enhanced view into cloud and data transformations , with valuable context to guide smarter usage. Integrating helpful metadata into user workflows gives all people, from data scientists to analysts , the context they need to use data more effectively.

Metadata 52

Metadata Cost-Benefit Data Transformation Predictive Modeling 52

Octopai

JUNE 9, 2024

The goal was to develop sophisticated data products, such as predictive analytics models to forecast patient needs, patient care optimization tools, and operational efficiency dashboards. These data products were intended to enhance patient outcomes, streamline hospital operations, and provide actionable insights for decision-making.

IT 52

IT Data-driven Predictive Analytics Data Strategy 52

AWS Big Data

NOVEMBER 16, 2023

Data Vault 2.0 allows for the following: Agile data warehouse development Parallel data ingestion A scalable approach to handle multiple data sources even on the same entity A high level of automation Historization Full lineage support However, Data Vault 2.0

Enterprise 110

Enterprise Data Warehouse Data Lake Optimization 110

Alation

JANUARY 17, 2023

These help data analysts visualize key insights that can help you make better data-backed decisions. ELT Data Transformation Tools: ELT data transformation tools are used to extract, load, and transform your data. Examples of data transformation tools include dbt and dataform.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Science Data Transformation 52

Jet Global

MAY 1, 2023

Their dashboards were visually stunning. In turn, end users were thrilled with the bells and whistles of charts, graphs, and dashboards. As rich, data-driven user experiences are increasingly intertwined with our daily lives, end users are demanding new standards for how they interact with their business data.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

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 Visualization 52

Jet Global

JULY 19, 2023

The General Self-Service Enhancements in the latest product release include: View/Edit Mode for a Dashboard offers further customization and engagement options for end-users. View mode must respect interactivity, responsive layout and limit operations with dashboard. Simba Partnership now offers two new options for data connectors.

Dashboards 52

Dashboards Visualization Reporting Interactive 52

AWS Big Data

APRIL 29, 2025

While enabling organization-wide efficiency, the team also applied these principles to the data architecture, making sure that CLEA itself operates frugally. After evaluating various tools, we built a serverless data transformation pipeline using Amazon Athena and dbt. However, our initial data architecture led to challenges.

Data Transformation 55

Data Transformation Cost-Benefit Testing Data Lake 55

AWS Big Data

MAY 12, 2025

Streaming pipelines used Spark Streaming to ingest real-time data from Kafka, writing raw datasets to an Amazon Simple Storage Service (Amazon S3) data lake while simultaneously loading them into BigQuery and Google Cloud Storage to build logical data layers.

Metrics 85

Metrics Cost-Benefit Metadata Data Lake 85

AWS Big Data

APRIL 28, 2025

The data is stored in Apache Parquet format with AWS Glue Catalog providing metadata management. While this architecture supported NI analytical needs, it lacked the flexibility required for a truly open and adaptable data platform. The gold layer was coupled only with query engines that supported Hive and AWS Glue Data Catalog.

Data Lake 74

Data Lake Metadata Cost-Benefit Snapshot 74