AWS Big Data

JANUARY 30, 2025

AWS Glue A data integration service, AWS Glue consolidates major data integration capabilities into a single service. These include data discovery, modern ETL, cleansing, transforming, and centralized cataloging. Its also serverless, which means theres no infrastructure to manage.

Data Warehouse 52

Data Warehouse Data Architecture Machine Learning Data Transformation 52

erwin

MARCH 26, 2020

Reducing the IT bottleneck that creates barriers to data accessibility. Desire for self-service to free the data consumers from strict predefined data transformations and organizations. Hybrid on-premises/cloud environments that complicate data integration and preparation.

Data-driven 90

Data-driven Unstructured Data Enterprise Machine Learning 90

AWS Big Data

OCTOBER 11, 2023

Under the Transparency in Coverage (TCR) rule , hospitals and payors to publish their pricing data in a machine-readable format. Due to this low complexity, the solution uses AWS serverless services to ingest the data, transform it, and make it available for analytics.

Visualization 110

Visualization Dashboards Data-driven Gap analysis 110

DataKitchen

OCTOBER 25, 2022

It’s because it’s a hard thing to accomplish when there are so many teams, locales, data sources, pipelines, dependencies, data transformations, models, visualizations, tests, internal customers, and external customers. That data then fills several database tables. It’s not just a fear of change.

Testing 130

Testing Data-driven Visualization Dashboards 130

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 116

Data Lake Management Metrics Data Warehouse 116

AWS Big Data

SEPTEMBER 13, 2024

To share data to our internal consumers, we use AWS Lake Formation with LF-Tags to streamline the process of managing access rights across the organization. Data integration workflow A typical data integration process consists of ingestion, analysis, and production phases.

Interactive 86

Interactive Strategy Cost-Benefit Data Governance 86

AWS Big Data

MARCH 3, 2023

It has been well published since the State of DevOps 2019 DORA Metrics were published that with DevOps, companies can deploy software 208 times more often and 106 times faster, recover from incidents 2,604 times faster, and release 7 times fewer defects. Finally, data integrity is of paramount importance.

Software 52

Software Data Lake Testing Cost-Benefit 52

Ontotext

MARCH 27, 2024

For example, a node in an LPG with a given label does not guarantee anything about its properties and data type (because it is a string and represents no semantics). LPG lacks schema and semantics, which makes it inappropriate for publishing and sharing of data. This makes LPGs inflexible.

Modeling 53

Modeling Metadata Data Quality Enterprise 53

Jet Global

FEBRUARY 23, 2024

Data mapping is essential for integration, migration, and transformation of different data sets; it allows you to improve your data quality by preventing duplications and redundancies in your data fields. Data mapping is important for several reasons.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Visualization 52

Jet Global

MAY 9, 2024

Data Extraction : The process of gathering data from disparate sources, each of which may have its own schema defining the structure and format of the data and making it available for processing. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

Jet Global

MAY 6, 2024

Thorough data preparation and control act as the foundation, allowing finance teams to leverage the full power of Oracle’s AI and transform their financial operations, now or in the future. These tools excel at data integration, consolidating information from various financial systems (ERP, CRM, legacy) into a central hub.

Finance 52

Finance Reporting Data Transformation Data-driven 52

Jet Global

AUGUST 24, 2023

It streamlines data integration, ensures real-time access to accurate information, enhances collaboration, and provides the flexibility needed to adapt to evolving ERP systems and business requirements. Data transformation ensures that the data aligns with the requirements of the new cloud ERP system.

Finance 52

Finance Reporting Data Integration Data Warehouse 52

Jet Global

MARCH 13, 2024

Complex Data Structures and Integration Processes Dynamics data structures are already complex – finance teams navigating Dynamics data frequently require IT department support to complete their routine reporting. With Atlas, you can put your data security concerns to rest.

Reporting 52

Reporting Finance Data Quality Sales 52

Jet Global

NOVEMBER 7, 2023

The alternative to BICC is BI Publisher (BIP)​. While BIP reports can be generated with different output formats, including Excel files​, BIP is not intended as a data extraction tool but rather a reporting tool.​ Quickly combine from a variety of sources into a singular data warehouse and a set of dimensional cubes or tabular models.

Enterprise 52

Enterprise Data Warehouse Operational Reporting Reporting 52

Jet Global

JULY 16, 2024

Apache Iceberg is an open table format for huge analytic datasets designed to bring high-performance ACID (Atomicity, Consistency, Isolation, and Durability) transactions to big data. It provides a stable schema, supports complex data transformations, and ensures atomic operations. What is Apache Iceberg?

Dashboards 52

Dashboards Data-driven Reporting Business Intelligence 52

Jet Global

MARCH 14, 2024

Jet streamlines many aspects of data administration, greatly improving data solutions built on Microsoft Fabric. It enhances analytics capabilities, streamlines migration, and enhances data integration. Through Jet’s integration with Fabric, your organization can better handle, process, and use your data.

Analytics 52

Analytics Management Reporting Data Quality 52

Jet Global

MAY 1, 2023

Strategic Objective Create a complete, user-friendly view of the data by preparing it for analysis. Requirement Multi-Source Data Blending Data from multiple sources is compiled and the output is a single view, metric, or visualization. Data Transformation and Enrichment Data can be enriched for analysis.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52