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 108

Data Lake Management Metrics Data Warehouse 108

Smart Data Collective

OCTOBER 13, 2021

There are countless examples of big data transforming many different industries. There is no disputing the fact that the collection and analysis of massive amounts of unstructured data has been a huge breakthrough. Multi-channel publishing of data services. Does Data Virtualization support web data integration?

Visualization 135

Visualization Cost-Benefit Big Data Prescriptive Analytics 135

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 Finance 90

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 Optimization 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 Risk 52

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 Sales 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

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

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 Enterprise 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