CIO Business Intelligence

SEPTEMBER 2, 2022

Finance companies collect massive amounts of data, and data engineers are vital in ensuring that data is maintained and that there’s a high level of data quality, efficiency, and reliability around data collection.

Finance 98

Finance IT Software Reporting 98

CIO Business Intelligence

AUGUST 31, 2022

Finance companies collect massive amounts of data, and data engineers are vital in ensuring that data is maintained and that there’s a high level of data quality, efficiency, and reliability around data collection.

Finance 98

Finance IT Software Reporting 98

CIO Business Intelligence

MARCH 24, 2023

The Business Application Research Center (BARC) warns that data governance is a highly complex, ongoing program, not a “big bang initiative,” and it runs the risk of participants losing trust and interest over time.

Data Governance 142

Data Governance Management Metadata Data Quality 142

O'Reilly on Data

NOVEMBER 13, 2018

At the recent Strata Data conference we had a series of talks on relevant cultural, organizational, and engineering topics. Here's a list of a few clusters of relevant sessions from the recent conference: Data Integration and Data Pipelines. Data Platforms. Model lifecycle management.

Machine Learning 224

Machine Learning Risk Management Statistics 224

datapine

FEBRUARY 22, 2022

Improved risk management: Another great benefit from implementing a strategy for BI is risk management. IT should be involved to ensure governance, knowledge transfer, data integrity, and the actual implementation. Because it is that important. Think of security, privacy, and compliance.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

Jet Global

NOVEMBER 29, 2023

To be considered, product capabilities must include close management, financial consolidation, financial statement reconciliation and journal entry processing. Optional capabilities include financial reporting risk management and disclosure management. Extensive Data Integration.

Reporting 52

Reporting Marketing Software Management 52

Jet Global

MAY 9, 2024

Batch processing pipelines are designed to decrease workloads by handling large volumes of data efficiently and can be useful for tasks such as data transformation, data aggregation, data integration , and data loading into a destination system. What is the difference between ETL and data pipeline?

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52