Smart Data Collective

OCTOBER 19, 2022

What Are Their Ranges of Data Models? MongoDB has a wider range of datatypes than DynamoDB, even though both databases can store binary data. DynamoDB is limited to 400KB for documents and MongoDB can support up to 16MB file sizes. But MongoDB also offers filesystem snapshot backups and queryable backups.

Big Data 112

Big Data Management Cost-Benefit Recreation/Entertainment 112

FineReport

JUNE 14, 2023

Key Performance Indicators (KPIs) serve as vital metrics that help measure progress towards business goals. What is a KPI report？ A KPI report, also known as KPI reporting, serves as a management tool for measuring, organizing, and analyzing the primary key performance indicators that are vital to a business.

KPI 52

KPI Reporting Key Performance Indicator Sales 52

O'Reilly on Data

MARCH 20, 2019

Data integrity constraints: Many databases don’t allow for strange or unrealistic combinations of input variables and this could potentially thwart watermarking attacks. Applying data integrity constraints on live, incoming data streams could have the same benefits. Disparate impact analysis: see section 1.

Modeling 227

Modeling Machine Learning Predictive Modeling Consulting 227

FineReport

JUNE 26, 2023

Serving as foundational documents : Performance reports serve as the groundwork for other reports and documentation. Internal performance reports serve as a fundamental source for preparing external reports and documents, given that the required data is already collected.

Reporting 52

Reporting Key Performance Indicator Sales Visualization 52

AWS Big Data

MARCH 3, 2023

Additionally, the scale is significant because the multi-tenant data sources provide a continuous stream of testing activity, and our users require quick data refreshes as well as historical context for up to a decade due to compliance and regulatory demands. Finally, data integrity is of paramount importance.

Software 52

Software Data Lake Testing Cost-Benefit 52

DataKitchen

JANUARY 23, 2023

DataOps Observability includes monitoring and testing the data pipeline, data quality, data testing, and alerting. Data testing is an essential aspect of DataOps Observability; it helps to ensure that data is accurate, complete, and consistent with its specifications, documentation, and end-user requirements.

Testing 130

Testing Data Governance Data Quality Data-driven 130