DataKitchen

SEPTEMBER 21, 2023

Bridging the Gap: How ‘Data in Place’ and ‘Data in Use’ Define Complete Data Observability In a world where 97% of data engineers report burnout and crisis mode seems to be the default setting for data teams, a Zen-like calm feels like an unattainable dream. What is Data in Use?

Testing 169

Testing Data Quality Predictive Modeling Metrics 169

Jet Global

NOVEMBER 16, 2021

Logistics KPIs can measure a variety of metrics, most of which pertain to purchasing, warehousing, transportation, delivery of goods, and financials. Logistics KPIs can measure a variety of metrics, most of which pertain to purchasing, warehousing, transportation, delivery of goods, and financials. How to Build Useful KPI Dashboards.

Metrics 84

Metrics Reporting Key Performance Indicator KPI 84

Jet Global

JANUARY 5, 2021

Although Microsoft’s rollout of its two ERP cloud products (D365 F&SCM, and for smaller businesses, D365 Business Central) has been going on for some time, the current climate of economic uncertainty has prompted a lot of companies to hit the pause button on migration, choosing instead to stay the course with their existing Dynamics AX systems.

Reporting 98

Reporting Data Warehouse Finance Cost-Benefit 98

AWS Big Data

AUGUST 7, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. Tens of thousands of customers use Amazon Redshift to process exabytes of data every day to power their analytics workloads. Forecasting acts as a planning tool to help enterprises prepare for the uncertainty that can occur in the future.

Forecasting 86

Forecasting Data Warehouse Machine Learning Modeling 86

Jet Global

NOVEMBER 7, 2023

If any one word could encapsulate 2023, it would be “uncertainty.” Cash metrics and liquidity show a company’s ability to weather financial challenges and satisfy its short-term obligations, both attractive qualities for investors during uncertain economic times.

Finance 52

Finance Uncertainty Reporting Marketing 52

Domino Data Lab

JULY 22, 2019

He also really informed a lot of the early thinking about data visualization. It involved a lot of interesting work on something new that was data management. It involved a lot of work with applied math, some depth in statistics and visualization, and also a lot of communication skills. Then we roll out a decade later.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109