IBM Big Data Hub

SEPTEMBER 11, 2023

Government executives face several uncertainties as they embark on their journeys of modernization. A pain point tracker (a repository of business, human-centered design and technology issues that inhibit users’ ability to execute critical tasks) captures themes that arise during the data collection process.

Data-driven 86

Data-driven IT Measurement Cost-Benefit 86

Jet Global

NOVEMBER 15, 2019

Despite the fact that massive amounts of information lives inside this solution, PeopleSoft reporting is a cumbersome process, mostly because the data are poorly integrated. Members of the finance or IT teams have to go hunting through multiple data sources, identifying and integrating the metrics they need to build reports.

Reporting 75

Reporting Uncertainty Metrics Finance 75

Jet Global

JANUARY 22, 2020

Much of the financial reporting process, including data collection, integration, analysis, and visualization, can now run on autopilot. They’ve identified their most important performance metrics and report on those at the exclusion of all others. All of this is possible thanks to breakthroughs in automation.

Reporting 78

Reporting Snapshot Data-driven Uncertainty 78

Darkhorse

MARCH 31, 2015

Add to these all of the decisions that they could be making (but aren’t) because of uncertainty or laziness. Step 3: Scope the Projects In looking at what remains, you can start to estimate the difficulty or uncertainty associated with finding a solution. Step 1: The Brain Storm We start at the end: the decision.

Uncertainty 45

Uncertainty Data-driven Consulting Metrics 45

Domino Data Lab

JUNE 23, 2019

Companies with successful ML projects are often companies that already have an experimental culture in place as well as analytics that enable them to learn from data. Ensure that product managers work on projects that matter to the business and/or are aligned to strategic company metrics. That’s another pattern.

Management 110

Management Machine Learning Experimentation Metrics 110

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. How could that make sense?

Data Science 109

Data Science Machine Learning Data Governance Modeling 109