Decision Management Solutions

JUNE 4, 2021

Like many enterprises, you’ve likely made a hefty investment in analytic technology—from interactive dashboards and advanced visualization tools to data mining, predictive analytics, machine learning (ML), and artificial intelligence (AI). Limitations of common approaches to analytic projects.

Analytics Technologies 52

Analytics Technologies Technology Modeling Key Performance Indicator 52

BizAcuity

APRIL 28, 2019

is delinquent as of June 30th, 2017. Today, it’s no secret that most forward-thinking businesses are keenly following the latest developments on big data, artificial intelligence, machine learning, and predictive analytics. And this data is crucial in taking the necessary steps to ensure successful debt collection.

Predictive Analytics 98

Predictive Analytics Analytics Big Data Data mining 98

bridgei2i

JULY 28, 2020

She’s the founder and CEO of StatWeather, a company, which was recognized as number one in climate technology globally in the year, 2017, by the Energy Risk Awards. In my company StatWeather we use this kind of data and data mining to forecast weather and climate patterns, which has been very successful.

Enterprise 98

Enterprise Digital Transformation Insurance B2B 98

Occam's Razor

SEPTEMBER 15, 2014

Remember, when someone says mobile analytics, first ask the clarifying question: Do you mean mobile application or mobile website ? Then approach each separately (even though there are tools like Google Analytics that will do both). In Google Analytics there are five parameters: Source, Medium, Campaign, Term and Content.

Metrics 141

Metrics Reporting Analytics Marketing 141

datapine

NOVEMBER 27, 2019

Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. The rise of self-service analytics democratized the data product chain. Suddenly advanced analytics wasn’t just for the analysts. 1) Data Quality Management (DQM).

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Alation

AUGUST 26, 2021

Why keep data at all? Answering these questions can improve operational efficiencies and inform a number of data intelligence use cases, which include data governance, self-service analytics, and more. Data Intelligence: Origin, Evolution, Use Cases. Examples of Data Intelligence use cases include: Data governance.

Metadata 64

Metadata Data Governance Dashboards Software 64