AWS Big Data

MARCH 26, 2024

Plan on how you can enable your teams to use ML to move from descriptive to prescriptive analytics. The AWS modern data architecture shows a way to build a purpose-built, secure, and scalable data platform in the cloud. Learn from this to build querying capabilities across your data lake and the data warehouse.

Data Strategy 92

Data Strategy Strategy Data Warehouse Prescriptive Analytics 92

Sisense

JUNE 30, 2020

Broadly, there are three types of analytics: descriptive , prescriptive , and predictive. The simplest type, descriptive analytics , describes something that has already happened and suggests its root causes. This data is gathered into either on-premises servers or increasingly into cloud data warehouses and data lakes.

Visualization 93

Visualization Analytics Dashboards Data-driven 93

Birst BI

OCTOBER 30, 2018

This may involve integrating different technologies, like cloud sources, on-premise databases, data warehouses and even spreadsheets. Add the predictive logic to the data model. With the source data now fully integrated into an analytic model, add and test different predictive algorithms.

Predictive Analytics 73

Predictive Analytics Descriptive Analytics Analytics Metrics 73

Cloudera

MARCH 2, 2018

Achieve best possible outcomes for individuals through the application of prescriptive analytics. There are many possible use cases for prescriptive analytics in the development sector, particularly in health where we have much existing data on what works in light of specific risk factors.

Data-driven 43

Data-driven Prescriptive Analytics Machine Learning Descriptive Analytics 43

Smarten

NOVEMBER 26, 2023

TechTarget defines business intelligence this way: ‘Business intelligence (BI) is a technology-driven process for analyzing data and delivering actionable information that helps executives, managers and workers make informed business decisions.’

Marketing 40

Marketing Business Intelligence Key Performance Indicator Prescriptive Analytics 40

IBM Big Data Hub

JULY 6, 2023

Data from various sources, collected in different forms, require data entry and compilation. That can be made easier today with virtual data warehouses that have a centralized platform where data from different sources can be stored. One challenge in applying data science is to identify pertinent business issues.

Machine Learning 54

Machine Learning Data Science Statistics Deep Learning 54

CDW Research Hub

SEPTEMBER 15, 2020

Creating a modern data platform that is designed to support your current and future needs is critical in a data-driven organization. Business leaders need to be able to quickly access data—and to trust the accuracy of that data—to make better decisions. Easy Access with a Secure Foundation.

Business Intelligence 52

Business Intelligence Prescriptive Analytics Unstructured Data Data Warehouse 52

Andrew White

JANUARY 11, 2021

See recorded webinars: Emerging Practices for a Data-driven Strategy. Data and Analytics Governance: Whats Broken, and What We Need To Do To Fix It. Link Data to Business Outcomes. Does Data warehouse as a software tool will play role in future of Data & Analytics strategy?

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

Alation

AUGUST 26, 2021

Augmented Analytics. DI empowers analysts to apply augmented analytics to applications, supporting predictive and prescriptive analytics use cases. Some examples of goals and accompanying use cases include: The business wants to make better use of customer data. Does it govern the data as it migrates?

Metadata 64

Metadata Data Governance Dashboards Software 64

Smarten

SEPTEMBER 9, 2024

What is a Cititzen Data Scientist? Gartner defines a citizen data scientist as, ‘ a person who creates or generates models that leverage predictive or prescriptive analytics, but whose primary job function is outside of the field of statistics and analytics.’ Who is a Citizen Data Scientist?

Consulting 52

Consulting Cost-Benefit Data Science Business Intelligence 52

Jet Global

MAY 1, 2023

These sit on top of data warehouses that are strictly governed by IT departments. The role of traditional BI platforms is to collect data from various business systems. Predictive Analytics: If x, then y (e.g., Prescriptive Analytics: Here’s what to do to achieve a desired outcome (e.g.,

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52