Ontotext

JANUARY 10, 2024

Often, an enterprise starts with one thing it does well and then adds more business lines to expand the market. Any type of metadata or universal data model is likely to slow down development and increase costs, which will affect the time to market and profit.

Metadata 72

Metadata Slice and Dice Data Integration Enterprise 72

IBM Big Data Hub

JULY 6, 2023

Businesses need to demonstrate with clear data and examples on how they are integrating fundamental principles in their key processes and measuring these decisions through KPIs. This data can be sliced and diced to align to the needs of multiple reporting frameworks as required. The above helps improve reporting efficiency.

Reporting 54

Reporting Slice and Dice Insurance Metrics 54

Jet Global

DECEMBER 2, 2019

Alone, the optimized environment data warehouse is a valuable asset to any BI initiative; however, the data is still two-dimensional (table/field format) and does not contain any calculated measures or KPIs. OLAP cubes do all the work by dimensionalizing all combinations of slicing and dicing the data ahead of time.

Business Intelligence 69

Business Intelligence Reporting OLAP Data Warehouse 69

Occam's Razor

JULY 15, 2014

You need access to data, the ability to analyze (slice, dice, drill-up, drill-down, drill-around) interesting data points that your performance throws up, ability to understand what caused the performance (often by understanding who did, what and where in other parts of the organization), and the power to make decisions.

Dashboards 159

Dashboards Key Performance Indicator Snapshot Slice and Dice 159

Occam's Razor

APRIL 19, 2010

The post will end with a Web Analytics Measurement Framework. Improve marketing effectiveness. Improve marketing effectiveness might translate into these goals because currently they are our priorities: 1. Point of confusion: Many web analytics tools, like Google Analytics , have a feature that encourages you to measure Goals.

Metrics 138

Metrics Key Performance Indicator KPI Business Objectives 138

Sisense

JANUARY 6, 2020

BI and analytics is used across multiple functions: marketing, sales, customer success, product, distribution, operations and logistics to name a few. This is not to say that data modeling should be focused specifically on sales. Key ways to optimize insights for sales.

Sales 91

Sales Forecasting Snapshot Management 91

AWS Big Data

FEBRUARY 28, 2023

Such analysis can provide insight into customer preferences and behavior, which can be used to inform marketing strategies and product development. This feature helps us clearly understand the aggregation grain, slice and dice data, and apply filters when business users are performing analysis.

Online Analytical Processing 72

Online Analytical Processing OLAP Slice and Dice Analytics 72

Occam's Razor

FEBRUARY 10, 2016

Yet, few Marketers or executives take them seriously (because they don't know what the heck all that means to the business or their own paychecks!). Hence, analytics framework to represent end-to-end business measurement is called Acquisition – Behavior – Outcomes. We see this everyday. "Analysts"

Analytics 80

Analytics Metrics Key Performance Indicator Slice and Dice 80

Occam's Razor

JANUARY 7, 2014

4: The Analytics/Marketing skills in your Analysis Ninjas is 70/30. #3. The organization functions off a clearly defined Digital Marketing & Measurement Model. #1. Digital Analyst, Web Analysis Guru, Digital Marketing Analyst, so on and so forth. Four Useless KPI Measurement Techniques. #9:

Data-driven 140

Data-driven Consulting Reporting Marketing 140

Jet Global

MAY 12, 2023

To keep up with the demands that digital innovations place upon product markets, businesses are increasingly incorporating analytics into their products. Product Analytics Defined Product analytics tools help product teams and managers measure the success of their digital products.

Analytics 52

Analytics Slice and Dice Sales Cost-Benefit 52

Jet Global

MAY 1, 2023

Section 2: Embedded Analytics: No Longer a Want but a Need Section 3: How to be Successful with Embedded Analytics Section 4: Embedded Analytics: Build versus Buy Section 5: Evaluating an Embedded Analytics Solution Section 6: Go-to-Market Best Practices Section 7: The Future of Embedded Analytics Section 1: What are Embedded Analytics?

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52