Jet Global

OCTOBER 22, 2020

The size and scope of business databases have grown as ERP functionality has evolved, businesses have increased their adoption of CRM and marketing automation, and collaboration networks have become more common. OLAP Cubes vs. Tabular Models. Let’s begin with an overview of how data analytics works for most business applications.

Modeling 52

Modeling OLAP Reporting Sales 52

Jet Global

JUNE 5, 2019

Data drives everything in the business world, from manufacturing to supply chain logistics to retail sales to customer experience to post-sale marketing and beyond, data holds the secrets to making processes more efficient, production costs cheaper, profit margins higher and marketing campaigns more effective.

Data mining 75

Data mining Business Intelligence OLAP Key Performance Indicator 75

FineReport

JULY 16, 2021

Among these problems, one is that the third party on market data analysis platform or enterprises’ own platforms have been unable to meet the needs of business development. When we talk about business intelligence system, it normally includes the following components: data warehouse BI software Users with appropriate analytical.

Business Intelligence 98

Business Intelligence Informatics Data Warehouse Data mining 98

Jet Global

DECEMBER 3, 2021

The term “ business intelligence ” (BI) has been in common use for several decades now, referring initially to the OLAP systems that drew largely upon pre-processed information stored in data warehouses. Sales and customer service interactions are tracked in CRM. Spot Problems (and Opportunities) Early.

Business Intelligence 52

Business Intelligence Sales OLAP Data Warehouse 52

Jet Global

APRIL 20, 2020

CRM software has gone through a similar transformation, starting with sales force automation, and more recently evolving into a new breed of products that support digital marketing campaigns through email, social media, and online advertising. Over the past few decades, however, technology has been closing that gap.

Business Intelligence 78

Business Intelligence Finance Data Warehouse OLAP 78

Jet Global

DECEMBER 1, 2020

Furthermore, it can be challenging to draw the proper connections between header tables (for example, the table that contains one record per sales invoice) and the associated detail tables (for example, the line item details associated with each of those invoices). Those systems contain valuable information.

Finance 78

Finance Data Warehouse OLAP Reporting 78

Octopai

JANUARY 8, 2020

With metadata queries, you can account for all appropriate inputs to your sales and inventory forecasts (among others). Even if new data sources go-live mid-year, your automated metadata discovery can uncover the data needed for spot-on forecasts before the enterprise stakeholders ask for them.

Metadata 54

Metadata Key Performance Indicator OLAP Forecasting 54

Jet Global

JANUARY 15, 2021

Why not take that opportunity to look around at the offerings from SAP, Sage, Epicor, Acumatica, or any of the other leading ERP vendors on the market? In many respects, it is more akin to some of the very complex data warehousing and OLAP tools of the past–perhaps with an even steeper learning curve.

Cost-Benefit 72

Cost-Benefit Data Lake Reporting OLAP 72

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