Remove Data Warehouse Remove Embedded Analytics Remove Finance
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Data and Analytics — the Foundation of Successful Apps

Sisense

The smart ones are finding new ways to monetize their data, either by embedding analytics into apps and services that existing users will pay for or using them to grow their audience and expand into new markets. Not a problem for engineers, but a huge barrier for business analysts and other data-savvy, but non-technical staff.”.

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How Profectus Delivers Value from Data

Sisense

For Profectus, data is absolutely everything. From accounts payable data coming in as direct feeds from ERP finance systems, to hundreds of thousands of invoices Profectus’ solutions ingest on behalf of its customers, along with any agreement data that their customers have with their suppliers.

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Why Not Embrace the Advantages of Self-Serve BI Tools?

ElegantJ BI

that will provide the foundational data for your users.

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Why Not Embrace the Advantages of Self-Serve BI Tools?

ElegantJ BI

that will provide the foundational data for your users.

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What Is Embedded Analytics?

Insight Software

Introduction Why should I read the definitive guide to embedded analytics? But many companies fail to achieve this goal because they struggle to provide the reporting and analytics users have come to expect. The Definitive Guide to Embedded Analytics is designed to answer any and all questions you have about the topic.

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2024 Embedded Analytics Round-Up

Insight Software

2024 has been an exciting year in the world of embedded analytics and business intelligence. From self-service to AI-powered analytics, organizations are leveraging embedding analytics to set themselves apart from the competition. Here, we share our embedded analytics highlights from 2024.

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What is a Data Pipeline?

Insight Software

The key components of a data pipeline are typically: Data Sources : The origin of the data, such as a relational database , data warehouse, data lake , file, API, or other data store. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.