Remove Business Analytics Remove Dashboards Remove Data Warehouse Remove Finance
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Business Intelligence Dashboard (BI Dashboard): Best Practices and Examples

FineReport

In today’s fast-paced business environment, making informed decisions based on accurate and up-to-date information is crucial for achieving success. With the advent of Business Intelligence Dashboard (BI Dashboard), access to information is no longer limited to IT departments.

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How Macmillan Publishers authored success using IBM Cognos Analytics

IBM Big Data Hub

Data analytics in the publishing industry With such a widespread global operation, Macmillan Publishers has a long history of investing in technology that can source deep analytical information about sales, inventory and transportation of their titles in the market.

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5 Signs You’re Using Bad Data to Make Business Decisions

Jet Global

Your month end numbers aren’t adding up and your finance team is forced to manually sift through spreadsheet after spreadsheet looking for inaccuracies and h uman errors . Your resources are spread thin with the additional calculations and system workarounds put in place trying to understand the data your system is delivering .

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9 Distinct Threats to Your BI Implementation

Jet Global

Risk to the business. The mechanical solution is to build a data warehouse. The solution is to establish a process or a set of automated controls to identify bad data and block it from entering the data warehouse or BI environment. Learn how to prepare your data for BI. Just give me a dashboard.

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Master Your Power BI Environment with Tabular Models

Jet Global

The world of business analytics is evolving rapidly. 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. The first is an OLAP model.

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A Simple Data Capability Framework

Peter James Thomas

Collation of Data to provide Information. This area includes what is often described as “traditional” reporting [3] , Dashboards and analysis facilities. Data Architecture / Infrastructure. When I first started focussing on the data arena, Data Warehouses were state of the art.

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3 Ways Data Engineers Can Deal with Enterprise Data Pipelines

Sisense

The right tools and platforms that are easy to deploy, play well with legacy and modern systems, and can manage a complete end-to-end BI process, are what modern data engineers need in order to fully embrace complex data. You want to make sure you have one place to bring in all your data and do your data modeling.