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Data Visualization Basics
This article provides an overview of high-level "data visualization" and is divided into the following sections:

Definition of viewing the display of dati.Scopo dati.Il role of data visualization within a stack of Business Intelligence.Definizione

Data Visualization:

The term "data visualization" is self-descriptive, meaning that literally means the data display. The information is displayed in a clear and graphical user interface, which can then assimilate and interpret data quickly. Of course, this interpretation occurs as efficient depends on how the data were analyzed and displayed.
Purpose

Data Visualization:.

The purpose of data visualization is to communicate information in a clear, concise, graphical way intended for an audience

Almost all companies are dealing with a huge amount of raw data, and make intelligent business decisions depends on how a company that analyzes and interprets the data. And 'possible to examine data in a text format such as tables and spreadsheets, however, this tends to be overwhelming for the analyst, as well as difficult to interpret. Major trends can be identified, resulting in poor decision-making business. This is where data visualization comes to the rescue: large amounts of data can be displayed (via dashboards, scorecards, graphs, dials, maps, gauges, graphs and other visual elements) and almost instantly absorbed by the user. Major trends can be quickly identified, thereby resulting in intelligent business decisions.

The old adage "a picture is worth a thousand words" says it all!

The stack of Business Intelligence and Data Visualization:

data display is actually a component of "business intelligence stack." Business intelligence refers to technological methods of collection, manipulation and analysis of business data. The "stack" refers to the following components used to achieve these objectives:

1. Level of presentation:

It consists of various methods used to display data for the user finale.Strumenti display data and the elements are: ....
I. Performance Dashboards
ii digital scorecard
iii Charts, graphs and indicators.

2. Layer Analytics:

The layer of analysis is where the data is massaged and manipulated into a format that can be viewed and analyzed visivamente.Aspetti significantly at this level include predictive analytics, data mining, KPIs (key performance indicators) as well as creating the BI tools third party.

Data Layer:

The data layer consists of all the sources that contain data that are often sourced from analizzati.Dati OLAP, MS SQL, MySQL and Oracle, and even spreadsheets such as Microsoft Excel.

From the information above you can see that the data display is at the top of the stack of BI. It should be noted that all three layers are critical when it comes to making good decisions using Business Intelligence. Present a well-designed dashboards for end users is of little value if the data you are viewing is poorly organized. In contrast, watching a poorly designed dashboard is of little value even if the data you are viewing has been mined and well-organized.

In conclusion, the visualization of data is extremely important when making smart business decisions. If properly executed, mass quantities of data can be analyzed and interpreted quickly and efficiently, which is a good thing when it comes to some sort of business management



Martin Eising is currently working with Dundas Data Visualization.

Dundas Data Visualization is a world leader in data visualization and dashboard solutions. The company's products include Dundas Dashboard, an easy to integrate, turnkey solution for creating dashboard.