The term Data Visualization loosely refers to the techniques used to communicate data or information by creating visual objects that are contained in graphics. The end goal is to communicate information clearly and efficiently to users via the information graphics selected, such as tables and charts. In his 1983 book “The Visual Display of Quantitative Information”, Professor Edward Tufte defines ‘graphical displays’ and principles for effective graphical display in the following passage: “Excellence in statistical graphics consists of complex ideas communicated with clarity, precision and efficiency. Graphical displays should: Continue reading this post>>
Why It’s a Bad Idea to Build a Business Intelligence Platform From Scratch
A friend of mine is a Python developer for a billion-dollar corporation. His team is building a custom call center reporting app that connects to the company’s cloud data storage via APIs. I’ve seen some of the application and while it’s impressive for a custom system, it’s mostly tables of numbers with the occasional pie chart. This is after 8 months of work, and the only people accessing the system are a select few big data scientists.
Believe it or not, a number of companies are doing this kind of in-house development of analytical platforms. All the hype surrounding big data has them convinced that they’re missing out on the action. Consequently, companies large and small are devoting huge amounts of time, money and human resources to developing custom business intelligence systems for big data (Google BigQuery, Hadoop, etc.) reporting rather than simply choosing a platform that already exists and is proven to work in a similar environment.
At the heart of this trend is a desire for big data to have a greater impact in the organization. Since it’s usually small teams of data scientists who are dealing with big data, their impact and effectiveness is equivalent to a small drop in a much larger body of water – their ripple effect throughout the organization is often minimal and short-lived. To extend the reach of big data in the company and get important insights out to a greater number of decision makers, a BI platform is a necessary next step – one that leverages big data insights in easily-digestible executive reports and dashboards.
Some companies are going down the road of custom BI platform development, but their efforts are no match for solutions like arcplan that are already available. Below is a list of what you’d need to do to build a BI platform from scratch. You’ll quickly see why the effort and expense aren’t worthwhile.
Scorecard & Dashboard Development: A Detailed How-To
Date: Wednesday, December 5, 2012
Time: 2:00 pm ET / 11:00 am PT
You’ll come away with well-rounded, practical knowledge about how to create best-in-class BI applications that are highly adopted and provide a stellar user experience.
In this webinar, we’ll show you real customer examples that illustrate:
- How to make your scorecards & dashboards simple, clean and effective
- Visualization trade-offs and choices
- Navigation as the key to success
- Managing the path of analysis
- Scorecards that tell a story
- And much more
We’ll also leave time for a Q&A session at the end of the webinar.
This event is a continuation of arcplan’s September webinar, Effective BI Dashboard & Scorecard Design, where we discussed the characteristics of successful dashboards. It is not a pre-requisite to have attended this webinar, but if you’d like to view the recording, you may do so here.