This is a Part 1 of surprise Guest post. My guest is Ugur Kadakal, Ph.D., he is the CEO and founder of Pagos, Inc., which he started almost 10 years ago.
Dr. Kadakal is an expert in Excel, Business Intelligence, Data Analytics and Data Visualization. His comprehensive knowledge of Excel, along with his ambitious inventions and ideas, supply the foundation for all Pagos products, which include SpreadsheetWEB (which converts Excel spreadsheets into web applications), SpreasheetLIVE (a fully-featured, browser-based spreadsheet application environment) and Pagos Spreadsheet Component (which integrates Excel spreadsheets into enterprise web applications).
Pagos started and hosted the largest free collection and repository of professional templates of Excel spreadsheets on the web: http://spreadsheetzone.com . 3 Excel-based Dashboard below can be found on this very popular repository and done by Dr. Kadakal:
Dashboard 1 : Human Resources Dashboard: http://spreadsheetzone.com/templateview.aspx?i=498
Dashboard 2 : Business Activity Dashboard in EuroZone: http://spreadsheetzone.com/templateview.aspx?i=490
Dashboard 3 : Energy Dashboard for Euro Zone: http://spreadsheetzone.com/templateview.aspx?i=491
The topic is large, so this Guest article is splitted on 3 blog posts. The first portion of article contains the Introduction and Part 1 “Use of Excel as a BI Platform Today“, then I expect Dr. Kadakal will do at least 2 more posts: Part 2 – “Dos and Don’ts of building dashboards in Excel“, Part 3 – “Moving Excel dashboards to the Web“.
Excel as a Business Intelligence Platform – Part 1
Electronic spreadsheets were one of the very first Business Intelligence (BI) software. While the availability of spreadsheet software and it use as a tool for data analysis dates back to the 1960s, its application in the BI field began with the integration of OLAP and pivot tables. In 1991, Lotus released Improve, followed by Microsoft’s release of PivotTable in 1993. However, Essbase was the first scalable OLAP software to handle large data sets that the early spreadsheet software was incapable of. This is where its name comes from: Extended Spread Sheet Database.
There is no doubt that Microsoft Excel is the most commonly used software for BI purposes. While Excel is general business software, its flexibility and ease of use makes it popular for data analysis with millions of users worldwide. Excel has an install base of hundreds of millions of desktops: far more than any other BI platform. It has become a household name. From educational utilization to domestic applications and enterprise implementation, Excel has been proven incredibly indispensable. Most people with commercial or corporate backgrounds have developed a proficient Excel skillset. This makes Excel the ultimate self-service BI platform. However, like all systems, Excel has some weaknesses that make it difficult to use as a BI tool under certain conditions.
Use of Excel as a BI Platform Today
Traditionally, small businesses are not considered as an important market segment by most BI vendors. Their data analysis and reporting needs are limited primarily due to their smaller commercial volumes. However, this is changing quickly as smaller organizations begin to collect large amounts of data, thanks to the Internet and social media, and require tools to manage that data. However, what is not changing is the limited financial resources available to them. Small businesses cannot spare to spend large amounts of money on BI software or consultants to aid them in the creation of the applications. That’s why Excel is the ideal platform for them and will most probably remain that way for a foreseeable future. The reasons are clear: (1) most of them already have Excel licenses, (2) most of their users know how to use Excel and (3) their needs are simpler and can be met with Excel.
Mid-range businesses are a quickly growing market segment for BI vendors. Traditionally, Excel as a BI platform has been more popular among these businesses. Cost and availability are the primary factors in this. However, two aspects have been steering them to searching for alternatives: (1) Excel can no longer handle their growing data volumes and (2) other BI vendors started offering cost-effective alternatives.
As a result, Excel’s market share in this field is in decline although it still remains the most popular. On the other hand, with the release of Office 2010 and its extended capabilities for handling very large data sets, Excel stands a good chance at reversing this decline.
The situation with large enterprises is rather complex. Most of them already have large-scale a BI implementation in place. Those implementations often connect various databases and data warehouses within the organizations. They have made significant investments and continue doing so to expand and maintain their BI systems. They already have a number of dashboards and reports designed to serve their business units. However, business users always need new and different dashboards and reporting tools. The only software that gives them the ultimate flexibility in creating their own reports is Excel. As a result, even in large Enterprises, usage of Excel for BI purposes is common. Business users often go to their data warehouses or BI tools and get a data extract to bring into Excel. They can then prepare their analysis and build their reports in Excel.
Enterprises will continue using their existing platforms because they have made huge investments building those systems. However, Excel use by business users as their secondary BI and reporting tool will continue to rise unless the alternative vendors significantly improve their self-servicing capabilities.
Excel is one of the ultimate business platforms and offers unparalleled features and capabilities to non-programmers. This makes it an ideal self-service BI platform. In this article, we examined the use of Excel as a BI platform in companies of different sizes. In the next article of this series, we will discuss how to use Excel more efficiently as a BI platform, from handling data to calculations and visual interactions.